Synthetic Aperture Radar (SAR) uses signal processing techniques to synthesize a large antenna from data collected by a physically small antenna as it moves along a flight path. This allows SAR to achieve high-resolution images independent of altitude. SAR transmits microwave pulses and analyzes the returned echoes to build up images of the terrain. SAR has various applications including topographic mapping and measuring ocean waves, currents, and wind. Ocean backscatter measured by SAR is influenced by surface roughness driven by factors like wind as well as hydrodynamic effects of waves and currents.
How to better understand SAR, interpret SAR products and realize the limitationsNopphawanTamkuan
This content shows how to better understand SAR (how to interpret SAR images and read SAR interferogram ). Moreover, capacities and limitations of SAR are discussed for each disaster emergency mapping (Flood, Landslide and Earthquake).
SAR is a type of radar which works with antenna and receiver using radio waves which can create two dimension or three dimension of the objects . A synthetic-aperture radar is an imaging radar mounted on a moving platform. SAR gives high resolution data and works 24*7.
How to better understand SAR, interpret SAR products and realize the limitationsNopphawanTamkuan
This content shows how to better understand SAR (how to interpret SAR images and read SAR interferogram ). Moreover, capacities and limitations of SAR are discussed for each disaster emergency mapping (Flood, Landslide and Earthquake).
SAR is a type of radar which works with antenna and receiver using radio waves which can create two dimension or three dimension of the objects . A synthetic-aperture radar is an imaging radar mounted on a moving platform. SAR gives high resolution data and works 24*7.
A ~25 slide presentation that explains the underlying principles and some applications of InSAR, with a particular focus on the measurement of deformation due to earthquakes. The presentation could be used in a lecture or lab setting, or provided to students for review out of class. The slides are annotated with additional background information designed to assist instructors.
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 pulse to form an image.
SBAS-DInSAR processing on the ESA Geohazards Exploitation PlatformEmmanuel Mathot
In the context of space-borne geodetic techniques, Differential Synthetic Aperture Radar Interferometry (DInSAR) has demonstrated its high performance in measuring surface displacements in different conditions and scenarios, both natural and anthropic. In particular, the advanced DInSAR time series processing method referred to as Small BAseline Subset (SBAS), that allows studying both the spatial and temporal variability of the surface displacements, has proven to be particularly suitable in different contexts, as for natural hazards (volcanoes, earthquakes and landslides) and human-induced deformation (subsidence due to aquifer exploitation, mining operations, and building of large infrastructures). Recently, an efficient implementation of this algorithm (referred to as P-SBAS approach) has been fully integrated within the ESA’s Grid Processing on Demand (G-POD) environment, which is part of the [Geohazards Thematic Exploitation Platform (GEP)](https://geohazards-tep.eo.esa.int/#!) of ESA. The GEP is devoted to the exploitation of EO data resources in the context of the Geohazard Supersites & Natural Laboratories as well as on the CEOS Pilots on Seismic Hazards and Volcanoes. The GEP is sourced with elements, data and processing, including P-SBAS, relevant to the geohazards theme. The integration of the P-SBAS algorithm within GEP resulted in a web-based tool freely available to the scientific community. This tool allows users to process, from their own laptops, the European SAR data archives (ERS, ENVISAT and Sentinel-1) for obtaining surface displacement maps and time series in a completely unsupervised way, without caring about data download and processing facility procurements. The workshop is organized in four parts. First, a short overview on the DInSAR processing methods allowing retrieving mean surface deformation maps and displacement time series will be provided, with a specific focus on the SBAS-DInSAR technique. Secondly, the GEP and G-POD environments will be introduced and the P-SBAS web tool will be presented. The third and the fourth parts are dedicated to the advanced features and to case studies and results achieved via the web tool, respectively.
This content presents for basic of Synthetic Aperture Radar (SAR) including its geometry, how the image is created, essential parameters, interpretation, SAR sensor specification, and advantages and disadvantages.
Working Processes Of Radar
History – Before Radar
Principle Of Operation
Radio Detection And Ranging
Radar Functions
Radar Bands And Usage
Terminology Of Radar Systems
Radar Range Equation
Types Of Radar
Pulse RADAR
Duplexer Using Pin Switches
Doppler Effect
Principle Of Continuous Wave Radar
Principles Of MTI RADAR
Different Types Of RADAR & It’s Applications
This course gives keys to understand the SAR image and specificities: geometry, speckle, penetration capabilities, layovers, multipath, dielectric properties.
Advanced modes: polarimetry, interferomety and POLINSAR are also presented.
Using Metamaterials as Optical Perfect AbsorberSepehr A. Benis
Article review and presentation on basics of using metamaterials as optical perfect absorbers
Metamaterial Course Final Project ( Optional Graduate Course )
Dr. Leyla Yousefi
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.
A ~25 slide presentation that explains the underlying principles and some applications of InSAR, with a particular focus on the measurement of deformation due to earthquakes. The presentation could be used in a lecture or lab setting, or provided to students for review out of class. The slides are annotated with additional background information designed to assist instructors.
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 pulse to form an image.
SBAS-DInSAR processing on the ESA Geohazards Exploitation PlatformEmmanuel Mathot
In the context of space-borne geodetic techniques, Differential Synthetic Aperture Radar Interferometry (DInSAR) has demonstrated its high performance in measuring surface displacements in different conditions and scenarios, both natural and anthropic. In particular, the advanced DInSAR time series processing method referred to as Small BAseline Subset (SBAS), that allows studying both the spatial and temporal variability of the surface displacements, has proven to be particularly suitable in different contexts, as for natural hazards (volcanoes, earthquakes and landslides) and human-induced deformation (subsidence due to aquifer exploitation, mining operations, and building of large infrastructures). Recently, an efficient implementation of this algorithm (referred to as P-SBAS approach) has been fully integrated within the ESA’s Grid Processing on Demand (G-POD) environment, which is part of the [Geohazards Thematic Exploitation Platform (GEP)](https://geohazards-tep.eo.esa.int/#!) of ESA. The GEP is devoted to the exploitation of EO data resources in the context of the Geohazard Supersites & Natural Laboratories as well as on the CEOS Pilots on Seismic Hazards and Volcanoes. The GEP is sourced with elements, data and processing, including P-SBAS, relevant to the geohazards theme. The integration of the P-SBAS algorithm within GEP resulted in a web-based tool freely available to the scientific community. This tool allows users to process, from their own laptops, the European SAR data archives (ERS, ENVISAT and Sentinel-1) for obtaining surface displacement maps and time series in a completely unsupervised way, without caring about data download and processing facility procurements. The workshop is organized in four parts. First, a short overview on the DInSAR processing methods allowing retrieving mean surface deformation maps and displacement time series will be provided, with a specific focus on the SBAS-DInSAR technique. Secondly, the GEP and G-POD environments will be introduced and the P-SBAS web tool will be presented. The third and the fourth parts are dedicated to the advanced features and to case studies and results achieved via the web tool, respectively.
This content presents for basic of Synthetic Aperture Radar (SAR) including its geometry, how the image is created, essential parameters, interpretation, SAR sensor specification, and advantages and disadvantages.
Working Processes Of Radar
History – Before Radar
Principle Of Operation
Radio Detection And Ranging
Radar Functions
Radar Bands And Usage
Terminology Of Radar Systems
Radar Range Equation
Types Of Radar
Pulse RADAR
Duplexer Using Pin Switches
Doppler Effect
Principle Of Continuous Wave Radar
Principles Of MTI RADAR
Different Types Of RADAR & It’s Applications
This course gives keys to understand the SAR image and specificities: geometry, speckle, penetration capabilities, layovers, multipath, dielectric properties.
Advanced modes: polarimetry, interferomety and POLINSAR are also presented.
Using Metamaterials as Optical Perfect AbsorberSepehr A. Benis
Article review and presentation on basics of using metamaterials as optical perfect absorbers
Metamaterial Course Final Project ( Optional Graduate Course )
Dr. Leyla Yousefi
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.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Standard radar detection process requires that the sensor output is compared to a predetermined threshold. The
threshold is selected based on a-priori knowledge available and/or certain assumptions. However, any
knowledge and/or assumptions become in adequate due to the presence of multiple targets with varying signal
return and usually non stationary background. Thus, any predetermined threshold may result in either increased
false alarm rate or increased track loss. Even approaches where the threshold is adaptively varied will not
perform well in situations when the signal return from the target of interest is too low compared to the average
level of the background .Track-before-detect techniques eliminate the need for a detection threshold and provide
detecting and tracking targets with lower signal-to-noise ratios than standard methods. However, although trackbefore-
detect techniques eliminate
the need for detection threshold at sensor's signal processing stage, they often use tuning thresholds at the output
of the filtering stage .This paper presents a computerized simulation model for target detection process.
Moreover, the proposed model method is based on the target motion models, the output of the detection
process can easily be employed for maneuvering target tracking.
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.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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/
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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/
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
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.
2. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
OutlineOutline
➢ Radar imaging systemsRadar imaging systems
➢ Synthetic aperture radars (SAR)Synthetic aperture radars (SAR)
➢ SAR measurements in the oceanSAR measurements in the ocean
3. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: What is a radar?What is a radar?
➢ What is a radar ?
Radar = RAdio Detection And Ranging
Radars are used in many contexts, including meteorological detection of
precipitation, measuring ocean surface waves, air traffic control, police
detection of speeding traffic, and by the military.
There are active and passive radar sensors:
Active radars: Radar imaging systems (SARs), Scatterometers, Altimeters
Passive radars: radiometers
4. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: how do they work?how do they work?
A radar is essentially a ranging or distance measuring device.
It consists fundamentally of a transmitter, a receiver, an antenna, and an electronics system to
process and record the data. The same antenna is often used for transmission and reception.
By measuring the time delay between the transmission of a pulse and the reception of the
backscattered "echo" from different targets, their distance from the radar and thus their
location can be determined.
5. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: frequencies and bandsfrequencies and bands
The microwaves emitted and received by SAR are at much longer
wavelengths (5.6cm for ERS SAR) than optical or infrared waves.
6. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: frequencies and bandsfrequencies and bands
Measurements through clouds
Images can be acquired
independently on the current weather
conditions
Measurements day and night
Images independent of solar illumination,
which is particularly important in high
latitudes (polar night)
7. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: imaging geometryimaging geometry
Most imaging radars used for remote
sensing are side-looking airborne radars
(SLARs) to avoid ambiguities.
The antenna points to the side with a beam
that is wide vertically and narrow
horizontally.
Azimuth = flight direction
Range = perpendicular to the flight
direction
Swath = 100 to 500km
8. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: building a 2D imagebuilding a 2D image
A pulse of energy is transmitted from the radar
antenna.
The amplitude and phase of the backscattered signal
is recorded as a function of time.
This is repeated over again while platform is moving.
As the sensor platform moves forward, recording and
processing of the backscattered signals builds up a
two-dimensional image of the surface.
9. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: Azimuth resolutionAzimuth resolution
Azimuth resolution describes the ability of an imaging radar to separate two closely spaced
scatterers in the direction parallel to the motion vector of the sensor
When two objects are in the radar beam
simultaneously, for almost all pulses, they both
cause reflections, and their echoes will be
received at the same time. However, the reflected
echo from the third object will not be received
until the radar moves forward. When the third
object is illuminated, the first two objects are no
longer illuminated, thus the echo from this object
will be recorded separately. For a real aperture
radar, two targets in the azimuth or along-track
resolution can be separated only if the distance
between them is larger than the radar beamwidth.
For all types of radars, the beamwidth is a
constant angular value with range.
For a given radar wavelength, the azimuth
beamwidth depends on the physical length of the
antenna in the horizontal direction according to:
RADARRADAR
TRAJECTORYTRAJECTORY
LL
WW
RADARRADAR
FOOTPRINTFOOTPRINT
SWATHSWATH
NADIR TRACKNADIR TRACK
hh
RADAR PULSERADAR PULSE
cτ = c / BW
θθ
Xa
Xr
L
B
λ
=Beamwidth:
11. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: Azimuth resolutionAzimuth resolution
Real Aperture Radars have azimuth resolution determined by the antenna beamwidth, so that it is
proportional to the distance between the radar and the target (slant-range). For real aperture radars,
azimuth resolution can be improved only by longer antenna or shorter wavelength.
The use of shorter wavelength generally leads to a higher cloud and atmospheric attenuation, reducing the
all-weather capability of imaging radars.
RADARRADAR
TRAJECTORYTRAJECTORY
LL
WW
RADARRADAR
FOOTPRINTFOOTPRINT
SWATHSWATH
NADIR TRACKNADIR TRACK
hh
RADAR PULSERADAR PULSE
cτ = c / BW
θθ
Xa
Xr
X a =
h λ
L co s θ
L
B
λ
=
Azimuth resolution:
Beamwidth:
12. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: Range resolutionRange resolution
To distinguish between two targets, the backscatter must be received at two different times. Since the
radar pulse must travel two ways, the two targets lead to distinguished echoes if:
d > L/2
If d==L/2, A and B are mapped as same target !
Range resolution
(here B = bandwith, Ɵ = radar incidence angle
Good range resolution for
➢ short pulse
➢ Large incidence angle
13. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: Range resolutionRange resolution
To improve range resolution, radar pulses should be as short as possible. However, it is also
necessary for the pulses to transmit enough energy to enable the detection of the reflected
signals.
If the pulse is shortened, its amplitude must be increased to keep the same total energy in
the pulse.
One limitation is the fact that the equipment required to transmit a very short, high-energy
pulse is difficult to build.
Synthetic Aperture Radars were developed as a means of overcoming the limitations of real
aperture radars.
14. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: Improving azimuth resolutionImproving azimuth resolution
Synthetic Aperture Radar (SAR) refers to a technique used to synthesize a very long
antenna by combining signals (echoes) received by the radar as it moves along its flight
track.
it is important to note that some details of the structure of the echoes produced by a given target
change during the time the radar passes by. This change is explained also by the Doppler effect
which among others is used to focus the signals in the azimuth processor.
15. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: Improving azimuth resolutionImproving azimuth resolution
Perception is relative!
It's to do with the effect of sound or light waves on the person seeing or hearing them - like the difference
you hear as an emergency siren passes you. It is caused by the change in distance between the thing
creating the wave and whatever is measuring, seeing or hearing the wave.
16. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: Improving azimuth resolutionImproving azimuth resolution
1122 1133
The Azimutal bandwith of the SAR is B = 2 fd
17. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Improving azimuth resolutionImproving azimuth resolution
The accuracy for determining the position of a target in the antenna beam is better, the
longer one is able to listen to the sound signal.
➢ The larger the beamwidth, the longer one can listen to the sound
➢ The smaller the antenna, the larger is the beamwidth ( β = λ/D)
➢ Thus, the azimuthal resolution becomes better, the smaller the antenna length D.
This result is completely contrary to what applies to other remote sensing instruments
where the larger the antenna, the better the resolution.
Here, the smaller the antenna, the better the resolution.
Azimuth resolution is Xa =D/2
The azimuthal resolution of a SAR is independent of range R and is proportional to D
18. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Improving range resolutionImproving range resolution
Pulse chirping: Signal modulation is a way to increase the radar pulse length without
decreasing the radar range resolution
This technique is analogous to the technique used in the azimuth (flight)
direction to improve the azimuthal resolution.
In the azimuth direction the frequency modulation of the backscatter signal
results from the motion of the platform and is thus naturally induced.
In range direction, the frequency modulation of the backscatter signal is
artificially induced by the emitted signal
All civilian spaceborne SARs, and most civilian airborne SARs use linear FM chirps as
the modulation scheme.
19. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: data processingdata processing
Layover
Slant-range scale distortion
Foreshortening
Shadowing
These effect my enhance the visual appearance of
relief and terrain structure, making radar imagery
excellent for applications such as topographic
mapping and identifying geologic structure
20. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Radar imaging systems:Radar imaging systems: Data processingData processing
SAR processing can be considered as a two-dimensional focusing operation :
➢ Range focusing: relatively straight forward
➢ Azimuth focusing: depends upon the Doppler histories produced by each point in the target field
For even moderate azimuth resolutions, a target's range to each location on the synthetic aperture
changes along the synthetic aperture. The energy reflected from the target must be "mathematically
focused" to compensate for the range dependence across the aperture prior to image formation.
21. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Data processingData processing
Speckle in SAR
SAR image optical image
22. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Data processingData processing
Contribution from random scattering
elements on the surface, with varying
path length to antenna cause
constructive / destructive interference.
Therefore amplitude is the sum of the
coherent contributions with random
phase shifts.
Unlike system noise, speckle is a real
electromagnetic measurement.
Correct using:
➢ multi-look processing
➢ spatial filtering.
23. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: ConclusionsConclusions
➢ SAR simulates a very long antenna using the “synthetic aperture principle”. The
“synthetic” antenna is generated by the motion of the platform (aircraft or satellite)
and through the use of signal processing of the Doppler shift associated with the motion
of the aircraft
➢ As a result SAR resolution is independent of the platform height and
proportional to the synthetic antenna length.
➢ For Envisat SAR (called ASAR), the length of the synthetic antenna is ~20 km
➢ Generally, depending on the processing, resolutions achieved are of the order of 1-2
metres for airborne radars and 5-50 metres for spaceborne radars.
➢ SAR processing requires very heavy computing after data acquisition
24. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Observing the oceanObserving the ocean
At the ocean's surface radar echoes from SARs are reflected through Bragg Scatering
Bragg scattering is the strong, resonnant signal for surface roughness (waves) on the scale of the radar
wavelength
The short Bragg-scale waves are formed in response to wind stress (need at least 3.25m/sec at C band).
For C-band,For C-band, λλrr ~ 6 cm~ 6 cm
25. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Observing the oceanObserving the ocean
Bragg scattering is affected by wind
Radar backscatter increases
with wind speed
No wind
Bragg scattering is affected by wind and many other things ...
26. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Observing the oceanObserving the ocean
➢ SAR measures sea surface roughness (Bragg waves - order cm)
➢ Sea surface roughness is affected by wind, waves, currents, surface
film (oil / biological matter) or sea ice
➢ Backscatter from the surface roughness is registered by SAR in both
amplitude and phase
Waves Oil spill Wind field Current front Internal waves
27. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Observing the oceanObserving the ocean
(a) Aircraft L-band VV SAR
image that includes the
north wall of the Gulf
Stream and adjacent shelf
near Cape Hatteras,
(b) Sketch map of
detectable features and
conditions in (a) including
the USNS Bartlett. [After
Lyzenga and Marmorino,
1998]
28. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Observing the oceanObserving the ocean
Bragg Scattering is modulated by three principal mechanisms that can enhance or suppress
average backscatter of ocean surface:
➢ Tilt modulation: change in local incident angle
➢ Hydrodynamic modulation: alteration of Bragg scale waves due to surface currents
➢ Damping by surfactants: suppression of Bragg scale waves
29. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Observing the oceanObserving the ocean
Long waves change the
slope of the small Bragg
waves, with maximum
backscatter on the face of
the wave, 90o
out of phase
with the wave amplitude.
30. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Observing the oceanObserving the ocean
Schematic plot of processes associated with the passage of a linear oceanic internalSchematic plot of processes associated with the passage of a linear oceanic internal
wave. Deformation of the thermocline (heavy solid line), orbital motions of the waterwave. Deformation of the thermocline (heavy solid line), orbital motions of the water
particles (dashed lines), streamlines of the velocity field (light solid lines), surfaceparticles (dashed lines), streamlines of the velocity field (light solid lines), surface
current velocity vectors (arrows in the upper part of the image), and variation of thecurrent velocity vectors (arrows in the upper part of the image), and variation of the
amplitude of the Bragg waves (wavy line at the top). [After Alpers, 1985]amplitude of the Bragg waves (wavy line at the top). [After Alpers, 1985]
31. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Observing the oceanObserving the ocean
An Additional influence on ocean backscatter is “Velocity Bunching”
➢ Artifact of SAR system
➢ Caused by moving ocean surface
➢ Moving waves introduce Doppler offsets and result in azimuth displacement ‘errors’ in
images
➢ Displacements can combine in non-linear fashion and cannot be removed
➢ Most prevalent for azimuth travelling waves
Velocity bunching does not change average backscatter; it introduces only local variations
due to location displacements
33. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Wind measurementsWind measurements
Backscatter σ depends on:
➢
wind speed
➢
wind direction relative to radar look direction
➢
radar incidence angle (known)
One measurement of σ gives several possible solutions of wind speed and direction
For SAR, information about wind direction is needed as auxiliary information
➢
Simplest solution is to take wind direction from numerical model
➢
Scatterometer (if colocated in time and space)
➢
Use wind streaks in the SAR-image
Empirical functions are then used to relate σ to wind speeds These functions are tuned to co-located
– ECMWF 10 m winds
– ERS-1 scatterometer data (σ)
CMOD-algorithm (C-band model function), with same algorithm later applied to SAR
35. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Wind measurementsWind measurements
SAR provides unique opportunity to monitor
oceans winds at high resolution
(typically 1 km x 1 km)
Available information and performance
➢ Wind speed accuracy: < 2 m/s (rms)
➢ Wind direction accuracy: ~25° (rms)
Applications
Near real-time:
➢ High resolution coastal wind field
measurement
➢ Improve Oil spill monitoring
➢ Coastal navigation
Long term:
➢ Wind farm design, wind resource
assessment.
➢ Understanding coastal dynamics
➢ Monitoring and study of meteorological
phenomena
37. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Wave measurementsWave measurements
Collard, F., F. Ardhuin and B. Chapron (2005): Extraction of
coastal ocean wave fields from SAR images. IEEE Journal
of Oceanic Engineering, 30(3), 526–533.
38. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Wave measurementsWave measurements
Instruments:
SAR is the only spaceborne instrument that can measured the two-dimensional ocean wave
spectra
concept operationally since 1991 (ERS-1, ERS-2, Envisat).
Envisat ASAR Wave Mode – improved successor of ERS Wave Mode
Sentinel-1 (2011->) - improved successor of Envisat ASAR
Wave Applications:
Wave nowcasting and wave forcasting: Assimilation into numerical wave models for better
swell wave prediction
Assessment of swell wave climate, globally
Coastal wave studies, and coastal wave climate
Swell tracking and storm location
Example of application:
http://www.esa.int/esaEO/SEMAKIV681F_economy_0.html
39. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Wave measurementsWave measurements
Agulhas Current region is
unique. It is a region where
most long waves and cross-
seas occur.
There is a high risk of
Rogue wave and
dangerous seas for ships.
40. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Internal WavesInternal Waves
There are internal waves all around Africa
41. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Current measurementsCurrent measurements
Direct measurements of the surface current velocity across the track of
the satellite are derived using Doppler Anomaly signal from ASAR
Doppler Anomaly/Velocity (ASAR WM)
Radial Wind Speed (ECMWF)
CDOP_23
Doppler Anomaly/Velocity predicted (NNT)
--
Residual Doppler Anomaly (current)
Slide from Dr. Fabrice Collard
42. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Current measurementsCurrent measurements
➢ Coverage = 400 km by 400 km wide swath
image
➢ Spatial resolution = 150m by 150m
➢ 1 ascending and 1 descending path every
3 days in the Agulhas Current region since
July 2007
ASAR Wide Swath mode uses five
predetermined overlapping antenna
beams to make up the swath.
43. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Ship detectionShip detection
Ships detected around False Bay at a
distance greater than 1km from the shore
on the 26th
August 2007. Green symbols
indicate that there is an ambiguity in the
detection. Symbols in red indicate a
definite ship identifications.
Credit: CLS radar division
44. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: Oils spill detectionOils spill detection
Prestige oil spill
Galicia – November 2002
BP oil spill
Gulf of Mexico – June 2010
45. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Synthetic Aperture Radars:Synthetic Aperture Radars: the futurethe future
SAR satellite missions Owner Launch date
(planned)
Frequency
band
ERS-2 ESA March 1995 C
Radarsat-1 CSA (operated by
MDA)
November 1995 C
ENVISAT ESA March 2002 C
ALOS PALSAR JAXA January 2006 L
COSMO SkyMed ASI June 2007 X
TerraSAR X DLR June 2007 X
Radarsat-2 MDA December 2007 C
SAOCOM (SIASGE) CONAE 2008 L
RISAT ISRO 2008 C
Sentinel1 ESA June 2011 C
HayYang-3 SOA 2012 X
Radarsat-C ? 2012 C
The number of SAR missions is booming
46. SSyntheticynthetic AApertureperture RRadar: introductionadar: introduction
Useful URLsUseful URLs
➢ ESA Earth Remote Sensing Home Page: http://earth.esa.int/
➢ Canada Centre for Remote Sensing: http://www.ccrs.nrcan.gc.ca/
➢ The German Remote Sensing Data Center: http://www.dfd.dlr.de/
➢ The NASA/JPL Imaging Radar Home Page: http://southport.jpl.nasa.gov/
➢ Remote Sensing Platforms and Sensors: http://quercus.art.man.ac.uk/rs/sat_list.cfm
➢ UCT Dept. Electr. Eng.: http://www.rrsg.uct.ac.za/applications/applications.html