This document describes a study of a satellite navigation system that uses measurements from both satellites and a fixed base transceiver station (BTS) to aid in positioning. The system allows positioning with fewer than the minimum number of satellites required. The BTS provides measurements of its time drift relative to the GNSS system to help solve the positioning equations. Simulations were conducted using both synthetic and real satellite data. Results showed that accuracy of position estimation depends on the time drift and distance between the user and the BTS.
Effect of grid adaptive interpolation over depth imagescsandit
A suitable interpolation method is essential to keep the noise level minimum along with the timedelay.
In recent years, many different interpolation filters have been developed for instance
H.264-6 tap filter, and AVS- 4 tap filter. This work demonstrates the effects of a four-tap lowpass
tap filter (Grid-adaptive filter) on a hole-filled depth image. This paper provides (i) a
general form of uniform interpolations for both integer and sub-pixel locations in terms of the
sampling interval and filter length, and (ii) compares the effect of different finite impulse
response filters on a depth-image. Furthermore, the author proposed and investigated an
integrated Grid-adaptive filter, that implement hole-filling and interpolation concurrently,
causes reduction in time-delay noticeably along with high PSNR .
POSITION ESTIMATION OF AUTONOMOUS UNDERWATER SENSORS USING THE VIRTUAL LONG B...ijwmn
This article contains a description of a mathematical model of an acoustic system for positioning
autonomous underwater sensors using the virtual long base method, which can be used during the vessel’s
collection of information over the deployed underwater network of autonomous sensors (underwater
wireless sensors network), during the initial determination of the geographical position of the bottom long
baseline elements or search, including cooperative, with the use of a swarm of autonomous surface vehicles
(UASV) of emergency submerged objects equipped with an emergency beacon (for example, aircraft and
ships); The article provides a scheme of an experimental set of equipment, as well as a description of the
conducted field experiments and their results.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Effect of grid adaptive interpolation over depth imagescsandit
A suitable interpolation method is essential to keep the noise level minimum along with the timedelay.
In recent years, many different interpolation filters have been developed for instance
H.264-6 tap filter, and AVS- 4 tap filter. This work demonstrates the effects of a four-tap lowpass
tap filter (Grid-adaptive filter) on a hole-filled depth image. This paper provides (i) a
general form of uniform interpolations for both integer and sub-pixel locations in terms of the
sampling interval and filter length, and (ii) compares the effect of different finite impulse
response filters on a depth-image. Furthermore, the author proposed and investigated an
integrated Grid-adaptive filter, that implement hole-filling and interpolation concurrently,
causes reduction in time-delay noticeably along with high PSNR .
POSITION ESTIMATION OF AUTONOMOUS UNDERWATER SENSORS USING THE VIRTUAL LONG B...ijwmn
This article contains a description of a mathematical model of an acoustic system for positioning
autonomous underwater sensors using the virtual long base method, which can be used during the vessel’s
collection of information over the deployed underwater network of autonomous sensors (underwater
wireless sensors network), during the initial determination of the geographical position of the bottom long
baseline elements or search, including cooperative, with the use of a swarm of autonomous surface vehicles
(UASV) of emergency submerged objects equipped with an emergency beacon (for example, aircraft and
ships); The article provides a scheme of an experimental set of equipment, as well as a description of the
conducted field experiments and their results.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
COMPARATIVE STUDY ON BENDING LOSS BETWEEN DIFFERENT S-SHAPED WAVEGUIDE BENDS ...cscpconf
Bending loss in the waveguide as well as the leakage losses and absorption losses along with a comparative study among different types of S-shaped bend structures has been computed with
the help of a simple matrix method.This method needs simple 2×2 matrix multiplication. The
effective-index profile of the bended waveguide is then transformed to an equivalent straight
waveguide with the help of a suitable mapping technique and is partitioned into large number of thin sections of different refractive indices. The transfer matrix of the two adjacent layers will be a 2×2 matrix relating the field components in adjacent layers. The total transfer matrix is
obtained through multiplication of all these transfer matrices. The excitation efficiency of the
wave in the guiding layer shows a Lorentzian profile. The power attenuation coefficient of the
bent waveguide is the full-width-half-maximum (FWHM) of this peak .Now the transition losses and pure bending losses can be computed from these FWHM datas.The computation technique
is quite fast and it is applicable for any waveguide having different parameters and wavelength of light for both polarizations(TE and TM)
3D Reconstruction from Multiple uncalibrated 2D Images of an ObjectAnkur Tyagi
3D reconstruction is the process of capturing the shape and appearance of real objects. In this project we are using passive methods which only use sensors to measure the radiance reflected or emitted by the objects surface to infer its 3D structure.
STATE SPACE GENERATION FRAMEWORK BASED ON BINARY DECISION DIAGRAM FOR DISTRIB...csandit
This paper proposes a new framework based on Binary Decision Diagrams (BDD) for the graph distribution problem in the context of explicit model checking. The BDD are yet used to represent the state space for a symbolic verification model checking. Thus, we took advantage of high compression ratio of BDD to encode not only the state space, but also the place where each state will be put. So, a fitness function that allows a good balance load of states over the nodes of an homogeneous network is used. Furthermore, a detailed explanation of how to
calculate the inter-site edges between different nodes based on the adapted data structure is presented
This presentation contains the concepts of frequency domain filtering of digital images. This includes the different kinds of filters used in frequency domain analysis,their characteristics and various phenomenon such as aliasing, inverse filtering etc. The contents are taken from variety of sources like Gonzalez image processing book, Pratt image processing book and some on-line resources.
A Compressed Sensing Approach to Image Reconstructionijsrd.com
compressed sensing is a new technique that discards the Shannon Nyquist theorem for reconstructing a signal. It uses very few random measurements that were needed traditionally to recover any signal or image. The need of this technique comes from the fact that most of the information is provided by few of the signal coefficients, then why do we have to acquire all the data if it is thrown away without being used. A number of review articles and research papers have been published in this area. But with the increasing interest of practitioners in this emerging field it is mandatory to take a fresh look at this method and its implementations. The main aim of this paper is to review the compressive sensing theory and its applications.
A MODIFIED DIRECTIONAL WEIGHTED CASCADED-MASK MEDIAN FILTER FOR REMOVAL OF RA...cscpconf
In this paper a Modified Directional Weighted Cascaded-Mask Median (MDWCMM) filter has
been proposed, which is based on three different sized cascaded filtering windows. The
differences between the current pixel and its neighbors aligned with four main directions. A
direction index is used for each edge aligned with a given direction. Then, the minimum of these
four direction indexes is used for impulse detection for each and every masking window.
Depending on the minimum direction indexes among the three windows one window is selected.
The filtering is done on this selected window. Extensive simulations showed that the MDWCMM
filter provides good performances of suppressing impulse with low noise level as well as for highly corrupted images from both gray level and colored benchmarked images.
COMPARATIVE STUDY ON BENDING LOSS BETWEEN DIFFERENT S-SHAPED WAVEGUIDE BENDS ...cscpconf
Bending loss in the waveguide as well as the leakage losses and absorption losses along with a comparative study among different types of S-shaped bend structures has been computed with
the help of a simple matrix method.This method needs simple 2×2 matrix multiplication. The
effective-index profile of the bended waveguide is then transformed to an equivalent straight
waveguide with the help of a suitable mapping technique and is partitioned into large number of thin sections of different refractive indices. The transfer matrix of the two adjacent layers will be a 2×2 matrix relating the field components in adjacent layers. The total transfer matrix is
obtained through multiplication of all these transfer matrices. The excitation efficiency of the
wave in the guiding layer shows a Lorentzian profile. The power attenuation coefficient of the
bent waveguide is the full-width-half-maximum (FWHM) of this peak .Now the transition losses and pure bending losses can be computed from these FWHM datas.The computation technique
is quite fast and it is applicable for any waveguide having different parameters and wavelength of light for both polarizations(TE and TM)
3D Reconstruction from Multiple uncalibrated 2D Images of an ObjectAnkur Tyagi
3D reconstruction is the process of capturing the shape and appearance of real objects. In this project we are using passive methods which only use sensors to measure the radiance reflected or emitted by the objects surface to infer its 3D structure.
STATE SPACE GENERATION FRAMEWORK BASED ON BINARY DECISION DIAGRAM FOR DISTRIB...csandit
This paper proposes a new framework based on Binary Decision Diagrams (BDD) for the graph distribution problem in the context of explicit model checking. The BDD are yet used to represent the state space for a symbolic verification model checking. Thus, we took advantage of high compression ratio of BDD to encode not only the state space, but also the place where each state will be put. So, a fitness function that allows a good balance load of states over the nodes of an homogeneous network is used. Furthermore, a detailed explanation of how to
calculate the inter-site edges between different nodes based on the adapted data structure is presented
This presentation contains the concepts of frequency domain filtering of digital images. This includes the different kinds of filters used in frequency domain analysis,their characteristics and various phenomenon such as aliasing, inverse filtering etc. The contents are taken from variety of sources like Gonzalez image processing book, Pratt image processing book and some on-line resources.
A Compressed Sensing Approach to Image Reconstructionijsrd.com
compressed sensing is a new technique that discards the Shannon Nyquist theorem for reconstructing a signal. It uses very few random measurements that were needed traditionally to recover any signal or image. The need of this technique comes from the fact that most of the information is provided by few of the signal coefficients, then why do we have to acquire all the data if it is thrown away without being used. A number of review articles and research papers have been published in this area. But with the increasing interest of practitioners in this emerging field it is mandatory to take a fresh look at this method and its implementations. The main aim of this paper is to review the compressive sensing theory and its applications.
A MODIFIED DIRECTIONAL WEIGHTED CASCADED-MASK MEDIAN FILTER FOR REMOVAL OF RA...cscpconf
In this paper a Modified Directional Weighted Cascaded-Mask Median (MDWCMM) filter has
been proposed, which is based on three different sized cascaded filtering windows. The
differences between the current pixel and its neighbors aligned with four main directions. A
direction index is used for each edge aligned with a given direction. Then, the minimum of these
four direction indexes is used for impulse detection for each and every masking window.
Depending on the minimum direction indexes among the three windows one window is selected.
The filtering is done on this selected window. Extensive simulations showed that the MDWCMM
filter provides good performances of suppressing impulse with low noise level as well as for highly corrupted images from both gray level and colored benchmarked images.
How Visma works with UX and how we are working on going from feature driven to user centered design.
Created in Keynot and exported to PPT - that's why there are weird typography.
In a communications system, the channel is affected by an additive white Gaussian noise (AWGN)
and a fading due to a distance between a transmitter and a receiver. Especially, there are many kinds of
channel fadings. Depending on the moving speeds of transmitters or receivers, a fading type can be a slow
fading or a fast fading (i.e., the product of 0.1 and coherence time than smaller or larger than the symbol
period of signal are corresponding to fast and slow fadings). Moreover, a channel can be referred as a
selective fading or a flat fading corresponding to the product of 0.1 and coherence bandwidth than smaller
or larger than the bandwidth of signal. These above effects can suffer received signals at a destination.
Hence the performance of received signals in term of bit-error-rate (BER) is much degraded.
In order to overcome these issues, communications systems would be carefully designed. In detail,
application systems operating over the AWGN channels would use coding schemes to combat an additive
white noise. However, if environment is affected by fading, coding techniques only solve a fast fading.
It implies that, coding schemes degrade received signals when they go through slow fading channels. In
this case, an interleaving technique would be added to a communications system. In order to overcome
the fading channels, besides, using an interleaver as above, we can exploit the diversity of multi-path. It
implies that the effects of fading can be combated by transmitting the original signals over multiple paths
(experiencing independent fading) and then combining all received signals at the receiver. There are many
kinds of diversities to mitigate this issue, such as diversity in time, frequency, and space. Correspondingly,
a lot of state-of-art methods are given, viz. diversity receiving and transmitting, OFDM, space-time block
codes, MIMO, Cooperation and etc.
In summary, the main scope of this report is modeling a communications system. First, I create a
basic communications system, where it includes the modulation/demodulation using a QPSK modulation,
a channel type is an AWGN channel. Secondly, a coder/decoder scheme is added to a transmitter/receiver to
improve received signals. Thirdly, the fading channel is considered when a receiver/transmitter is moving.
It means that the slow fading is mentioned. The performance is shown to prove that the received signal
2
is degraded whether a coding scheme is used or not. Finally, an interleaver/deinterleaver is used to solve
this problem.
Besides, the performance in terms of BER is used to verify a validity of these above techniques in a
communications system.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Ill-posedness formulation of the emission source localization in the radio- d...Ahmed Ammar Rebai PhD
To contact the authors : tarek.salhi@gmail.com and ahmed.rebai2@gmail.com
In the field of radio detection in astroparticle physics, many studies have shown the strong dependence of the solution of the radio-transient sources localization problem (the radio-shower time of arrival on antennas) such solutions are purely numerical artifacts. Based on a detailed analysis of some already published results of radio-detection experiments like : CODALEMA 3 in France, AERA in Argentina and TREND in China, we demonstrate the ill-posed character of this problem in the sens of Hadamard. Two approaches have been used as the existence of solutions degeneration and the bad conditioning of the mathematical formulation problem. A comparison between experimental results and simulations have been made, to highlight the mathematical studies. Many properties of the non-linear least square function are discussed such as the configuration of the set of solutions and the bias.
Boosting CED Using Robust Orientation Estimationijma
n this paper, Coherence Enhancement Diffusion (CED) is boosted feeding external orientation using new
robust orientation estimation. In CED, proper scale selection is very important as the gradient vector at
that scale reflects the orientation of local ridge. For this purpose a new scheme is proposed in which pre
calculated orientation, by using local and integration scales. From the experiments it is found the proposed
scheme is working much better in noisy environment as compared to the traditional Coherence
Enhancement Diffusion
A new look on performance of small-cell network with design of multiple anten...journalBEEI
A downlink of small-cell network is studied in this paper studies in term of outage performance. We benefit by design of multiple antennas at the base station and fullduplex transmission mode. The scenario of multiple surrounded small-cell networks is considered to look the impact of interference. We derive the closed-form expression of outage probability to show performance of mobile user. We investigate target rate is main factor affecting to outage performance. According to the considered system, simulation results indicate reasonable value of outage probability and throughput as well. Finally, Monte-Carlo simulation method is deployed to determine exactness of main results found in this article. Finally, the considered system can exhibit improved performance if controlling interference term.
Time of arrival based localization in wireless sensor networks a non linear ...sipij
In this paper, we aim to obtain the location information of a sensor node deployed in a Wireless Sensor Network (WSN). Here, Time of Arrival based localization technique is considered. We calculate the position information of an unknown sensor node using the non- linear techniques. The performances of the techniques are compared with the Cramer Rao Lower bound (CRLB). Non-linear Least Squares and the Maximum Likelihood are the non-linear techniques that have been used to estimate the position of the unknown sensor node. Each of these non-linear techniques are iterative approaches, namely, Newton
Raphson estimate, Gauss Newton Estimate and the Steepest Descent estimate for comparison. Based on the
results of the simulation, the approaches have been compared. From the simulation study, Localization
based on Maximum Likelihood approach is having higher localization accuracy.
Geospatial Data Acquisition Using Unmanned Aerial SystemsIEREK Press
The Rivers State University campus in Portharcourt is one of the university campuses in the city of Portharcourt,
Nigeria covering over 21 square kilometers and housing a variety of academic, residential, administrative and other
support buildings. The University Campus has seen significant transformation in recent years, including the
rehabilitation of old facilities, the construction of new academic facilities and the most recent update on the creation
of new collages, faculties and departments. The current view of the transformations done within the University
Campus is missing from several available maps of the university. Numerous facilities have been constructed on the
University Campus that are not represented on these maps as well as the qualities associated with these facilities.
Existing information on the various landscapes on the map is outdated and it needs to be streamlined in light of
recent changes to the University's facilities and departments. This research article aims to demonstrate the
effectiveness of unmanned aerial systems (UAS) in geospatial data collection for physical planning and mapping of
infrastructures at the Rivers State University Port Harcourt campus by developing a UAS-based digital map and
tour guide for RSU's main campus covering all collages, faculties and departments and this offers visitors, staff and
students with location and attribute information within the campus.
Methodologically, Unmanned Aerial Vehicles were deployed to obtain current visible images of the campus
following the growth and increasing infrastructural development. At a flying height of 76.2m (250 ft), a DJI
Phantom 4 Pro UAS equipped with a 20-megapixel visible camera was flown around the campus, generating
imagery with 1.69cm spatial resolution per pixel. To obtain 3D modeling capabilities, visible imagery was acquired
using the flight-planning software DroneDeploy with a near nadir angle and 75 percent front and side overlap.
Vertical positions were linked to the World Geodetic System 1984 and horizontal positions to the 1984 World
Geodetic Datum universal transverse Mercator (UTM) (WGS 84). To match the UAS data, GCPs were transformed
to UTM zone 32 north.
Finally, dense point clouds, DSM, and an orthomosaic which is a geometrically corrected aerial image that provides
an accurate representation of an area and can be used to determine true distances, were among the UAS-derived
deliverables.
Availability of a Redundant System with Two Parallel Active Componentstheijes
This paper considers a redundant system which consists of two parallel active components. The time-to-failure
and the time-to-repair of the components follow an exponential and a general distribution, respectively. The
repairs of failed components are randomly interrupted. The time-to-interrupt is taken from an exponentially
distributed random variable and the interrupt times are generally distributed. We obtain the availability for the
system
Boosting ced using robust orientation estimationijma
In this paper, Coherence Enhancement Diffusion (CED) is boosted feeding external orientation using new
robust orientation estimation. In CED, proper scale selection is very important as the gradient vector at
that scale reflects the orientation of local ridge. For this purpose a new scheme is proposed in which pre
calculated orientation, by using local and integration scales. From the experiments it is found the proposed
scheme is working much better in noisy environment as compared to the traditional Coherence
Enhancement Diffusion
LOCALIZATION SCHEMES FOR UNDERWATER WIRELESS SENSOR NETWORKS: SURVEYIJCNCJournal
Underwater Wireless Sensor Networks (UWSNs) enable a variety of applications such as fish farming and water quality monitoring. One of the critical tasks in such networks is localization. Location information can be used in sensor networks for several purposes such as (i) data tagging in which sensed information is not useful for the application unless the location of the sensed information is known, (ii) tracking objects or (iii) multi-hop data transmission in geographic routing protocols. Since GPS does not work well underwater, several localization schemes have been developed for UWSNs. This paper surveys the state-ofthe-art of localization schemes for UWSNs. It describes the existing schemes and classifies them into different categories. Furthermore, the paper discusses some open research issues that need further investigation in this area.
Path Loss Prediction by Robust Regression Methodsijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
The Global Positioning System (GPS) is a network of dozens of satellites that hover out in space with the purpose of allowing people to identify their location on earth. Signals from the GPS satellites are transmitted to a GPS receiver on earth’s surface to pinpoint the satellite’s location in space. With knowledge of the satellite’s orbit and utilizing time information, a GPS receiver is able to determine its own location under the condition that four satellites are within range. However, due to the inaccuracy of the receiver’s clock when utilizing commercial GPS units for low cost, the distances calculated, called pseudo-ranges, are not accurate. Ideally, these four pseudo-ranges should intersect at a single point for a true receiver-satellite distance, but the unsynchronized clocks prevent this. To accurately determine a location, a few algebraic computations are necessary to make the adjustment for the imperfect information. These algebraic computations consist of deriving, implementing, and testing two algorithms, the Gradient Descent and Gauss Newton algorithms. Throughout this project, we will be exploring how these algorithms contribute to resolving the clock error when determining the true pseudo- range under noiseless conditions.
Design of Linear Array Transducer Using Ultrasound Simulation Program Field-IIinventy
This paper analyze the effect of number of elements of linear array and frequency influence the
image quality in a homogenous medium. Linear arrays are most common for conventional ultrasound imaging,
because of the advantages of electronic focusing and steering. Propagation of ultrasound in biological tissues is
of nonlinear in nature. But linear approximation in far-field is promising solution to model and simulate the
real time ultrasound wave propagation. The simulation of ultrasound imaging using linear acoustics has been
most widely used for understanding focusing, image formation and flow estimation, and it has become a
standard tool in ultrasound research. . In this paper the ultrasound field generated from linear array transducer
and propagation through biological tissues is modeled and simulated using FIELD II program.
Fast Object Recognition from 3D Depth Data with Extreme Learning MachineSoma Boubou
Object recognition from RGB-D sensors has recently emerged as a renowned and challenging research topic. The current systems often require large amounts of time to train the models and to classify new data. We proposed an effective and fast object recognition approach from 3D data acquired from depth sensors such as Structure or Kinect sensors.
Our contribution in this work} is to present a novel fast and effective approach for real-time object recognition from 3D depth data:
- First, we extract simple but effective frame-level features, which we name as differential frames, from the raw depth data.
- Second, we build a recognition system based on Extreme Learning Machine classifier with a Local Receptive Field (ELM-LRF).
Similar to Report Satellite Navigation Systems (20)
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
insect taxonomy importance systematics and classification
Report Satellite Navigation Systems
1. POLITECNICO DI TORINO
Telecommunication Engineering
Academic Year 2014/15
Demetrio Ferro
Information Theory and
Digital Signal Processing
E-mail - Linkedin
Alex Minetto
Information Theory and
Digital Signal Processing
E-mail - Linkedin
BTS-Assisted Positioning System - Simulation and
Performance Analysis
Abstract
This work concerns the study of a satellite navigation system providing a solution to the positioning problem with
the support of a fixed Base Transceiver Station (BTS), which will work as an aiding peer.
The main idea is to use less signals coming from satellites than the minimum required since user’s coverage
may not be full. The amount of information required to solve the Position, Velocity, Time (PVT) equations will be
provided by a fixed aiding peer which provides measurements of its time drift with respect to the GNSS system.
The problem was formulated and simulated by using both synthetic satellites positions generated randomly and
by using real ones. The results of the study were discussed in terms of accuracy of the position estimation.
Master of Science Academic Project - 02LPXOT Satellite Navigation Systems - Professor: Fabio Dovis
Contents
1 Introduction 1
2 Problem Formulation 1
3 Performance Evaluation 4
4 Simulation 6
4.1 Synthetic Data Simulation - - - - - - - - - - - - - - - - 6
4.2 Real Data Simulation - - - - - - - - - - - - - - - - - - - - 7
5 Summary of Results 8
5.1 Time Drift of the two peers - - - - - - - - - - - - - - - - 8
5.2 Distance of the two peers - - - - - - - - - - - - - - - - - 9
6 Further comments 10
1. Introduction
This work concerns the study of a satellite nav-
igation system providing a solution to the posi-
tioning problem with the support of a fixed Base
Transceiver Station (BTS), which will work as an
aiding peer.
One of the main issues with satellite navigation sys-
tems discussed most is the availability: the service
may not have a good coverage on the user’s area.
The main idea is to use less satellites than the mini-
mum amount which is required to localize the user,
asking for the help of an aiding peer which provides
measurements of its distance from satellites which
it has in view.
Such problem was formulated by considering a sin-
gle user which has exactly three satellites in view,
but communicates with a fixed BTS which is close
to him, and has a better service coverage, so that it
can receive signal from at least another satellite.
The assumption leading to this formulation is that,
even if the user position is not exactly the same as
the antenna’s, it is close enough to let the position-
ing computation algorithm converge to a solution
which is close enough to the true one.
2. Problem Formulation
The problem, by its physical nature, consists of
finding the user’s coordinates, which, in their rela-
tive reference system uniquely identify the user’s
position.
xu = [ xu yu zu ] (1)
The navigation problem is generally solved by com-
puting the distance from each satellite to the user:
ri. Then, by trilateration, the actual user’s position
is computed.
r2
i = (xi −xu)2
+(yi −yu)2
+(zi −zu)2
(2)
Since distance measurements involve time, there
is a fourth unknown: time misalignment between
the satellite navigation system time reference and
the user’s clock: δtu, which introduces a spatial
uncertainty but = c·δtu.
2. BTS-Assisted Positioning System - Simulation and Performance Analysis — 2/10
r1 r2 r3 r4
(x1,y1,z1) (x2,y2,z2) (x3,y3,z3) (x4,y4,z4)
(xu,yu,zu)
d
d
d
d
d
d
d
d
d
d
f
f
f
f
f
f
f
f
f
¡
¡
¡
¡
¡
¡
¡
¡
¡
Figure 1. Satellite Positions (xi,yi,zi), User Position (xu,yu,zu) and distances from each satellite ri.
From now on, distances from satellites will be called
pseudoranges ρi, since they identify the radius of
a sphere centered on each satellite, tangent to the
user device.
ρi = (xi −xu)2 +(yi −yu)2 +(zi −zu)2 −but (3)
The equations leading to the solution of the naviga-
tion problem may be linearized through the Taylor
expansion around a known location:
ˆxu = (ˆxu, ˆyu, ˆzu, ˆbut) (4)
The linearization consists in the following:
∆ρi = ˆρi −ρi = axi∆xu +ayi∆yu +azi∆zu −∆but (5)
axi =
xi − ˆxu
ˆri
, ayi =
yi − ˆyu
ˆri
, azi =
yi − ˆyu
ˆri
ˆri = (xi − ˆxu)2 +(yi − ˆyu)2 +(zi − ˆzu)2
Since the problem consists of finding four unknowns,
its solution needs to involve at least four equations,
so at least four satellites have to be seen by the user.
∆ρ1 = ax1∆xu +ay1∆yu +az1∆zu −∆but
∆ρ2 = ax2∆xu +ay2∆yu +az2∆zu −∆but
...
∆ρn = axn∆xu +ayn∆yu +azn∆zu −∆but
(6)
In matrix notation, we may write:
∆ρ = H·∆xu (7)
By defining the matrices ∆ρ,H,∆xu as follows:
∆ρ =
∆ρ1
∆ρ2
...
∆ρn
H =
ax1 ay1 az1 1
ax2 ay2 az2 1
...
...
...
...
axn ayn azn 1
∆xu =
xu − ˆxu
yu − ˆyu
zu − ˆzu
−(but − ˆbut)
=
∆xu
∆yu
∆zu
−∆but
(8)
The solution of the linear equations system can be
obtained, by using a Least Mean Square approach,
from:
∆xu = (HT
·H)−1
HT
∆ρ (9)
The position obtain in this way may be used to
compute iteratively the actual user’s position with
higher accuracy, by setting
ˆxu = (ˆxu +∆xu, ˆyu +∆yu, ˆzu +∆zu, ˆbut −∆but) (10)
.Pseudorange measurements are affected by noise,
assumed to be a realization of a random variable:
δρi ∼ N (0,σ2
UERE), i.i.d. (11)
The standard deviation of the measurements is called
σUERE: User Equivalent Range Error.
Since the pseudorange measurements are affected
by noise, at the end of the computation, the position
estimation will be the realization of random variable
affected by bias and variance.
∆ρ +δρ = H·(∆xu +δxu) (12)
3. BTS-Assisted Positioning System - Simulation and Performance Analysis — 3/10
ρ1 ρ2 ρ3 ρ4
(x1,y1,z1) (x2,y2,z2) (x3,y3,z3) (x4,y4,z4)
(xu,yu,zu) (xB,yB,zB)
e
e
e
e
e
e
e
e
e
e
e
e
e
¡
¡
¡
¡
¡
¡
¡
¡
¡
¡
¡
¡
¡
Figure 2. Satellite Positions (xi,yi,zi), User Position (xu,yu,zu), BST Position (xB,yB,zB) and relative pseudoranges ρi.
The average magnitude of the error committed in
considering the computed one as true position, is
called bias of the estimation.
Bias [ˆxu] = E[ˆxu −xu] = E[δxu]
= (HT ·H)−1HT ·E[δρ] = 0
(13)
While the covariance of the estimated position is:
COV [δxu] = (HT ·H)−1HT ·COV[δρ]·
H(HT ·H)−1
= (HT ·H)−1 ·σ2
UERE
(14)
One of the most interesting quantity of interest is the
trace matrix G = (HT ·H)−1, because it determines
the Geometric Diluition of Precision (GDOP):
GDOP = tr{(HT ·H)−1} (15)
The variance of the error will be defined by using
this coefficient, which refers to the geometry of the
satellites with respect to the user:
σˆxu
= σ2
xu
+σ2
yu
+σ2
zu
+σ2
xbut
= GDOP·σUERE
(16)
Of course it is desirable that the variance of the
estimation is not too high, so that the computed
position converges to the right one.
Once considered the the problem formulation, more
restrictive assumptions may be done.
By supposing that user has three satellites in view,
it has to communicate with an aiding peer which
has a fourth satellite in view, both measuring pseu-
doranges from the satellites they see.
Once the base station has computed its own pseu-
dorange, transmits it to the user, who employs it to
find its own position.
Given that the user position is not the same as the
base station’s, the fourth pseudorange ρ4 will intro-
duce errors because it refers to:
xB = (xB,yB,zB,bbt) (17)
The model built in this project tries to give a solu-
tion to the localization problem, by using as first
approximation point the base station location:
(ˆxu, ˆyu, ˆzu, ˆbut) = (xB,yB,zB,bbt) (18)
Given that if the user and the antenna are not sup-
posed to be synchronous, it is important to take into
account the ratio:
γub =
∆bbt
∆but
. (20)
By considering that the antenna may have a lower
misalignment with respect to the GNSS time refer-
ence, we may set γub = 1 as a worst condition.
The linear system of equations may be written, in
matrix notation, as:
∆Dρ = DH·∆xu (21)
4. BTS-Assisted Positioning System - Simulation and Performance Analysis — 4/10
∆ρ1 −∆ρ2 = (ax1 −ax2)∆xu +(ay1 −ay2)∆yu +(az1 −az2)∆zu
∆ρ1 −∆ρ3 = (ax1 −ax3)∆xu +(ay1 −ay3)∆yu +(az1 −az3)∆zu
∆ρ1 −∆ρ4 = (ax1 −ax4)∆xu +(ay1 −ay4)∆yu +(az1 −az4)∆zu −(∆but −∆bbt)
∆ρ1 = ax1∆xu +ay1∆yu +az1∆zu −∆but
(19)
By defining respectively the matrices ∆Dρ and DH:
∆Dρ =
∆ρ1 −∆ρ2
∆ρ1 −∆ρ3
∆ρ1 −∆ρ4
∆ρ1
(22)
DH =
ax1 −ax2 ay1 −ay2 az1 −az2 0
ax1 −ax3 ay1 −ay3 az1 −az3 0
ax1 −ax4 ay1 −ay4 az1 −az4 1−γub
ax1 ay1 az1 1
This time, the solution to the positioning problem
is given by:
∆xu = (DH)−1
·∆Dρ (23)
Since the matrix DH is square, it results to be in-
vertible provided that it is non-singular.
3. Performance Evaluation
In order to evaluate the performances of such an
estimator, the error on pseudorange measurements
has to be taken into account:
∆Dρ +δDρ = DH·(∆xu +δxu) (24)
First of all, from the physical model:
δDρ =
δDρ1
δDρ2
δDρ3
δDρ4
=
δρ1 −δρ2
δρ1 −δρ3
δρ1 −δρ4(B)
δρ1
(25)
It is possible to notice that now the components of
δDρ are not i.i.d.:
δDρi ∼ N (0,2σ2
UERE), i = 1,2
δDρ3 ∼ N (δρ4,geom,2σ2
UERE)
δDρ4 ∼ N (0,σ2
UERE)
(26)
In this formulation, the pseudorange ρ4, being mea-
sured by the antenna and not by the user, carries
two error components:
δρ4(B)
= δρ4(U)
+δρ4,geom (27)
It is important to notice that the two errors have
different nature:
δρ4(U)
∼ N (0,σ2
UERE)
δρ4,geom, Deterministic
δρ4(B)
∼ N (δρ4,geom,σ2
UERE)
(28)
In order to have a metric of the error, Bias and
Variance of the error has to be computed.
Bias [ˆxu] = E[ˆxu −xu] = E[δxu]
= (DH)−1 ·E[δDρ]
= (DH)−1 ·[ 0, 0, δρ4,geom, 0 ]T
(29)
COV[δxu] = (DH)−1
COV[δDρ](DHT
)−1
(30)
The steps to the actual computation of the covari-
ance matrix are reported in Equations 31, 32.
The previous can be simplified in the following
expression:
COV[δDρ] = C1 ·σ2
UERE +C2 ·δρ2
4,geom (33)
where C1 and C2 are opportunely set to:
C1 =
2 1 1 1
1 2 1 1
1 1 2 1
1 1 1 1
(34)
C2 =
0 0 0 0
0 0 0 0
0 0 1 0
0 0 0 0
(35)
The covariance of the error can be expressed easier:
COV[δxu] = (DH)−1 ·COV[δDρ]·(DHT
)−1
(36)
6. BTS-Assisted Positioning System - Simulation and Performance Analysis — 6/10
4. Simulation
The simulation of the model discussed in the previ-
ous sections was made in Matlab ,
4.1 Synthetic Data Simulation
In the first instance of simulations, it is simulated a
scenario where:
- The Aiding Peer is located in the origin of the
reference system: xB = [0,0,0, ˆbbt].
- The User is located at a fixed distance from the
antenna. xu = xB + 500,500,0,
ˆbbt
γub
- The Satellite Vehicles (SV) have random position:
xSV ∼ N (0,
√
2e7)
- The SV follow a random linear trajectory.
(The speed of each SV has been altered from its
realistic value, in order to see what happens with
a smaller/larger variation in the skyplot).
- The solution of the problem is obtained by us-
ing an algorithm which solves the Linear System
of equations iterating on pseudorange measure-
ments:
1. Measure pseudoranges from the satellites in
view;
2. (a) If they are at least 4, solve Equation (9).
(b) If they are 3 instead, get the pseudorange
measurement from the BTS and solve
Equation (23).
3. (a) If the position estimation obtained at step
(2) has small enough bias, (||ˆxu −xu||
10[m]) return the computed position.
(b) If the bias is not much large, update the
approximation point to the computed one
and go to step (1).
(c) If the computed position is way too far
from the BTS, (||ˆxu −xB|| 1500[m]), it
means that the algorithm does not con-
verge to a position which would be cov-
ered by the BTS.
- The bias of the computed position is shown in
magnitude an on the single coordinates.
Figure 4. Random constellation of Satellites
400
450
500
550
600
300
350
400
450
500
−100
−80
−60
−40
−20
0
20
40
60
80
100
User Position
Z[m]
Solution Convergence
Y [m] X [m]
Figure 5. Convergence of the solution
As shown in Figure 4, by using a random generated
constellation of satellites following a random linear
trajectory, it is possible see in Figure 5 that the
computation of user’s position converges even if it
lasts long.
Since the solution will be affected by bias, on all
the coordinates, in Figure 6 it is have reported the
overall bias that the user experiences:
E[||xu − ˆxu||] = (xu − ˆxu)2 +yu − ˆyu)2 +(zu − ˆzu)2
(41)
Then, in Figure 7 it is reported the bias on the single
coordinates:
E[xu − ˆxu] = [(xu − ˆxu), (yu − ˆyu), (zu − ˆzu)]. (42)
As previously shown, for synthetic SV positions,
the algorithm that iteratively solves PVT equations
actually converges.
7. BTS-Assisted Positioning System - Simulation and Performance Analysis — 7/10
0 20 40 60 80 100 120
0
50
100
150
200
250
Overall Bias of Synthetic Simulation
Iterations
Bias[m]
177.43
112.68
47.93
Figure 6. Bias of the norm of the solution.
0 20 40 60 80 100 120
0
20
40
60
80
100
120
140
160
180
Synthetic Simulation Bias
Iteration
Bias[m]
X−Coordinate
Y−Coordinate
Z−Coordinate
Figure 7. Bias on the coordinates of the solution.
4.2 Real Data Simulation
In order to give more consistency to the simulation,
it is made with real data, by the following steps:
- Measurements are obtained by a GPS receiver
located here at Polytechnic of Turin, ECEF coor-
dinates are rougly xu = [4.47, 0.60, 4.49, 0.73]·
106 [m], since the measurements obtained were
discontinuous, a subset of the whole data collec-
tion (where they have a continuous behaviour)
was selected.
- One of the pseudorange measurements is altered
as if it was obtained by an aiding peer located in
xB = xU ·[1,1,1,γub]+[500,500,0,0].
- The solution of the problem is obtained by using
the same algorithm as previously.
- The bias of the computed position is shown in
magnitude and on ECEF coordinates.
−505101520
x 10
6
−1 −0.5 0 0.5 1
x 10
7
−5
0
5
10
15
20
x 10
6
X [m]
PRN 21
Satellites Constellation
Y [m]
PRN 1
PRN 16
PRN 6
Z[m]
Figure 8. Real satellites constellation
4.4723
4.4723
4.4724
4.4724
4.4724
x 10
6
6.0142
6.0143
6.0144
6.0145
6.0146
x 10
5
4.4925
4.4926
4.4927
4.4927
4.4928
x 10
6
User Position
Z[m]
Navigation Solution
X [m]
Y [m]
Figure 9. Real position estimation
In Figure 8 are reported the real satellites and user’s
position. As it is possible to appreciate in Figure 9,
the positioning solution gets very close to the actual
position, but is always biased.
In Figure 10 is reported the overall bias of the sim-
ulation, whereas in Figure 11 is reported the single-
coordinate bias.
As we can immediately see from the plots, the sce-
nario generated with random SV positions gives a
sharper bias curve.
8. BTS-Assisted Positioning System - Simulation and Performance Analysis — 8/10
0 5 10 15 20 25 30 35 40
0
10
20
30
40
50
60
70
80
90
21.58
43.01
0.16
Overall Bias on User’s Estimated Position
Iterations
Bias[m]
Figure 10. Bias of the norm of the solution
0 5 10 15 20 25 30 35 40
0
10
20
30
40
50
60
70
ECEF Coordinates − Baias Behaviour
Iterations
Bias[m]
X−Coordinate
Y−Coordinate
Z−Coordinate
Figure 11. Bias of the norm of the solution
5. Summary of Results
The algorithm was tested by running a Monte Carlo
simulation, with the generation of random satellites’
positions following random trajectories.
The output of the simulation declared about 60%
convergency of the implemented solution.
Once the performances of such a solution are ob-
tained by simulating both with synthetic and real
data, the aim is to study when the new parameters
introduced achieve better performances or exploit
most the utility the solution.
5.1 Time Drift of the two peers
First of all, consider the issues involved with the
parameter γub = ∆bbt
∆but
.
In order to do that, fix the Satellite constellation
standing above the user and the aiding peer. Fo-
cused on an optimal geometry, reported in Figure
12: the user has in view three equispaced satellites
at the horizon, while the fourth is seen by the an-
tenna.
From the known results (29), let the user to ob-
tain the fourth measure from a satellite close to the
zenith of the aiding peer because it introduces less
bias.
Let γub vary in [0, 2], in order to understand what
happens when the misalignment ratio is different.
One could expect that having a very small value
of γub would lead to better performances, since it
introduces less error in pseudorange measurement.
−2
−1
0
1
2
x 10
7
−2
−1
0
1
2
x 10
7
−1.5
−1
−0.5
0
0.5
1
1.5
2
x 10
7
S1
X [m]
S4
Satellites Constellation
S2
Y [m]
S3
Z[m]
Figure 12. Optimal Constellation of Satellites
0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
0
0.5
1
1.5
2
2.5
x 10
6 γ Analysis
γ
Bias[m]
Bias Samples
Sliding Mean
Figure 13. Bias[ˆxu] varying with γub ∈ [0,2].
Executing the same algorithm for different values
of γub, it is obtained the plot reported in Figure 13,
where it is possible to see that a very low value of
bias is obtained for γub = 1.
The reason of this is not so immediate by looking at
9. BTS-Assisted Positioning System - Simulation and Performance Analysis — 9/10
formulas, but results to be pretty easy to expect one
thinks that the algorithm solves the LS of equations
to find a value but.
If the pseudorange ρ4 measured by the BTS is af-
fected by exactly the same time misalignment as
the other ones measured by the user, the matrix DH
has the same coefficients on all the rows, this makes
the search for a but value much easier.
So, having an aiding receiver with time drift which
is way too far from the user’s leads to a worse esti-
mation of the position.
5.2 Distance of the two peers
Another important issue of our problem is how
much the bias and the variance vary when the dis-
tance of the user from the aiding peer vary.
The algorithm was run with ||xB −xu|| ∈ [0,1500]
meters, by considering the coverage of a standard
telecommunication BTS.
From the output shown in Figure14, it is possible
to notice that, the theoretical value assumed by the
bias depends mostly on the User-BTS distance on
the slant range (δρ4,geom).
In particular, it is going to assume higher values
when the measurements from the SV used as aid to
the user is located close to the horizon.
Satellites at the zenith of the aiding peer not visible
by the user would carry a lower bias. This may find
application in urban environments.
After these considerations, it is possible to discuss
applicability of such a solution.
The main idea is to understand how much it is con-
sistent for a user to get a position even if it is af-
fected by a lot of bias. It may be useful to introduce
a new metric for the Optimality of our solution:
ψU,B =
E[||ˆxu −xu||]
||xB −xu||
(43)
that is a ratio between amount of bias we have at a
given distance by the aiding peer.
0 500 1000 1500
16
18
20
22
24
26
28
30
32
34
36
Average Bias and Variance
Distance User−BTS [m]
[m]
Variance
Average Bias
Figure 14. Bias and Variance or the position
estimation varying with User-BTS distance
0 500 1000 1500
10
−2
10
−1
10
0
10
1
10
2
Optimality
Distance User−BTS [m]
Log(Ψ)
23 m
Figure 15. Trade-off of the applicability of our
solution over distance
This consideration leads to a trade-off between the
mean error that the user is disposed to accept with
respect to the possibility of getting positioned where
the aiding peer is.
In this simulation, it is supposed that when the error
is larger than the distance from the next given point,
it is convenient for him to get the position of that
point.
With this assumption, it is possible to found out that
when the factor ψU,B 1, the user is so far from the
aiding peer that the bias he gets by implementing
this solution is less than the one he would accept by
being located at the BTS position.
From real data simulations, as shown in Figure 15,
ψU,B = 1 at about 23 meters, so it is convenient for
users who are further than this distance.
10. BTS-Assisted Positioning System - Simulation and Performance Analysis — 10/10
6. Further comments
The implementation of such a solution may involve
further considerations, which exploit the benefits of
using of a fixed aiding peer.
- At first, the BTS has a known position. By using
just one satellite in view, it may compute its own
time misalignment with respect to the GNSS time
reference.
This may be used to adjust its clock and keep the
value assumed by ∆bbt much smaller than the one
assumed by ∆but.
Moreover, the antenna may use a receiver whose
clock frequency drifts less from the reference one,
with respect to the user’s.
This leads to the consideration that the time mis-
alignment ratio γub → 0, but this is way far from
the ideal condition (γub = 1), where the bias as-
sumes lower values.
A hint to solve this may be the compensation of
the value ∆bbt so that it is close to the one assumed
by ∆but, for example by applying this aiding tech-
nique in a synchronous network infrastructure.
- The user may receive more than a single pseu-
dorange measurement from the aiding peer, and
use them with an LMS approach to extend our
solution and solve the positioning problem.
This may be of very feasible since the aiding peer
may be located where there is a good GNSS cov-
erage and have a wider view of the skyplot.
- The antenna may help the user to improve the
solution of the linear system of equations (or to
select the best subset of pseudoranges) by trans-
mitting the measurement (or the measurements)
from the SV(s) it has in view close to the zenith.
This may be useful because they introduce less
error, given that the User-BTS distance in slant
range distance is smaller.
- Obtaining a measured approximation of δρ4,geom
may help to compensate the error.
This lead to have a zero-mean third component in
the bias vector, so that the user can appreciate a
higher accuracy in the position.
- Using more than one aiding peer may be an inter-
esting perspective since it would help very much
even if it is difficult to have different sets of SV
in view in a small region on the Earth.
Moreover, the aiding peers have to communicate
so that the user receives different sets of measures
from different sets of SVs.
As far as we can see, getting extra information from
an aiding peer may help to get coverage where the
service is not available, but involves issues about
time misalignment and geometry, so the user should
be satisfied as much as the error may be compen-
sated.