This four-day course is designed for SONAR systems engineers, combat systems engineers, undersea warfare professionals, and managers who wish to enhance their understanding of passive and active SONAR or become familiar with the "big picture" if they work outside of either discipline. Each topic is presented by instructors with substantial experience at sea. Presentations are illustrated by worked numerical examples using simulated or experimental data describing actual undersea acoustic situations and geometries. Visualization of transmitted waveforms, target interactions, and detector responses is emphasized.
NAVIC (Navigation with Indian Constellation) is an Operational name of IRNSS.
Independent Indian Regional Navigation Satellite System
provide accurate position information service to users in India as well as the region extending up to 1500 km from its boundary.
In this Programme there are two levels of service/access to data
1. Standard Positioning Service (SPS)
-which is provided to all the users
2. Restricted Service (RS)
- which is an encrypted service provided only to the authorised users like Indian Security forces.
• NAVIC has total of 7 satellites of which 3 are in GEO (GeoStationary) orbit and 4 are in GSO (GeoSynchronous) orbit.
10 range and doppler measurements in radar systemsSolo Hermelin
Present method of Range and Doppler measurement in a RADAR system.
For comments please contact me at solo.hermelin@gmail.com.
For more presentations on different subjects visit my website at http://www.solohermelin.com.
Recommend to view this presentation on my website in power point.
NAVIC (Navigation with Indian Constellation) is an Operational name of IRNSS.
Independent Indian Regional Navigation Satellite System
provide accurate position information service to users in India as well as the region extending up to 1500 km from its boundary.
In this Programme there are two levels of service/access to data
1. Standard Positioning Service (SPS)
-which is provided to all the users
2. Restricted Service (RS)
- which is an encrypted service provided only to the authorised users like Indian Security forces.
• NAVIC has total of 7 satellites of which 3 are in GEO (GeoStationary) orbit and 4 are in GSO (GeoSynchronous) orbit.
10 range and doppler measurements in radar systemsSolo Hermelin
Present method of Range and Doppler measurement in a RADAR system.
For comments please contact me at solo.hermelin@gmail.com.
For more presentations on different subjects visit my website at http://www.solohermelin.com.
Recommend to view this presentation on my website in power point.
Design & Study of Microstrip Patch Antenna.The project here provides a detailed study of how to design a probe-fed Square Micro-strip Patch Antenna using HFSS, v11.0 software and study the effect of antenna dimensions Length (L), and substrate parameters relative Dielectric constant (εr), substrate thickness (t) on the Radiation parameters of Bandwidth and Beam-width.
This presentation covers:
Basics of Satellite communication
Indian Communication satellites
Satellite link and elements of satellite communication
Frequency bands of satellite communication
Different orbits of satellite communication
Link budget calculations
Microwave experiments
Reflex Klystron Characteristics
Study of Horn Antenna
Study of Directional Coupler
Frequency and wavelength measurement
VSWR Measurement
Impedance Measurement
Study of Isolator
Gunn diode characteristics
Lidar is an acronym for light detection and ranging. It is an optical remote sensing technology that can measure the distance to, or other properties of a target by illuminating the target with light, often using pulses from a laser.
Propagation Effects and Their Impact on Satellite-Earth Links: Introduction,
Quantifying attenuation and depolarization,
Propagation effects that are not associated with hydrometeors, Prediction of rain attenuation,
Prediction of XPD,
Propagation impairments countermeasures.
Harvesting of wave energy and converting it into electrical energy is the subject of worldwide efforts for many years. In light of the cost of electricity production from fossil fuels, (for example electricity generated by large scale coal burning power plants costs about 2.6 cents per kilowatt-hour), the target-cost for wave power production is 5 cents per kilowatt-hour or lower, equal to the wind turbine power production cost. However, we must point out two important factors that are missing from the cost of burning fossil fuels; a) the cost of environmental destruction and b) that the fossil fuels on the planet do not last forever. On the other hand in very industrialized countries like Japan, the energy consumption is less than 1% of solar energy reaching the surface of these countries. Therefore, it is very comprehensible the need to utilize the primary and secondary solar energy offered to us profusely and forever. In particular, the net resource (minus "costs") of wave energy is equal to or better than the resources of wind, solar, small hydro plants, or biomass energy. Thus, the use of the wave ocean energy remains a major challenge for many years.
The innovative concept of the proposed converter by HWET is aimed to low cost electric power production. The converter is a linear type attenuator. Unlike any known machine so far its operation is based in the mediation of water between sea waves and a chain from pairs of buoys. Both the mediated water and the buoys are enclosed in a hermetically sealed "floating tube". As the tube interacts with the waves, the buoys are moving up and down and by means of proper transmission mechanism they activate an electric generator enclosed also in the "floating tube". The development and commercialization of a low cost converter for exploitation of the enormous wave energy potential, is beneficial not only for countries with high wave energy potential, but even for countries with moderate wave energy potential and long coast line, as for example, Greece, Japan, etc. Therefore, an ambitious project leading to the development of a low-cost wave-energy converter is a challenge and any possible joint venture would be very welcomed.
Contact: alexandrosanastassiadis@gmail.com
Animations: http://youtu.be/33nXbjlpam4
Design & Study of Microstrip Patch Antenna.The project here provides a detailed study of how to design a probe-fed Square Micro-strip Patch Antenna using HFSS, v11.0 software and study the effect of antenna dimensions Length (L), and substrate parameters relative Dielectric constant (εr), substrate thickness (t) on the Radiation parameters of Bandwidth and Beam-width.
This presentation covers:
Basics of Satellite communication
Indian Communication satellites
Satellite link and elements of satellite communication
Frequency bands of satellite communication
Different orbits of satellite communication
Link budget calculations
Microwave experiments
Reflex Klystron Characteristics
Study of Horn Antenna
Study of Directional Coupler
Frequency and wavelength measurement
VSWR Measurement
Impedance Measurement
Study of Isolator
Gunn diode characteristics
Lidar is an acronym for light detection and ranging. It is an optical remote sensing technology that can measure the distance to, or other properties of a target by illuminating the target with light, often using pulses from a laser.
Propagation Effects and Their Impact on Satellite-Earth Links: Introduction,
Quantifying attenuation and depolarization,
Propagation effects that are not associated with hydrometeors, Prediction of rain attenuation,
Prediction of XPD,
Propagation impairments countermeasures.
Harvesting of wave energy and converting it into electrical energy is the subject of worldwide efforts for many years. In light of the cost of electricity production from fossil fuels, (for example electricity generated by large scale coal burning power plants costs about 2.6 cents per kilowatt-hour), the target-cost for wave power production is 5 cents per kilowatt-hour or lower, equal to the wind turbine power production cost. However, we must point out two important factors that are missing from the cost of burning fossil fuels; a) the cost of environmental destruction and b) that the fossil fuels on the planet do not last forever. On the other hand in very industrialized countries like Japan, the energy consumption is less than 1% of solar energy reaching the surface of these countries. Therefore, it is very comprehensible the need to utilize the primary and secondary solar energy offered to us profusely and forever. In particular, the net resource (minus "costs") of wave energy is equal to or better than the resources of wind, solar, small hydro plants, or biomass energy. Thus, the use of the wave ocean energy remains a major challenge for many years.
The innovative concept of the proposed converter by HWET is aimed to low cost electric power production. The converter is a linear type attenuator. Unlike any known machine so far its operation is based in the mediation of water between sea waves and a chain from pairs of buoys. Both the mediated water and the buoys are enclosed in a hermetically sealed "floating tube". As the tube interacts with the waves, the buoys are moving up and down and by means of proper transmission mechanism they activate an electric generator enclosed also in the "floating tube". The development and commercialization of a low cost converter for exploitation of the enormous wave energy potential, is beneficial not only for countries with high wave energy potential, but even for countries with moderate wave energy potential and long coast line, as for example, Greece, Japan, etc. Therefore, an ambitious project leading to the development of a low-cost wave-energy converter is a challenge and any possible joint venture would be very welcomed.
Contact: alexandrosanastassiadis@gmail.com
Animations: http://youtu.be/33nXbjlpam4
This PowerPoint describes briefly about the ultrasonic absorption technique. I briefly discussed the various techniques and theoretical concepts involved in the absorption technique.
TOPICS COVERED:-
How SONAR works
Factors that affect the performance of a sonar unit
Factors that affect underwater acoustic propagation
in the ocean
Principles of sonar
Application of sonar.
Significance of frequency
Conclusion…
UNDER WATER NOISE REDUCTION USING WAVELET AND SAVITZKY-GOLAYcsandit
A precise, linear indication of the depth of water in a specific part of water body is what always
required. Presently there are a wide variety of ways to produce a signal that tracks the depth of
water.The Ultrasonic signal is most commonly used for the depth estimation. This signal is
affected by various underwater noises which results in inaccurate depth estimation. The
objective of this paper is to provide noise reduction methods for underwater acoustic signal.In
present work, the signal processing is done on the data collected using TC2122 dual frequency
transducer along with the Navisound 415 echo sounder. There are two signal processing
techniques which are used: The first method is denoising algorithm based on Stationary wavelet
transform (SWT)and second method is Savitzky-Golay filter. The results are evaluated based on
the criteria of peak signal to noise ratio and 3D Surfer plots of the dam reservoir whose depth
estimation has to be done.
Digital Signal Processing - Practical Techniques, Tips and Tricks Course SamplerJim Jenkins
The goal of this 3-day course is to Introduce, explain, and demonstrate powerful, proven techniques, tips and “tricks of the trade” that can dramatically improve accuracy, speed and efficiency in Digital Signal Processing (DSP) applications.
The concepts are first presented using many colorful, clear figures along with plain English explanations and real-world examples. They are next demonstrated using clearly written MATLAB programs (with graphics). This way the student sees the key equations “in action” which increases intuitive understanding and learning speed. These (free) working programs can also be later modified or adapted by the student for customized, site specific use.
Each student will receive extensive course slides, a CD with MATLAB m-files for demonstration and later adaptation, supplementary materials and references to aid in the understanding and application of these “techniques, tips, and tricks” and a copy of the instructor’s latest book “The Essential Guide to Digital Signal Processing”.
ELINT Interception and Analysis course samplerJim Jenkins
The course covers methods to intercept radar and other non-communication signals and a then how to analyze the signals to determine their functions and capabilities. Practical exercises illustrate the principles involved.
Space Radiation & It's Effects On Space Systems & Astronauts Technical Traini...Jim Jenkins
This course is designed for technical and management personnel who wish to gain an understanding of the fundamentals and the effects of space radiation on space systems and astronauts. The radiation environment imposes strict design requirements on many space systems and is the primary limitation to human exploration outside of the Earth's magnetosphere. The course specifically addresses issues of relevance and concern for participants who expect to plan, design, build, integrate, test, launch, operate or manage spacecraft and spacecraft subsystems for robotic or crewed missions. The primary goal is to assist attendees in attainment of their professional potential by providing them with a basic understanding of the interaction of radiation with non-biological and biological materials, the radiation environment, and the tools available to simulate and evaluate the effects of radiation on materials, circuits, and humans
Space Systems & Space Subsystems Fundamentals Technical Training Course SamplerJim Jenkins
This four-day course in space systems and space subsystems is for technical and management personnel who wish to gain an understanding of the important technical concepts in the development of space instrumentation, subsystems, and systems. The goal is to assist students to achieve their professional potential by endowing them with an understanding of the subsystems and supporting disciplines important to developing space instrumentation, space subsystems, and space systems. It designed for participants who expect to plan, design, build, integrate, test, launch, operate or manage subsystems, space systems, launch vehicles, spacecraft, payloads, or ground systems. The objective is to expose each participant to the fundamentals of each subsystem and their inter-relations, to not necessarily make each student a systems engineer, but to give aerospace engineers and managers a technically based space systems perspective. The fundamental concepts are introduced and illustrated by state-of-the-art examples. This course differs from the typical space systems course in that the technical aspects of each important subsystem are addressed.
AESA Airborne Radar Theory and Operations Technical Training Course SamplerJim Jenkins
The revolutionary active electronically scanned array (AESA) Radar provides huge gains in performance and all the front line fighters in the world from the Americans (F35, F22, F18, F15, F16) to the Europeans, Russians and Chinese already have one or soon will. This four day seminar, which took 10,000 man hours to produce, is a comprehensive treatment on the latest systems engineering technology required to design the modes for an AESA to capitalize on the systems inherent multi role, wide bandwidth, fast beam switching, and high power capabilities. Steve Jobs once said “You must provide the tools to let people become their best”, and this seminar will include two indispensable tools for the AESA engineer. 1) A newly written 400+ page electronic book with interactive calculations and simulations on the more complicated seminar subjects like STAP and Automatic Target Recognition. 2) A professionally designed spread sheet (with software) for designing, capturing and predicting the detection performance of the AESA modes including the challenging Alert-Confirm waveform.
This three day course is intended for practicing systems engineers who want to learn how to apply model-driven systems Successful systems engineering requires a broad understanding of the important principles of modern spacecraft communications. This three-day course covers both theory and practice, with emphasis on the important system engineering principles, tradeoffs, and rules of thumb. The latest technologies are covered. <p>
Communications Payload Design and Satellite System Architecture: Bent Pipe a...Jim Jenkins
This four-day course, ATI Courses.com's Communications Payload Design and Satellite System Architecture course , provides communications and satellite systems engineers and system architects with a comprehensive and accurate approach for the specification and detailed design of the communications payload and its integration into a satellite system. Both standard bent pipe repeaters and digital processors (on board and ground-based) are studied in depth, and optimized from the standpoint of maximizing throughput and coverage (single footprint and multi-beam). Applications in Fixed Satellite Service (C, X, Ku and Ka bands) and Mobile Satellite Service (L and S bands) are addressed as are the requirements of the associated ground segment for satellite control and the provision of services to end users.
Software Defined Radio Engineering course samplerJim Jenkins
This 3-day course is designed for digital signal processing engineers, RF system engineers, and managers who wish to enhance their understanding of this rapidly emerging technology. Most topics include carefully described design analysis, alternative approaches, performance analysis, and references to published research results. Many topics are illustrated by Matlab simulation demos. An extensive bibliography is included.
Satellite RF Communications and Onboard Processing Course SamplerJim Jenkins
Successful systems engineering requires a broad understanding of the important principles of modern satellite communications and onboard data processing. This course covers both theory and practice, with emphasis on the important system engineering principles, tradeoffs, and rules of thumb. The latest technologies are covered, including those needed for constellations of satellites.
This course is recommended for engineers and scientists interested in acquiring an understanding of satellite communications, command and telemetry, onboard computing, and tracking. Each participant will receive a complete set of notes.
Space Environment & It's Effects On Space Systems course samplerJim Jenkins
This class on the space environment and its effects on space systems is for technical and management personnel who wish to gain an understanding of the important issues that must be addressed in the development of space instrumentation, subsystems, and systems. The goal is to assist students to achieve their professional potential by endowing them with an understanding of the fundamentals of the space environment and its effects. The class is designed for participants who expect to either, plan, design, build, integrate, test, launch, operate or manage payloads, subsystems, launch vehicles, spacecraft, or ground systems.
Each participant will receive a copy of the reference textbook: Pisacane, VL. The Space Environment and its Effects on Space Systems. AIAA Education Series, 2008.
Bioastronautics: Space Exploration and its Effects on the Human Body Course S...Jim Jenkins
This three-day course is intended for technical and managerial personnel who wish to be introduced to the effects of the space environment on humans. This course introduces bioastronautics from a fundamental perspective, assuming no prior knowledge of biology, physiology, or chemistry. The objective of the course is to provide the student with basic knowledge that will allow him or her to contribute more effectively to the human space exploration program. The human body, that through evolution is uniquely designed to function on the Earth, adapts to the space environment characterized by weightlessness and enhanced radiation. These alterations can impact the health and performance of astronauts, especially on return to the Earth.
Fundamentals Of Space Systems & Space Subsystems course samplerJim Jenkins
This course in space systems and space subsystems is for technical and management personnel who wish to gain an understanding of the important technical concepts in the development of space instrumentation, subsystems, and systems. The goal is to assist students to achieve their professional potential by endowing them with an understanding of the subsystems and supporting disciplines important to developing space instrumentation, space subsystems, and space systems. It designed for participants who expect to plan, design, build, integrate, test, launch, operate or manage subsystems, space systems, launch vehicles, spacecraft, payloads, or ground systems. The objective is to expose each participant to the fundamentals of each subsystem and their inter-relations, to not necessarily make each student a systems engineer, but to give aerospace engineers and managers a technically based space systems perspective. The fundamental concepts are introduced and illustrated by state-of-the-art examples. This course differs from the typical space systems course in that the technical aspects of each important subsystem are addressed.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
Fundamentals of Passive and Active Sonar Technical Training Short Course Sampler
1. FUNDAMENTALS OF PASSIVE AND ACTIVE SONAR
Instructor:
Duncan Sheldon, Ph.D.
ATI Course Schedule: http://www.ATIcourses.com/schedule.htm
ATI's Passive & Active Sonar: http://www.aticourses.com/Fundamentals_of_Passive_and_Active_Sonar.htm
2. www.ATIcourses.com
Boost Your Skills 349 Berkshire Drive
Riva, Maryland 21140
with On-Site Courses Telephone 1-888-501-2100 / (410) 965-8805
Tailored to Your Needs
Fax (410) 956-5785
Email: ATI@ATIcourses.com
The Applied Technology Institute specializes in training programs for technical professionals. Our courses keep you
current in the state-of-the-art technology that is essential to keep your company on the cutting edge in today’s highly
competitive marketplace. Since 1984, ATI has earned the trust of training departments nationwide, and has presented
on-site training at the major Navy, Air Force and NASA centers, and for a large number of contractors. Our training
increases effectiveness and productivity. Learn from the proven best.
For a Free On-Site Quote Visit Us At: http://www.ATIcourses.com/free_onsite_quote.asp
For Our Current Public Course Schedule Go To: http://www.ATIcourses.com/schedule.htm
3. DECISION: H1/H0 ?
ACTIVE SONAR DETECTION MODEL
POST-DETECTION
PROCESSOR
TRANSMISSION
DETECTOR
PRE-DETECTION
FILTER
DELAY AND
ATTENUATION AMBIENT NOISE RECEPTION
TIME-VARYING
MULTIPATH
TARGET
TIME-VARYING DELAY AND
MULTIPATH ATTENUATION
REVERBERATION 2
4. DEFINITIONS
Acoustic pressure, p: The difference between the total pressure, ptotal, and
the hydrostatic (or undisturbed) pressure po.
ptotal = ptotal(x,y,z;t) Pascals
po = po(x,y,z) or
Newtons/(meter)2
p = p (x,y,z;t) = ptotal - po
Acoustic intensity, I : A vector whose component I •n in the direction of any
unit vector n is the rate at which energy is being
transported in the direction n across a small plane
element perpendicular to n , per unit area of that plane
element.
I ≡ pu ; where u is the fluid velocity at (x,y,z;t).
I = I (x,y,z;t) Watts/(Meter)2
3
5. ACOUSTIC INTENSITY LEVELS EXPRESSED IN DECIBELS
(prms)2
For a plane wave, Iref = ρ c
ref
PRESSURE
1 Pascal = 1 Newton/(1 Meter)2
prms = Root -mean -square pressure
ENERGY ρ = Density
1 Joule = 1 Newton x 1 Meter c = Sonic velocity
POWER prms, ref water = 10- 6 Pascals
1 Watt = 1 Joule/(1Second)
ρ c water = 1.5 x 10 + 6 kgm/(meter 2second)
INTENSITY (or ENERGY FLUX)
Watts/(Meter)2 prms, ref air = 20 x 10- 6 Pascals
Joules/Second /(Meter)2
ρ c air = 430 kgm/(meter 2second)
Intensity level, I, usually refers to a normalized intensity magnitude,
( | I |average /Iref), expressed in decibels. For example, I = 60 dB means
60 dB = 10 log10 (| I | average/ Iref)
6 = log10 (| I | average/ Iref)
I = 10 +6 x Iref [ Watts/(meter2) ] 4
6. ACOUSTIC INTENSITY REFERENCE VALUES: AIR AND WATER
(prms)2
Average acoustic intensity magnitude for a plane wave, | I | =
ρc .
prms = Root -mean -square of acoustic pressure
ρ = Density
c = Sonic velocity
For water: Iref water ≡ | I |ref water
ρ c = 1.5 x 10 + 6 kgm/(meter 2 second)
Iref water ≡ [10 − 6 Pascals] 2 [ρ c]
/ = 0.67 x 10 −18 Watts / (meter)2
water
For air: Iref air ≡ | I |ref air
ρ c = 430 kgm/(meter 2 second)
Iref air ≡ [ 20 x 10 − 6 Pascals] 2 [ρ c]
/ ≈ 10 −12 Watts / (meter)2
air
5
7. DECIBELS MEASURED IN AIR AND WATER
X watts/meter2
100 dB water re 10-6 Pa = 10log10 ( I ref water watts/meter2
)
X watts/meter2
= 10log10 ( )
6.76 x 10-19 watts/meter2
Y watts/meter2
100 dB air re 20 x 10-6 Pa = 10log10 ( )
I ref air watts/meter2
Y watts/meter2
= 10log10 ( )
10-12 watts/meter2
For water: X watts/meter2 = 6.76 x 10-9 watts/meter2
For air: Y watts/meter2 = 10-2 watts/meter2
10-2 watts/meter2
10log10 ( ) = 61.7 dB difference in intensity level.
6.76 x 10-9 watts/meter 2
6
8. REPLICA CORRELATION (1 of 6)
o A cross-correlation sequence can be calculated for any pair of causal
sequences x[k] and y[k], and there is no implied restriction on their relationship:
k = +∞
xcorr[x,y;n] = ∑x[k] y[k -n] ≡ g[n]
k = −∞
where g[n] is used to denote a cross-correlation sequence whose
constituent sequences are understood but not explicitly stated.
k = +∞
INPUT x[k] X ∑x[k] y[k -n] g[n] OUTPUT
k = −∞
REPLICA y[k-n] REPLICA CORRELATOR
o The term ‘replica correlator’ or ‘replica correlation’, is applied when there
is some relationship between the input x[k] and the replica y]k], for example:
x[k]=y[k], i.e, auto-correlation,
x[k] may be the result of applying a Doppler shift to y[k],
x[k] is the result of applying a (fixed) shift n to y[k], i.e., x[k]=y[k-n], or
x[k] = A y[k-n], where A is a constant and the same for all k. When
this is the case, it is helpful to think of x[k] and y[k] as structurally
matched or simply matched. 7
9. REPLICA CORRELATION (2 of 6)
40
x[k], 30 k(2) NON-ZERO
INPUT 20 VALUES OF x[k]
(SIGNAL) 10
k(2) = 4
k(1), FIXED BULK DELAY
k
0
k(1) k(1) + k(2)
y[k], k(2) NON-ZERO
REPLICA VALUES OF y[k]
4
3
2
1 k(2) = 4
k
0 1 2 3
y[k-n],
SHIFTED n INCREASES Each n > 0 produces a
4
REPLICA 2
3 different (shifted)
1
y[k-n] sequence.
k
0 n n+ k(2)
y[k-k(1)],
SHIFTED
REPLICA 4
3
ALIGNED 2
n = k(1) 1
WITH INPUT
k
0 k(1) k(1) + k(2) 8
10. REPLICA CORRELATION (3 of 6)
40
x[k], 30 k(2) NON-ZERO
INPUT 20 VALUES OF x[k]
(SIGNAL) 10
k(2) = 4
k(1) FIXED
k
k(1) k(1) + k(2)
y[k-n],
SHIFTED
n INCREASES 4
y[k-n] when n=k(1)
REPLICA 3 4
2 2 3
1 1
k
n n+ k(2) k(1) k(1) + k(2)
g[n],
k(1) 300
OUTPUT OF
REPLICA 200 200
CORRELATOR n = k(1)-k(2) 110 110 n = k(1)+k(2)
40
40
n
n= k(1)
The cross-correlation g[n] of x[k[ and y[k] is the output of the replica correlator, and
k ≥ k(1)+ k(2)
g[n] = ∑
k=
x[k]y[k − n] where n is the shift of y[k] with respect to x[k].
9
0
11. REPLICA CORRELATION (4 of 6)
40
x[k], 30 k(2) NON-ZERO
INPUT 20 VALUES OF x[k]
(SIGNAL) 10
k(2) = 4
k(1) FIXED
k
k(1) k(1) + k(2)
Instead of writing
k ≥ k(1)+ k(2)
g[n] = ∑
k=
x[k]y[k − n]
0
we can write
k = +∞
g[n] = ∑∞ y[k −n]
k=−
x[k]
Since x[k] = 0 if k < 0 or k > k(1) + k(2).
10
12. REPLICA CORRELATION (5 of 6)
SIGNAL k = +∞
INPUT +
NOISE
x[k] X ∑x[k] y[k -n] g[n] OUTPUT
k = −∞
REPLICA y[k-n] REPLICA CORRELATOR
SIGNAL+NOISE
REPLICA
2 k = +∞ 2
| g[n]| = | ∑∞ y[k −n] |
k=−
x[k]
o The instantaneous power output of the replica correlator |g[n]|2 is calculated
for each n and is the detection statistic, i.e., the statistic used to decide if a
signal matching, or nearly matching, the replica is embedded in the noise.
o A signal is declared to be present if | g[n] |2 exceeds a threshold:
INSTANTANEOUS POWER
OUTPUT OF REPLICA THRESHOLD
CORRELATOR,
SIGNAL + NOISE
2
|g[n]|
n
n = k(1)
BULK DELAY, k(1) 11
13. REPLICA CORRELATION (6 of 6)
SIGNAL k = +∞
INPUT +
NOISE
x[k] X ∑x[k] y[k -n] g[n] OUTPUT
k = −∞
REPLICA y[k-n] REPLICA CORRELATOR
SIGNAL+NOISE
REPLICA
2 k = +∞ 2
| g[n]| = | ∑∞ y[k −n] |
k=−
x[k]
INSTANTANEOUS POWER THRESHOLD
OUTPUT OF REPLICA
CORRELATOR,
SIGNAL + NOISE
2
|g[n]|
n
n = k(1)
BULK DELAY, k(1)
If zero-mean, statistically independent Gaussian noise masks the
input signal, cross-correlation of the received data with a replica
matching the signal is the optimum receiver structure.
12
14. REPLICA CORRELATION FOR A CONTINUOUS CW WAVEFORM (1 of 4)
TRANSMISSION
s(t) t
BULK DELAY
t =τ BD ECHO
s ( t − τ BD ) t
AMBIENT NOISE
n (t ) t
RECEIVED DATA
s ( t − τBD ) + n ( t ) t
REPLICAS OF THE
t = τ RD
TRANSMISSION FOR
s(t-τRD)
(1)
(1) DIFFERENT REPLICA DELAYS
REPLICA
t
t = τ RD
DELAYS
s(t-τRD)
(2)
(2)
t
t=0 13
15. REPLICA CORRELATION FOR A CONTINUOUS CW WAVEFORM (2 of 4)
ECHO
t =τ BD RECEIVED DATA
s ( t − τBD ) + n ( t )
t
REPLICAS OF THE
t = τ RD
(1) TRANSMISSION FOR
DIFFERENT REPLICA DELAYS
s(t-τRD)
(1)
t
t = τ RD
REPLICA (2)
DELAYS
s(t-τRD)
(2) t
t=0
Shifted replicas, each with the same shape but different delays,
τRD, i=1,2, …, n,
(i)
are under consideration,
Only one record of the received data is under consideration.
14
16. REPLICA CORRELATION FOR A CONTINUOUS CW WAVEFORM (3 of 4)
INCREASING
REPLICA DELAY REPLICA OF THE
TRANSMISSION FOR
τ RD
Replica
SOME REPLICA DELAY
Time, t
τ BD
Signal
τd τd = τBD - τRD
Output of the replica correlator is the product of the
echo and the replica for time delays τd.
Note triangular
shape of upper
Peak value is peaks.
at τ d= 0
−τd Time delay, τd
Replica correlator output
and its envelope
τd =0 for a CW waveform 15
17. REPLICA CORRELATION FOR A CONTINUOUS CW WAVEFORM (4 of 4)
INCREASING
REPLICA DELAY REPLICA OF THE
TRANSMISSION FOR
τ
Replica
SOME REPLICA DELAY RD
Time, t
Received
data
τd
Time delay, τd
−τd
Replica correlator output
τd =0 for a CW waveform
plus ambient noise. 16
18. REPLICA CORRELATOR OUTPUT FOR A CW
WAVEFORM MASKED BY NOISE (1 of 3)
15
10
5 Independent normally
0 distributed noise only.
-5
INSTANTANEOUS
AMPLITUDES
-10
-15 0 200 400 600 800 1000 1200
SAMPLED DATA POINTS
Sine wave 240 samples
15
long with zero-padding on
10 each side.
5
0
Normally distributed
-5 noise plus sine wave.
-10
-15
Replica of sine wave
0 200 400 600 800 1000 1200
SAMPLED DATA POINTS (offset by -5).
150
Sine wave
CORRELATOR
100
σNOISE = 4.0 amplitude = 1.0
REPLICA
OUTPUT
50
0
Sine wave power
-50
= 0.516 = 132
-100 Noise power
-150
10 log( 132) = -15 dB
-600 -400 -200 0 200 400 600
17
TIME DELAY τd IN DATA SAMPLES
19. REPLICA CORRELATOR OUTPUT FOR A CW
WAVEFORM MASKED BY NOISE (2 of 3)
15
10
Independent
5
normally
0
distributed
-5 noise only.
INSTANTANEOUS
-10
AMPLITUDES
-15
0 500 1000 1500 2000 2500 Sine wave 480
SAMPLED DATA POINTS samples long with
15 zero-padding on
10 each side.
5
Normally
0 distributed noise
-5 plus sine wave.
-10
Replica of sine
-15
0 500 1000 1500 2000 2500 wave (offset -5).
SAMPLED DATA POINTS
REPLICA CORRELATOR
300
200 As on previous
slide,
OUTPUT
100
0 Sine wave power
-100 Noise power
-200
=> -15 dB
-300
0
-1000 -500 0 500 1000 18
TIME DELAY τd IN DATA SAMPLES
20. REPLICA CORRELATOR OUTPUT FOR A CW
WAVEFORM MASKED BY NOISE (3 of 3)
15
10
Independent
5
normally
0
distributed
-5 noise only.
INSTANTANEOUS
-10
AMPLITUDES
-15
0 500 1000 1500 2000 2500 Sine wave 480
SAMPLED DATA POINTS samples long with
15 zero-padding on
10 each side.
5
Normally
0 distributed noise
-5 plus sine wave.
-10 Note
Replica of sine
-15
0 500 1000 triangular 2000
1500 2500 wave (offset -5).
SAMPLED DATA POINTS shape
REPLICA CORRELATOR
300
200 As on previous
slide,
OUTPUT
100
0 Sine wave power
-100 Noise power
-200
=> -15 dB
-300
0
-1000 -500 0 500 1000 19
TIME DELAY τd IN DATA SAMPLES
21. RANDOM WALK SAMPLE AND A GENERAL RESULT (1 of 2)
INDEPENDENT NORMALLY DISTRIBUTED NOISE, σ = 1
3
NOISE VALUES
2
1
0
-1
-2
-3
-4
0 100 200 300 400 500 600 700 800 900 1000
SAMPLED DATA POINTS
N INCREASING N
STEPS REMOVED FROM
RANDOM WALK (SUM OF NOISE VALUES UP TO N DATA POINTS)
STARTING POSITION
20
10
0
-10
-20
-30
-40
-50
0 100 200 300 400 500 600 700 800 900 1000
NUMBER OF STEPS, N
Root-mean-square departure from starting position is N . 20
23. RANDOM WALK SAMPLE AND A GENERAL RESULT (2 of 2)
POINT-BY-POINT PRODUCTS OF REPLICA AND NOISE
(FROM PREVIOUS SLIDE)
2
PRODUCT
VALUES
1
0
-1
-2
0 100 200 300 400 500 600 700 800 900 1000
SAMPLED DATA POINTS
N INCREASING N
SUM OF ABOVE PRODUCT VALUES OUT TO N POINTS
SUM OF PRODUCT
10
5
0
VALUES
-5
-10
-15
-20
-25
-30
-35
0 100 200 300 400 500 600 700 800 900 1000
N, NUMBER OF PRODUCTS SUMMED
Root-mean-square departure from starting position (zero) is proportional to N .
22
24. PEAK REPLICA CORRELATOR OUTPUT WHEN ECHO MATCHES REPLICA
ECHOES OF INCREASING DURATION
1
0
N
-1
0 100 200 300 400 500 600 700 800 900 1000
SAMPLED DATA POINTS
REPLICAS OF INCREASING DURATION
1
0
N
CORRELATOR OUTPUT
-1
0 100 200 300 400 500 600 700 800 900 1000
PEAK REPLICA
SAMPLED DATA POINTS
500
400
300
200
100
0
0 100 200 300 400 500 600 700 800 900 1000
LENGTH OF REPLICA CORRELATION IN SAMPLED DATA POINTS, N
Peak replica correlator output with matched inputs is (nearly) proportional to N,
not N . 23
25. SUMMARY
If the number of ‘matched’ sampled data points in a received
signal and replica is N, and if the noise masking the signal is
uncorrelated from sample-to-sample, then:
1) The expectation of the root-mean-square noise
1
output of the replica correlator increases as N , 2
2) The peak output of the replica correlator due to
the signal increases (nearly) linearly with N.
3) The ratio of the peak signal output to the root-mean-square
N
noise output is expected to increase as 1 ,
N 2
4) The peak signal-to-noise instantaneous power output of
2
N
=
the replica correlator is expected to increase as
1
N.
N2
24
26. HYPOTHETICAL TRANSMISSION, RECEIVED DATA, AND
INSTANTANEOUS POWER OUTPUT OF A REPLICA CORRELATOR
ARBITRARY N SAMPLES
UNITS REPLICA OF TRANSMISSION
FOR TIME SHIFT τd
TIME
RECEIVED DATA,
SIGNAL MATCHING REPLICA PLUS NOISE
ARBITRARY
UNITS
TIME
τd
OUTPUT OF REPLICA OUTPUT AT τd = 0
ARBITRARY
CORRELATOR DUE TO SIGNAL ~ N
UNITS
TIME DELAY
- τd +τd
OUTPUT DUE TO ROOT-MEAN SQUARE VALUE
NOISE ALONE OF NOISE ALONE ~ N1/2
OUTPUT AT τ=0 INSTANTANEOUS POWER OUTPUT OF
ARBITRARY
DUE TO SIGNAL ~ N2 REPLICA CORRELATOR AND ITS PEAK
UNITS
POWER ENVELOPE
TIME DE;AY
- τd +τd
τd = 0 MEAN VALUE OF NOISE
25
POWER ALONE ~ N
(Too weak to be seen on this scale.)
27. THRESHOLD SETTING DETERMINES (WITHIN LIMITS) THE
RESULTING PROBABILITIES OF DETECTION AND FALSE ALARM
INSTANTANEOUS POWER OUTPUT OF A REPLICA
CORRELATOR FOR A CW WAVEFORM MASKED BY NOISE
REPLICA CORRELATOR
ARBITRATY UNITS
POWER OUTPUT,
TOO HIGH A THRESHOLD LEADS
TO MISSED DETECTIONS TOO LOW A THRESHOLD
LEADS TO EXCESSIVE
FALSE ALARMS
0
-100
-1000 -500 0 500 1000
-200 SAMPLED DATA POINTS FORWARD AND BACKWARD IN TIME
FROM EXACT OVERLAP OF CW WAVEFORM AND ITS REPLICA
26
28. PROBABILITIES OF FOUR POSSIBLE OUTCOMES
SEPARATE AND DISTINCT
ENSEMBLES
pd is the probability a threshold
crossing will occur when a target
TRUTH
is actually present. COLUMNS
pfa is the probability a threshold
crossing will occur when a target
TARGET IS TARGET IS
is not present. PRESENT ABSENT
THRESHOLD IS CORRECT FALSE
CROSSED,
DECIDE TARGET DETECTION ALARM
INSTANTANEOUS
PRESENT pd pfa
POWER OUTPUT OF
REPLICA THRESHOLD NOT NO
CORRELATOR
MISSED
CROSSED, ACTION
DECIDE TARGET
DETECTION
ABSENT 1 - pd 1 - pfa
For example, a detector might be designed to provide a 50% probability
of detection while maintaining a probability of false alarm below 10-6.
27
29. DECISION: H1/H0 ?
ACTIVE SONAR DETECTION MODEL
(DISCUSSED SO FAR, ALONG WITH SONAR EQUATION)
POST-DETECTION
PROCESSOR
REPLICA
TRANSMISSION FOR CW
CORRELATOR,
TRANSMISSIONS DFT DETECTOR
PRE-DETECTION
FILTER
(Beamformer)
DELAY AND RECEPTION
ATTENUATION AMBIENT NOISE
(Receive array)
TIME-VARYING
MULTIPATH
TARGET
TIME-VARYING DELAY AND
MULTIPATH ATTENUATION
REVERBERATION 28
30. DECISION: H1/H0 ?
ACTIVE SONAR DETECTION MODEL
(NEXT STEPS)
POST-DETECTION
PROCESSOR
TRANSMISSION FOR FREQUENY REPLICA
MODULATED CORRELATOR,
TRANSMISSIONS DFT DETECTOR
PRE-DETECTION
FILTER
(Beamformer)
DELAY AND RECEPTION
ATTENUATION AMBIENT NOISE
(Receive array)
TIME-VARYING
MULTIPATH
TARGET
TIME-VARYING DELAY AND
MULTIPATH ATTENUATION
REVERBERATION 29
31. REPLICA CORRELATION FOR A CONTINUOUS CW WAVEFORM
Replica matches echo
Replica
PRESSURE except for time delay.
Time, t
Echo
+τ d
Replica correlator output
and its envelope
for a CW waveform.
- τd +τd
τd = 0
τd is the time delay of the echo with respect
to the replica established in the correlator. 30
32. EFFECT SHIFTING A CW WAVEFORM’S FREQUENCY BY φ
USING THE ‘NARROWBAND’ APPROXIMATION
Frequency = fo + φ
Echo
PRESSURE
Time, t
Replica
Frequency = fo
Replica correlator output
Envelope and its envelope
narrows
for a CW waveform
- τd +τd
τd = 0
φ is the frequency difference (shift) of the echo with respect to
the replica established in the correlator. The greater | φ |, the
narrower the envelope of the correlator’s output
31
33. TRANSMITTED AND RECEIVED CW FREQUENCIES
AFTER APPLYING A NARROWBAND DOPPLER SHIFT
Instantaneous frequency
g6
Received CW frequencies
f6 g1 , g 2 , g 3 , … , g 6
g5
are each the result
f5 of the same narrowband
g4
Doppler shift with respect
f4 to equally spaced transmitted
g3
CW frequencies
f
g2 3 f1 , f 2 , f 3 , … , f 6
g1 f 2
f1 T TRANSMIT
Time
T RECEIVE
32
34. TRANSMITTED AND RECEIVED CW FREQUENCIES
FOR AN ECHO PRODUCED BY A CLOSING TARGET,
A WIDEBAND DOPPLER TRANSFORMATION
g6
Instantaneous frequency
g5 Received CW frequencies
f6 g1 , g 2 , g 3 , … , g 6
are each the result
g 4 f5 • of a different narrowband
Doppler shift with respect
f4 to equally spaced transmitted
g3
CW frequencies
f3 f1 , f 2 , f 3 , … , f6
g2
f2
g1
f1 T TRANSMIT
Time
T RECEIVE
33
35. DOPPLER PARAMETER S AND THE
WIDEBAND DOPPLER TRANSFORMATION
o s ≡ (1 − ν / c) / (1 + ν / c) = 1 − (2ν / c ) if ν / c << 1
where
ν = Constant range-rate of a reflector, positive closing, and
c = Sonic velocity in the medium.
o Each closing range-rate νi maps into a ‘stretch’ parameter s : νi si
i
1 to 1
o Each transmitted CW pulse of frequency fk becomes a
received CW pulse of frequency gki that depends upon si:
gki = f 1 + 2ν i / c = f k /si k = 1,2, …, N
k
o The difference between the received and transmitted
CW frequencies depends on both si and fk:
s
gki _ fk = fk 1 - i
si 34
36. EFFECT SHIFTING A CW WAVEFORM’S FREQUENCY BY φ
USING THE WIDEBAND DOPPLER TRANSFORMATION
C
L
Frequency = fo + φ
Echo
PRESSURE
Time, t
- τd
Replica
Frequency = fo
C
L
Envelope of replica
correlator output
- τd +τd
τd = 0
φ is the frequency shift of the echo with respect to the replica
established in the correlator. In the ‘wideband’ case the echo
undergoes a Doppler transformation and not simply a Doppler shift. 35
37. REPLICA CORRELATOR OUTPUT FOR A
FREQUENCY-MODULATED WAVEFORM (1 of 3)
Echo
PRESSURE
No
frequency
Time, t
Replica
shift
- τd
Replica correlator output
and its envelope for a
frequency-modulated waveform
- τd +τd
τd = 0
τd is the time delay of the echo with respect
to the replica established in the correlator. 36
38. REPLICA CORRELATOR OUTPUT FOR A
FREQUENCY-MODULATED WAVEFORM (2 of 3)
Echo
PRESSURE
No
frequency
Time, t
Replica
shift
- τd
Replica correlator output
and its envelope for a
frequency-modulated waveform
- τd +τd
Time resolution of the
envelope is ~W-1 where
τd = 0 W is the bandwidth of
the waveform.
τd is the time delay of the echo with respect
to the replica established in the correlator. 37
39. REPLICA CORRELATOR OUTPUT FOR A
FREQUENCY-MODULATED WAVEFORM (3 of 3)
C
L
Echo
PRESSURE
With echo
+τˆd frequency
Replica
shift
τˆd is the time delay when C
L
Replica correlator output
the replica correlator’s output +τˆd and its envelope for a
envelope is a maximum. frequency-modulated echo
experiencing a frequency shift.
- τd +τd
τd = 0
When a frequency-modulated echo experiences a frequency shift
with respect to the replica, the peak output of the correlator is
diminished and his peak output is no longer at τd = 0. 38
40. THE LINEAR FREQUENCY MODULATED (LFM)
WAVEFORM OF UNIT AMPLITUDE
Instantaneous frequency, Hz
Bandwidth, W fc , Carrier
frequency >> W
-t +t
-T/2 +T/2
Time, Seconds
39
41. TIME-FREQUENCY DIAGRAM REFERRED TO REPLICA WAVEFORM (1 of 2)
Instantaneous
frequency
Echo φ , frequency shift
Replica
~ ~
-t ~
+t
t=0 Time
T
Echo
~
PRESSURE
+t
Replica
~
+t
In the case of the narrowband assumption, φ is the
uniform upward frequency shift of the echo with
respect to the replica established in the correlator.
40
42. TIME-FREQUENCY DIAGRAM REFERRED TO REPLICA WAVEFORM (2 of 2)
Instantaneous Frequency shift is not uniform
frequency (closing target produces
Echo
(no narrowband increased echo frequencies)
assumption) Replica
~ ~
-t +t
~
t=0 Time
T Contraction if
frequency increases
Echo
~
PRESSURE
+t
Replica
~
+t
In the wideband case, the echo’s frequency shift is not uniform
over its duration, and any frequency shift brings about a dilation
or contraction in the duration of the waveform. 41
43. TIME DELAY DIAGRAMS
Echo data moves with
Instantaneous respect to replica
frequency Replica established in correlator
(narrowband
assumption)
Increasing clock time
τd
~ ~
-t +t
~
t=0 Time scale referred to replica waveform
BULK DELAY
t =τ BD ECHO
s ( t − τ BD ) t
τd > 0 Clock time
s(t-τRD )
(1) t = τ RD
(1) REPLICA
REPLICA
t
DELAY t=0
42
44. TIME DELAY DIAGRAMS
Echo data moves with
Instantaneous respect to replica
frequency Replica established in correlator
(narrowband
assumption)
Increasing clock time
~ ~
-t +t
~
t=0 Time scale referred to replica waveform
BULK DELAY
t =τ BD ECHO
s ( t − τ BD ) t
τd > 0 Clock time
s(t-τRD )
(1) t = τ RD
(1) REPLICA
REPLICA
t
DELAY t=0
43
45. TIME DELAY DIAGRAMS
Echo data moves with
Instantaneous respect to replica
frequency Replica established in correlator
(narrowband
assumption)
Increasing clock time
~ ~
-t +t
~
t=0 Time scale referred to replica waveform
BULK DELAY
t =τ BD ECHO
s ( t − τ BD ) t
τd > 0 Clock time
s(t-τRD )
(2) t = τ RD
(2) REPLICA
t
REPLICA
DELAY t=0
44
46. TIME DELAY DIAGRAMS
Echo data moves with
Instantaneous respect to replica
frequency Replica established in correlator
(narrowband
assumption)
Increasing clock time
~ ~
-t +t
~
t=0 Time scale referred to replica waveform
BULK DELAY
t =τ BD ECHO
s ( t − τ BD ) t
τd > 0 Clock time
s(t-τRD )
(3) t = τ RD
(3) REPLICA
t
REPLICA
DELAY t=0
45
47. TIME DELAY DIAGRAMS
Echo data moves with
Instantaneous τ d = τˆd when overlap is greatest respect to replica
frequency established in correlator
(narrowband
assumption) Replica
Increasing clock time
~ ~
-t +t
~
t=0 Time scale referred to replica waveform
BULK DELAY
t =τ BD ECHO
s ( t − τ BD ) t
τ d = τˆd > 0 Clock time
s(t-τRD )
(4) t = τ RD
(4) REPLICA
t
REPLICA
DELAY t=0
46
48. TIME DELAY DIAGRAMS
Echo data moves with
Instantaneous respect to replica
frequency established in correlator
(narrowband
assumption) Replica
Increasing clock time
~ ~
-t +t
~
t=0 Time scale referred to replica waveform
BULK DELAY
t =τ BD ECHO
s ( t − τ BD ) t
τd > 0 Clock time
s(t-τRD )
(5) t = τ RD
(5) REPLICA
t
REPLICA
DELAY t=0
47
49. TIME DELAY DIAGRAMS
Echo data moves with
Instantaneous respect to replica
frequency established in correlator
(narrowband
assumption) Replica
Increasing clock time
~ ~
-t +t
~
t=0 Time scale referred to replica waveform
BULK DELAY
t =τ BD ECHO
s ( t − τ BD ) t
τd = 0 Clock time
s(t-τRD )
(6) t = τ RD
(6) REPLICA
t
REPLICA
DELAY t=0
48
50. TIME DELAY DIAGRAMS
Echo data moves with
Instantaneous respect to replica
frequency established in correlator
(narrowband
assumption) Replica
Increasing clock time
~ ~
-t +t
~
t=0 Time scale referred to replica waveform
BULK DELAY
t =τ BD ECHO
s ( t − τ BD ) t
τd< 0 Clock time
s(t-τRD )
(7) t = τ RD
(6) REPLICA
t
REPLICA
DELAY t=0
49
51. USING THE TIME-FREQUENCY DIAGRAM TO ESTIMATE THE MAXIMUM
OUTPUT OF A REPLICA CORRELATOR WHEN THE ECHO
HAS A FREQUENCY SHIFT φ
Instantaneous
frequency τd = 0 τd > τ^d
Replica Echo data moves with
data respect to replica data
established in correlator
−~
t ~ =0 +~
t
t Time scale referred to replica waveform
Instantaneous
frequency τd = τd
^
φ Overlap region producing
maximum correlator power
output for frequency shift φ
−~
t ~ =0 +~
t
t Time scale referred to replica waveform
The greater the overlap region, the larger the maximum replica correlator output.
In this example an LFM waveform has experienced a narrowband Doppler shift.
50
52. TIME-FREQUENCY DIAGRAM REFERRED TO REPLICA WAVEFORM
Instantaneous Frequency shift is not uniform
frequency (closing target produces
Echo
(no narrowband increased echo frequencies
assumption) Replica at higher frequencies)
~ ~
-t +t
~
t=0 Time
T Contraction if
frequency increases
Echo
~
PRESSURE
+t
Replica
~
+t
In the wideband case, the echo’s frequency shift is not uniform
over its duration, and any frequency shift brings about a dilation
or contraction in the duration of the waveform. 51
53. USING THE TIME-FREQUENCY DIAGRAM TO ESTIMATE THE
MAXIMUM OUTPUT OF A REPLICA CORRELATOR
Instantaneous
frequency
(no narrowband
assumption)
Replica Echo data moves with
~ respect to replica ~
-t +t
~ Time scale referred to replica waveform
t=0
Instantaneous
frequency
τd
Overlap region producing
maximum correlator output
~ ~
-t +t
~ Time scale referred to replica waveform
t=0
Here an LFM echo has experienced a wideband Dopper transformation
rather than a narrowband Doppler shift. The overlap with the replica is
reduced, and the corresponding replica correlator output is reduced. 52
54. HYPERBOLIC FREQUENCY MODULATED (HFM) WAVEFORMS,
THEIR TIME-PERIOD AND TIME-FREQUENCY DIAGRAMS
Instantaneous period τ (t), linear
τ1
∆τ το
seconds
per cycle
τ2
-t +t
-T/2 0 +T/2
Instantaneous frequency (hyperbolic)
F2 = (τ2 )−1
W
F1 = (τ1 )−1
-t +t
-T/2 0 +T/2
HFM waveforms and linear period modulated
53
(LPM) waveforms are the same.
55. USING THE TIME-FREQUENCY DIAGRAM TO ESTIMATE THE
MAXIMUM OUTPUT OF A REPLICA CORRELATOR
Instantaneous Higher frequency echo
frequency data moves with
(no narrowband τd respect to replica
assumption)
Overlap region producing
maximum correlator output
Replica
~ ~
-t +t
~ Time scale referred to replica waveform
t=0
Here an HFM echo has experienced a wideband Dopper transformation
and the HFM’s time-frequency distribution adjusts itself to remain ‘more’
overlapped than in a similar case for an LFM waveform.
54
56. ANALYTIC SIGNAL OF A REAL WAVEFORM (1 of 2)
ο If U(f) is the Fourier transform of waveform u(t), U(f) can be folded
over as shown below to obtain Fourier transform Ψ(f).
ο The inverse Fourier transform of Ψ(f), ψ(t), is a complex waveform
in the time domain and provides a convenient way to describe the
envelope and phase of the real waveform u(t). ψ(t) is the analytic
signal of real waveform u(t), and the Fourier transform of ψ(t) (i.e.,
Ψ(f)) contains no negative frequencies.
|U(f)|
ENVELOPE
Q(f)
-f +f
+1
- fo2 + fo2 -f +f
|Ψ(f)|
FT
ENVELOPE u(t) ← → U ( f )
Ψ(f) = 2 Q(f) U(f)
FT
ψ (t ) ← → Ψ( f )
-f +f
55
+ fo2
57. ANALYTIC SIGNAL OF A REAL WAVEFORM (2 of 2)
ο If U(f) is the Fourier transform of waveform u(t), U(f) can be folded
over as show below to obtain Fourier transform Ψ(f).
ο The inverse Fourier transform of Ψ(f), ψ(t), is a complex waveform
in the time domain and provides a convenient way to describe the
envelope and phase of the real waveform u(t). ψ(t) is the analytic
signal of real waveform u(t).
ο If u(t) is a narrowband waveform, the frequency content of ψ (t),
(i.e., Ψ(f),) is negligible near zero frequency as well as null for all f < 0.
|U (f)|
Q(f)
+1
-f +f -f +f
- fo + fo
FT
ENVELOPES |Ψ (f)| u(t) ← → U ( f )
Ψ(f) = 2 Q(f) U(f)
-f FT
+f ψ (t ) ← → Ψ( f )
56
+ fo
58. ANALYTIC SIGNAL WITHOUT APPROXIMATION (1 of 2)
|U(f)| Q(f)
ENVELOPE
+1
-f +f
-f +f
- fo2 + fo2 FT
u(t) ← → U ( f )
|Ψ(f)| Ψ(f) = 2 Q(f) U(f)
ENVELOPE
FT
ψ (t ) ← → Ψ( f )
+∞
u(τ ) dτ
-f +f
ψ (t) = u(t) + j
∫
− ∞ π (t −τ )
+ fo2 u(t) = Re (ψ (t))
+∞ is the Hilbert transform of u(t)
u(τ ) dτ
∫
− ∞ π (t −τ ) ˆ
and is often denoted by u(t).
57
59. ANALYTIC SIGNAL WITHOUT APPROXIMATION (2 of 2)
ο ψ (t) is the analytic signal of real waveform u(t), and is always given by
+∞
u(τ ) dτ
ψ (t) = u(t) + j u(t) = u(t) + j
ˆ
∫
− ∞ π (t −τ )
even if u(t) is not narrowband! However, it may be difficult to find ˆ
u(t).
1.5 u(t) = - sin(2πfot)
u (t ) -0.5 < t < +0.5, Seconds
Instantaneous Amplitude
1
ˆ
u (t ) u(t) = 0; t > |0.5| Seconds
0.5 Envelope
fo = 3 Hertz; T = 1 Second
0
The envelope of u(t)
-0.5 is given by:
u 2 (t) + u 2 (t)
ˆ
-1
-1.5
-1.5 -1 -0.5 0 0.5 1 1.5 2
Time, seconds 58
60. APPROXIMATING THE ANALYTICAL SIGNAL WITH A
NARROWBAND COMPLEX WAVEFORM (1 of 6)
|U (f)|
Q(f)
ENVELOPE
+1
-f +f -f +f
- fo + fo
FT
|Ψ (f)| u(t) ← → U ( f )
ENVELOPE
Ψ(f) = 2 Q(f) U(f)
-f FT
+f ψ (t ) ← → Ψ( f )
+ fo
+∞
u(τ ) dτ
The analytic signal is always given by ψ (t) = u(t) + j
∫
− ∞ π (t −τ )
If u(t) is narrowband, ψ(t) can be approximated by
ψ (t) ≅ ψ (t) = [a(t) + j b(t)] exp[ 2π j fo t ]
ˆ
where a(t) and b(t) are real, +fo is a central frequency of U(f),
and a(t) and b(t) vary slowly compared to 2π fot.
59
61. ANALYTIC SIGNAL AND COMPLEX ENVELOPE OF REAL WAVEFORM u(t,fo)
ψ(t,fo) IS THE INVERSE FOURIER
U(f,fo) IS FOURIER TRANSFORM OF u(t.fo)
TRANSFORM OF Ψ (f,fo)
|U ( f , fo ) | | Ψ( f , fo ) | FT
ψ (t, fo ) ←→ Ψ( f , fo )
ENVELOPE
ENVELOPE
OF |U( f , fo )|
OF |Ψ ( f , fo )|
-f +f
-fo 0 fo -f 0 fo +f
DOWNSHIFT BY fo
ψ(t,fo) is the analytic signal υ(t) IS THE INVERSE FOURIER
~
of real waveform u(t.fo). TRANSFORM OF Ψ(f)
~
| Ψ( f ) | FT ~
υ (t ) ←→ Ψ( f )
υ(t) is the complex envelope
ENVELOPE
of real waveform u(t,fo). ~
OF |Ψ ( f )|
60
-f 0 +f
62. FACTORS OF THE COMPLEX NARROWBAND WAVEFORM ψ (t)
ˆ
Im Im
exp(+2π j fo t) |ψ (t)| =
ˆ
1/2
[a(t)2 + b(t)2 ]
b(t)
Re Re
a(t)
unit exp(-2π j fo t)
circle absent
a(t) and b(t) are real and
ψ (t) = [a(t) + j b(t)] exp(+2π j fo t)
ˆ vary slowly with respect
u(t) = Re (ψ (t) )
ˆ to 2π fot.
[a(t) + j b(t)]is the
complex envelope of ψ (t ).
ˆ 61
64. DEFINITION OF INSTANTANEOUS FREQUENCY
j[ Φ(t) ]
ψ (t) = A(t) e
ˆ is a particularly convenient form of the
analytic signal because Φ(t) is the argument of ψ (t ) and the
ˆ
instantaneous phase of u(t) in radians.
The instantaneous frequency of u(t) in Hertz is
finstantaneous(t ) ≡ fi (t ) ≡ 1 d [Φ(t)]
2 π dt
Given fi(t), the argument of ψ (t) and instantaneous phase of
ˆ
u(t) is given by
Φ(t) = 2π
∫ fi (t) dt + θ o
And we can write ψ (t ) as
ˆ
ψ (t) = A(t) e
ˆ [ ∫ ]
j 2π fi (t) dt + θ o
63
65. AMPLITUDE, FREQUENCY, AND PHASE MODULATION
ο In the expression ψ (t )
ˆ = A(t ) e [ ∫
j 2π fi (t) dt + θ o]
Variations in A(t) are amplitude modulation or AM
( A(t) = a(t )2 + b(t )2 ) ,
Variations in fi(t) are frequency modulation or FM.
ο Most active sonar waveforms are either frequency or amplitude
modulated; frequency modulation is more common.
ο Phase modulation or PM is used in underwater communications;
for example, 90o or 180o phase changes are embedded in θ (t)
and the analytic signal is expressed as
ψ (t) = A(t) [ exp ( j (2π fo t + θ (t) ) )]
ˆ
i.e., θ(t) ‘switches’ or ‘flips’ the phase of the carrier frequency.
64
66. IMPORTANCE OF THE COMPLEX ENVELOPE
ο In the expressions
ψ(t) = [a(t) + j b(t)] exp(+2π j fo t) , and
‹
u(t) = Re(ψ(t) ) = a(t)cos(2π fo t) – b(t)sin(2π fo t)
‹
both the amplitude and frequency modulation of u(t) and ψ(t)
‹
are embedded in the complex envelope [a(t) + j b(t)] :
Amplitude modulation is a(t)2 + b(t)2 = A(t ) , and
Frequency modulation is 1 d [θ (t ) ] where θ (t) = Arg ( a(t) + j b(t))
2π dt
ο All the properties of the waveform (favorable and unfavorable!)
independent of fo are embedded in the complex envelope.
ο This means analyses of most waveform properties (e.g., Doppler
tolerance, range resolution) can be carried out by considering
only the complex envelope without regard to a ‘carrier’ frequency.
65
67. OBTAINING THE ANALYTIC SIGNAL AND REAL WAVEFORM
o General form of the analytic signal is ψ (t ) = A(t ) e j[Φ(t)]
d
Start with fi(t) for the
finstantaneous(t ) ≡ fi (t ) ≡ 1 [Φ(t)]
waveform you want. 2 π dt
∫
Φ(t) ≡ 2π fi (t) dt
Next integrate to Need not be
find the phase. narrowband.
Finally, insert Φ(t) in the Φ(t) = 2π fo t + θ (t) + θo
general form for ψ(t). If narrowband.
where d[θ(t)]/dt << 2π fo
Variations in A(t) are amplitude modulation or AM
( A(t) = a(t )2 + b(t )2 ) ,
Variations in fi(t) are frequency modulation or FM.
o A(t) is often explicitly stated, i.e., rect(t/T).
o Re[ψ(t)] gives the real waveform, u(t). 66
68. OBTAINING THE ANALYTIC SIGNAL AND REAL WAVEFORM
o General form of the analytic signal is ψ (t ) = A(t ) e j[Φ(t)]
d
Start with fi(t) for the
finstantaneous(t ) ≡ fi (t ) ≡ 1 [Φ(t)]
waveform you want. 2 π dt
∫
Φ(t) ≡ 2π fi (t) dt
Then integrate to An indefinite integral with
find the phase. a constant of integration.
Finally, insert Φ(t) in the Φ(t) = 2π fo t + θ (t) + θo
general form for ψ(t). If narrowband.
where d[θ(t)]/dt << 2π fo
Variations in A(t) are amplitude modulation or AM
( A(t) = a(t )2 + b(t )2 ) ,
Variations in fi(t) are frequency modulation or FM.
o A(t) is often explicitly stated, i.e., rect(t/T).
o Re[ψ(t)] gives the real waveform, u(t). 67
69. THREE COMMON WAVEFORMS
The following slides give complex representations,
i.e., ψ (t ) for three common waveforms:
o CW (continuous wave)
o LFM (linear frequency modulation)
o HFM (hyperbolic frequency modulation)
68
70. FT sin ( π f T )
COMPLEX NARROWBAND u (t) = rect (t /T ) ← →
T = U( f )
CW WAVEFORMS OF πfT
FT
UNIT AMPLITUDE u (t) exp ( 2π j fc t) ← →
U ( f − fc )
ψ (t) = 1T
rect (t/T ) exp [ j 2 π ( fc t + θo )] 0.8T Shift to
2π frequency fc
0.6T
where T fc >> 1 cycle
0.4T to get U(f - fc )
U(f)
1 if |t/T| < 1/2
rect (t/T ) = 0.2T
0 if |t/T| > 1/2
0T
θο radians is a constant
that determines the phase -0.2T
of the CW waveform.
-0.4T-10 -8
∫
-6 -4 -2 0 2 4 6 8 10
(Φ(t) ≡ 2π fc dt = 2π fc t + θo ) T T T T T T T T T T T
FREQUENCY
Cycles /Second 69
71. THE LINEAR FREQUENCY MODULATED (LFM)
WAVEFORM OF UNIT AMPLITUDE
Instantaneous frequency
Bandwidth, W Carrier
fc frequency >> W
-t +t
-T/2 +T/2
Instantaneous phase (radians) = Φ(t) = 2 π fc t + θ (t) , t < |T/2| and TW >> 1
and instantaneous frequency (Hertz) = f (t ) ≡
1 d[ Φ(t) ]
i 2π dt
= 1 d [ 2 π fc t + θ (t) ] = fc + 1 d [θ (t) ]
2π dt 2π dt
Linear frequency modulation means
1 d [θ (t) ] = k t so θ (t) = 2 π k t 2 + θ
o
2π dt 2
i.e., the instantaneous frequency is a linear function of time, and k = W/T from the figure.
Therefore the LFM’s instantaneous phase = 2 π ( fc t + k t 2 + θo ) (radians)
2 2π 70
72. THE LINEAR FREQUENCY MODULATED (LFM)
WAVEFORM OF UNIT AMPLITUDE
Instantaneous frequency
W fc >> W
-t +t
-T/2 +T/2
j( fc t + k t 2 + θo )
t
ψ (t) = rect [] [T
exp 2 π
2 2π ]
j[ Φ(t) ] t
Given: ψ (t) = A(t) e and A(t) = rect [] T
Step 1 fi (t) = fc + k t
Step 2
Φ(t) = 2π
∫ fi (t) dt
Φ(t) = 2 π ( fc t + k t 2 + θo )
2 2π 71
73. HYPERBOLIC FREQUECY MODULATED (HFM) WAVEFORMS,
THEIR TIME-PERIOD AND TIME-FREQUENCY DIAGRAMS
Instantaneous period (linear) = τ(t)
τ1
∆τ το
τ2
-t +t
-T/2 0 +T/2
Instantaneous frequency (hyperbolic) = Finst(t) = 1/τ(t)
F2 = 1/τ2
W
F1 = 1/τ1
-t +t
-T/2 0 +T/2
HFM waveforms and linear period modulated
72
(LPM) waveforms are the same.