Ground moving target tracking with space-time adaptive radar

Ground moving target tracking by airborne radar provides situational awareness of vehicle movements in the supervised region. Vehicles are detected by applying space time adaptive processing to the received multi channel radar data. The detections are then fed to a tracking algorithm that processes them to tracks. In literature, radar signal processing and ground target tracking are treated as two separate topics and results are not validated by experimental data. The first objective of this thesis is to provide a closer link between these fields. The second objective is to show that tracking performance can be improved by providing additional data from the radar signal processing to the tracking step. The third objective is to validate the algorithm and the performance improvement using experimental data. As a result this thesis presents a unified treatment of ground moving target tracking from radar raw data to established tracks. A complete reference algorithm for ground moving target tracking based on the Gaussian mixture probability hypothesis density filter is presented. In particular, Jacobians of the observation process are derived. They are presented in such a form that immediate implementation in a programming language is possible. In the course of this thesis a measurement campaign with the experimental radar PAMIR of Fraunhofer FHR was conducted. The experiment included two GPS equipped reference vehicles and a multitude of targets of opportunity. Tracking results obtained with this experimental data and the reference tracking algorithm of this thesis are shown. The thesis also enhances the reference target tracking algorithm by a parameter that characterizes the variance of the direction of arrival measurement of the target signal. This parameter is determined adaptively depending on the estimated signal strength and the clutter background. The major contribution with regard to this enhancement is a thorough experimental validation: Firstly, a comparison between GPS based measurements and radar based measurements of the direction of arrival shows that this variance captures the distribution of measurement errors excellently. Secondly, tracking results are compared to the GPS tracks of the ground truth vehicles. It is found that the enhanced algorithm yields superior track quality with respect to both track accuracy and track continuity.Bodenzielverfolgung mit luftgestütztem Radar liefert das Lagebild von Fahrzeug­bewegungen innerhalb des beobachteten Gebiets. Fahrzeuge werden durch die Anwendung von Raum-Zeit adaptiver Signalverarbeitung (STAP) entdeckt. Die Entdeckungen werden dann von einem Zielverfolgungsalgorithmus zu Zielspuren verarbeitet. In der Literatur werden Radarsignalverarbeitung und Zielverfolgung als zwei getrennte Forschungsfelder behandelt und die Bodenzielverfolgung wird nicht anhand von Realdaten validiert. Das erste Ziel dieser Arbeit ist, eine engere Verbindung zwischen beiden Feldern herzustellen. Das zweite Ziel ist zu zeigen, dass die Qualität der Zielverfolgung durch das Verwenden zusätzlicher, durch die Radarsignalverarbeitung gewonnene Information verbessert werden kann. Das dritte Ziel ist, die Funktionalität der Zielverfolgung und die Verbesserung der Leistung durch experimentelle Realdaten zu belegen. Somit stellt diese Arbeit eine Gesamtbehandlung der Bodenzielverfolgung von den Radar-Rohdaten bis zu Zielspuren dar. Es wird ein vollständiger, auf dem Gaussian Mixture Probability Hypothesis Density Filter basierender Referenzalgorithmus für die Bodenzielverfolgung entwickelt. Insbesondere werden Jacobimatrizen der Beobachtungsfunktion hergeleitet. Sie werden in der Arbeit so dargestellt, dass sie direkt in einer Programmiersprache implementiert werden können. Im Zuge dieser Arbeit wurde ein Zielverfolgungs-Experiment mit dem Experimentalsystem PAMIR des Fraunhofer FHR durchgeführt. In dem Experiment wurden neben einer Vielzahl von Gelegenheitszielen zwei mit GPS-Geräten ausgerüstete Fahrzeuge von dem Radar beobachtet. Auf Basis dieses Experiments und des Referenzalgorithmus werden Zielverfolgungsergebnisse vorgestellt. Darüber hinaus erweitert diese Arbeit den Referenzalgorithmus um einen Parameter, der die Varianz der Richtungsschätzung des Zielsignals charakterisiert. Dieser Parameter wird adaptiv anhand der geschätzten Signalstärke und der Stärke störender Bodenrückstreuungen festgelegt. Der wesentliche Beitrag dieser Arbeit in Bezug auf diese Erweiterung ist eine gründliche experimentelle Validierung. Erstens zeigt der Vergleich von GPS- und Radar-basierten Richtungsschätzungen, dass dieser Parameter die Verteilung des Messfehlers exzellent beschreibt. Zweitens werden Zielverfolgungsergebnisse mit den GPS-Spuren verglichen. Es zeigt sich, dass der erweiterte Algorithmus sowohl in Bezug auf die Spurgenauigkeit als auch in Bezug auf die Spurkontinuität die Zielverfolgung verbessert

Implementation of tracking algorithms for multistatic systems

Due to the increased prevalence of ubiquitous communication technologies and the reduced cost of electronic components, there is an increasing interest in developing networked radar systems. Such networked radar systems offer potential benefits in robustness as well as improvements in performance for detection, tracking and classification. As a branch of applied computer sciences sensor data fusion addresses the ability to process this vast quantity of information, generated by multiple sources, in an effective way. The purpose of this thesis is to validate the tracking algorithms implemented, to determine whether they are capable of identifying and tracking two closely spaced targets, to determine the capability of the system to track a target that moves with fast maneuvers as well as the ability to handle a potential simultaneous attack from both the air and the sea. We present a method for multiple target tracking using multiple sensors both for passive and active sensors. Firstly, regarding active radar, we describe an algorithm for combining range-Doppler data from multiple sensors to perform multi-target tracking. In particular we considered the problem of very poor azimuth resolution. In this case more than two sensors are needed to triangulate target tracks and techniques like multilateration are needed to overcome the problem. Then two tracking algorithms for bistatic DVB-T passive radar based on the Extended Kalman Filter (for single target tracking) and on the Kalman filter (for multiple target tracking), exploiting measurement of bistatic range and bistatic velocity of a target are described. Also the direction of arrival of the target is estimated through beamforming and then used in the tracking model. The algorithms have been tested and validated by using real data

Beware the Boojum: Caveats and Strengths of Avian Radar

Radar provides a useful and powerful tool to wildlife biologists and ornithologists. However, radar also has the potential for errors on a scale not previously possible. In this paper, we focus on the strengths and limitations of avian surveillance radars that use marine radar front-ends integrated with digital radar processors to provide 360° of coverage. Modern digital radar processors automatically extract target information, including such various target attributes as location, speed, heading, intensity, and radar cross-section (size) as functions of time. Such data can be stored indefinitely, providing a rich resource for ornithologists and wildlife managers. Interpreting these attributes in view of the sensor’s characteristics from which they are generated is the key to correctly deriving and exploiting application-specific information about birds and bats. We also discuss (1) weather radars and air-traffic control surveillance radars that could be used to monitor birds on larger, coarser spatial scales; (2) other nonsurveillance radar configurations, such as vertically scanning radars used for vertical profiling of birds along a particular corridor; and (3) Doppler, single-target tracking radars used for extracting radial velocity and wing-beat frequency information from individual birds for species identification purposes

Laser Scanner Technology

Laser scanning technology plays an important role in the science and engineering arena. The aim of the scanning is usually to create a digital version of the object surface. Multiple scanning is sometimes performed via multiple cameras to obtain all slides of the scene under study. Usually, optical tests are used to elucidate the power of laser scanning technology in the modern industry and in the research laboratories. This book describes the recent contributions reported by laser scanning technology in different areas around the world. The main topics of laser scanning described in this volume include full body scanning, traffic management, 3D survey process, bridge monitoring, tracking of scanning, human sensing, three-dimensional modelling, glacier monitoring and digitizing heritage monuments

Aeronautical engineering: A cumulative index to a continuing bibliography (supplement 274)

This publication is a cumulative index to the abstracts contained in supplements 262 through 273 of Aeronautical Engineering: A Continuing Bibliography. The bibliographic series is compiled through the cooperative efforts of the American Institute of Aeronautics and Astronautics (AIAA) and the National Aeronautics and Space Administration (NASA). Seven indexes are included: subject, personal author, corporate source, foreign technology, contract number, report number, and accession number

Real-time spatial modeling to detect and track resources on construction sites

For more than 10 years the U.S. construction industry has experienced over 1,000 fatalities annually. Many fatalities may have been prevented had the individuals and equipment involved been more aware of and alert to the physical state of the environment around them. Awareness may be improved by automatic 3D (three-dimensional) sensing and modeling of the job site environment in real-time. Existing 3D modeling approaches based on range scanning techniques are capable of modeling static objects only, and thus cannot model in real-time dynamic objects in an environment comprised of moving humans, equipment, and materials. Emerging prototype 3D video range cameras offer another alternative by facilitating affordable, wide field of view, automated static and dynamic object detection and tracking at frame rates better than 1Hz (real-time). This dissertation presents an imperical work and methodology to rapidly create a spatial model of construction sites and in particular to detect, model, and track the position, dimension, direction, and velocity of static and moving project resources in real-time, based on range data obtained from a three-dimensional video range camera in a static or moving position. Existing construction site 3D modeling approaches based on optical range sensing technologies (laser scanners, rangefinders, etc.) and 3D modeling approaches (dense, sparse, etc.) that offered potential solutions for this research are reviewed. The choice of an emerging sensing tool and preliminary experiments with this prototype sensing technology are discussed. These findings led to the development of a range data processing algorithm based on three-dimensional occupancy grids which is demonstrated in detail. Testing and validation of the proposed algorithms have been conducted to quantify the performance of sensor and algorithm through extensive experimentation involving static and moving objects. Experiments in indoor laboratory and outdoor construction environments have been conducted with construction resources such as humans, equipment, materials, or structures to verify the accuracy of the occupancy grid modeling approach. Results show that modeling objects and measuring their position, dimension, direction, and speed had an accuracy level compatible to the requirements of active safety features for construction. Results demonstrate that video rate 3D data acquisition and analysis of construction environments can support effective detection, tracking, and convex hull modeling of objects. Exploiting rapidly generated three-dimensional models for improved visualization, communications, and process control has inherent value, broad application, and potential impact, e.g. as-built vs. as-planned comparison, condition assessment, maintenance, operations, and construction activities control. In combination with effective management practices, this sensing approach has the potential to assist equipment operators to avoid incidents that result in reduce human injury, death, or collateral damage on construction sites.Civil, Architectural, and Environmental Engineerin

Frequency Modulated Continuous Waveform Radar for Collision Prevention in Large Vehicles

The drivers of large vehicles can have very limited visibility, which contributes to poor situation awareness and an increased risk of collision with other agents. This thesis is focused on the development of reliable sensing for this close proximity problem in large vehicles operating in harsh environmental conditions. It emphasises the use of in-depth knowledge of a sensor’s physics and performance characteristics to develop effective mathematical models for use in different mapping algorithms. An analysis of the close proximity problem and the demands it poses on sensing technologies is presented. This guides the design and modelling process for a frequency modulated continuous waveform (FMCW) radar sensor for use in solving the close proximity problem. Radar offers better all-weather performance than other sensing modalities, but its measurement structure is more complex and often degraded by noise and clutter. The commonly used constant false alarm rate (CFAR) threshold approach performs poorly in applications with frequent extended targets and a short measurement vector, as is the case here. Therefore, a static detection threshold is calculated using measurements of clutter made using the radar, allowing clutter measurements to be filtered out in known environments. The detection threshold is used to develop a heuristic sensor model for occupancy grid mapping. This results in a more reliable representation of the environment than is achieved using the detection threshold alone. A Gaussian mixture extended Kalman probability hypothesis density filter (GM-EK-PHD) is implemented to allow mapping in dynamic environments using the FMCW radar. These methods are used to produce maps of the environment that can be displayed to the driver of a large vehicle to better avoid collisions. The concepts developed in this thesis are validated using simulated and real data from a low-cost 24GHz FMCW radar developed at the Australian Centre for Field Robotics at the University of Sydney

Earth resources shuttle imaging radar

A report is presented on a preliminary design of a Synthetic Array Radar (SAR) intended for experimental use with the space shuttle program. The radar is called Earth Resources Shuttle Imaging Radar (ERSIR). Its primary purpose is to determine the usefulness of SAR in monitoring and managing earth resources. The design of the ERSIR, along with tradeoffs made during its evolution is discussed. The ERSIR consists of a flight sensor for collecting the raw radar data and a ground sensor used both for reducing these radar data to images and for extracting earth resources information from the data. The flight sensor consists of two high powered coherent, pulse radars, one that operates at L and the other at X-band. Radar data, recorded on tape can be either transmitted via a digital data link to a ground terminal or the tape can be delivered to the ground station after the shuttle lands. A description of data processing equipment and display devices is given

Unmanned Aircraft Systems in the Cyber Domain

Unmanned Aircraft Systems are an integral part of the US national critical infrastructure. The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. This textbook will fully immerse and engage the reader / student in the cyber-security considerations of this rapidly emerging technology that we know as unmanned aircraft systems (UAS). The first edition topics covered National Airspace (NAS) policy issues, information security (INFOSEC), UAS vulnerabilities in key systems (Sense and Avoid / SCADA), navigation and collision avoidance systems, stealth design, intelligence, surveillance and reconnaissance (ISR) platforms; weapons systems security; electronic warfare considerations; data-links, jamming, operational vulnerabilities and still-emerging political scenarios that affect US military / commercial decisions. This second edition discusses state-of-the-art technology issues facing US UAS designers. It focuses on counter unmanned aircraft systems (C-UAS) – especially research designed to mitigate and terminate threats by SWARMS. Topics include high-altitude platforms (HAPS) for wireless communications; C-UAS and large scale threats; acoustic countermeasures against SWARMS and building an Identify Friend or Foe (IFF) acoustic library; updates to the legal / regulatory landscape; UAS proliferation along the Chinese New Silk Road Sea / Land routes; and ethics in this new age of autonomous systems and artificial intelligence (AI).https://newprairiepress.org/ebooks/1027/thumbnail.jp

Integrated perception, modeling, and control paradigm for bistatic sonar tracking by autonomous underwater vehicles

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 357-364).In this thesis, a fully autonomous and persistent bistatic anti-submarine warfare (ASW) surveillance solution is developed using the autonomous underwater vehicles (AUVs). The passive receivers are carried by these AUVs, and are physically separated from the cooperative active sources. These sources are assumed to be transmitting both the frequency-modulated (FM) and continuous wave (CW) sonar pulse signals. The thesis then focuses on providing novel methods for the AUVs/receivers to enhance the bistatic sonar tracking performance. Firstly, the surveillance procedure, called the Automated Perception, is developed to automatically abstract the sensed acoustical data from the passive receiver to the track report that represents the situation awareness. The procedure is executed sequentially by two algorithms: (i) the Sonar Signal Processing algorithm - built with a new dual-waveform fusion of the FM and CW signals to achieve reliable stream of contacts for improved tracking; and (ii) the Target Tracking algorithm - implemented by exploiting information and environmental adaptations to optimize tracking performance. Next, a vehicular control strategy, called the Perception-Driven Control, is devised to move the AUV in reaction to the track report provided by the Automated Perception. The thesis develops a new non-myopic and adaptive control for the vehicle. This is achieved by exploiting the predictive information and environmental rewards to optimize the future tracking performance. The formulation eventually leads to a new information-theoretic and environmental-based control. The main challenge of the surveillance solution then rests upon formulating a model that allows tracking performance to be enhanced via adaptive processing in the Automated Perception, and adaptive mobility by the Perception-Driven Control. A Unified Model is formulated in this thesis that amalgamates two models: (i) the Information-Theoretic Model - developed to define the manner at which the FM and CW acoustical, the navigational, and the environmental measurement uncertainties are propagated to the bistatic measurement uncertainties in the contacts; and (ii) the Environmental-Acoustic Model - built to predict the signal-to-noise power ratios (SNRs) of the FM and CW contacts. Explicit relationships are derived in this thesis using information theory to amalgamate these two models. Finally, an Integrated System is developed onboard each AUV that brings together all the above technologies to enhance the bistatic sonar tracking performance. The system is formulated as a closed-loop control system. This formulation provides a new Integrated Perception, Modeling, and Control Paradigm for an autonomous bistatic ASW surveillance solution using AUVs. The system is validated using the simulated data, and the real data collected from the Generic Littoral Interoperable Network Technology (GLINT) 2009 and 2010 experiments. The experiments were conducted jointly with the NATO Undersea Research Centre (NURC).by Raymond Hon Kit Lum.Sc.D