Localization Capability of Cooperative Anti-Intruder Radar Systems

System aspects of an anti-intruder multistatic radar based on impulse radio ultrawideband (UWB) technology are addressed. The investigated system is composed of one transmitting node and at least three receiving nodes, positioned in the surveillance area with the aim of detecting and locating a human intruder (target) that moves inside the area. Such systems, referred to also as UWB radar sensor networks, must satisfy severe power constraints worldwide imposed by, for example, the Federal Communications Commission (FCC) and by the European Commission (EC) power spectral density masks. A single transmitter-receiver pair (bistatic radar) is considered at first. Given the available transmitted power and the capability of the receiving node to resolve the UWB pulses in the time domain, the surveillance area regions where the target is detectable, and those where it is not, are obtained. Moreover, the range estimation error for the transmitter-receiver pair is discussed. By employing this analysis, a multistatic system is then considered, composed of one transmitter and three or four cooperating receivers. For this multistatic system, the impact of the nodes location on area coverage, necessary transmitted power and localization uncertainty is studied, assuming a circular surveillance area. It is highlighted how area coverage and transmitted power, on one side, and localization uncertainty, on the other side, require opposite criteria of nodes placement. Consequently, the need for a system compromising between these factors is shown. Finally, a simple and effective criterion for placing the transmitter and the receivers is drawn

Improved Target Localization in Multi-Waveform Multi-Band Hybrid Multistatic Radar Networks

This study proposes an algorithm to improve the target localization performance. This is implemented in a multi-waveform multi-band hybrid (passive and active) multistatic radar network scenario, that utilize broadcasting signals for radar sensing, in addition to the radar waveforms. Multi-waveform multi-band radar receivers can exploit the broadcast signals transmitted by non-cooperative transmitters, such as communication or broadcasting systems, for target sensing in addition to radar waveform. Hence, multiple measurements of the targets can be acquired and fused to improve the target detection and parameter estimation. Because of utilizing various waveforms, each transmitter-receiver (Tx-Rx) pair has a different range and velocity estimation accuracy, that is also affected by the bistatic geometry of the bistatic pairs. Taking this into account, this study proposes a target localization algorithm based on bistatic Cramér-Rao Lower Bounds (CRLBs) for multistatic multi-band radar networks. It is shown that modeling the entire network and evaluating the bistatic range CRLB of each bistatic pair in advance, and utilizing this information while estimating the target location significantly improves the localization accuracy. Moreover, the proposed algorithm also includes a target height estimation correction stage to achieve a better 3D localization accuracy

A comparison of processing approaches for distributed radar sensing

Radar networks received increasing attention in recent years as they can outperform single monostatic or bistatic systems. Further attention is being dedicated to these systems as an application of the MIMO concept, well know in communications for increasing the capacity of the channel and improving the overall quality of the connection. However, it is here shown that radar network can take advantage not only from the angular diversity in observing the target, but also from a variety of ways of processing the received signals. The number of devices comprising the network has also been taken into the analysis. Detection and false alarm are evaluated in noise only and clutter from a theoretical and simulated point of view. Particular attention is dedicated to the statistics behind the processing. Experiments have been performed to evaluate practical applications of the proposed processing approaches and to validate assumptions made in the theoretical analysis. In particular, the radar network used for gathering real data is made up of two transmitters and three receivers. More than two transmitters are well known to generate mutual interference and therefore require additional e�fforts to mitigate the system self-interference. However, this allowed studying aspects of multistatic clutter, such as correlation, which represent a first and novel insight in this topic. Moreover, two approaches for localizing targets have been developed. Whilst the first is a graphic approach, the second is hybrid numerical (partially decentralized, partially centralized) which is clearly shown to improve dramatically the single radar accuracy. Finally the e�ects of exchanging angular with frequency diversity are shown as well in some particular cases. This led to develop the Frequency MIMO and the Frequency Diverse Array, according to the separation of two consecutive frequencies. The latter is a brand new topic in technical literature, which is attracting the interest of the technical community because of its potential to generate range-dependant patterns. Both the latter systems can be used in radar-designing to improve the agility and the effciency of the radar

Multistatic radar optimization for radar sensor network applications

The design of radar sensor networks (RSN) has undergone great advancements in recent years. In fact, this kind of system is characterized by a high degree of design flexibility due to the multiplicity of radar nodes and data fusion approaches. This thesis focuses on the development and analysis of RSN architectures to optimize target detection and positioning performances. A special focus is placed upon distributed (statistical) multiple-input multipleoutput (MIMO) RSN systems, where spatial diversity could be leveraged to enhance radar target detection capabilities. In the first part of this thesis, the spatial diversity is leveraged in conjunction with cognitive waveform selection and design techniques to quickly adapt to target scene variations in real time. In the second part, we investigate the impact of RSN geometry, particularly the placement of multistatic radar receivers, on target positioning accuracy. We develop a framework based on cognitive waveform selection in conjunction with adaptive receiver placement strategy to cope with time-varying target scattering characteristics and clutter distribution parameters in the dynamic radar scene. The proposed approach yields better target detection performance and positioning accuracy as compared with conventional methods based on static transmission or stationary multistatic radar topology. The third part of this thesis examines joint radar and communication systems coexistence and operation via two possible architectures. In the first one, several communication nodes in a network operate separately in frequency. Each node leverages the multi-look diversity of the distributed system by activating radar processing on multiple received bistatic streams at each node level in addition to the pre-existing monostatic processing. This architecture is based on the fact that the communication signal, such as the Orthogonal Frequency Division Multiplexing (OFDM) waveform, could be well-suited for radar tasks if the proper waveform parameters are chosen so as to simultaneously perform communication and radar tasks. The advantage of using a joint waveform for both applications is a permanent availability of radar and communication functions via a better use of the occupied spectrum inside the same joint hardware platform. We then examine the second main architecture, which is more complex and deals with separate radar and communication entities with a partial or total spectrum sharing constraint. We investigate the optimum placement of radar receivers for better target positioning accuracy while reducing the radar measurement errors by minimizing the interference caused by simultaneous operation of the communication system. Better performance in terms of communication interference handling and suppression at the radar level, were obtained with the proposed placement approach of radar receivers compared to the geometric dilution of precision (GDOP)-only minimization metric

Improvement of detection and tracking techniques in multistatic passive radar systems. (Mejora de técnicas de detección y seguimiento en sistemas radar pasivos multiestáticos)

Esta tesis doctoral es el resultado de una intensa actividad investigadora centrada en los sensores radar pasivos para la mejora de las capacidades de detección y seguimiento en escenarios complejos con blancos terrestres y pequeños drones. El trabajo de investigación se ha llevado a cabo en el grupo de investigación coordinado por la Dra. María Pilar Jarabo Amores, dentro del marco diferentes proyectos: IDEPAR (“Improved DEtection techniques for PAssive Radars”), MASTERSAT (“MultichAnnel paSsive radar receiver exploiting TERrestrial and SATellite Illuminators”) y KRIPTON (“A Knowledge based appRoach to passIve radar detection using wideband sPace adapTive prOcessiNg”) financiados por el Ministerio de Economía y Competitividad de España; MAPIS (Multichannel passive ISAR imaging for military applications) y JAMPAR (“JAMmer-based PAssive Radar”), financiados por la Agencia Europea de Defensa (EDA) . El objetivo principal es la mejora de las técnicas de detección y seguimiento en radares pasivos con configuraciones biestáticas y multiestaticas. En el documento se desarrollan algoritmos para el aprovechamiento de señales procedentes de distintos iluminadores de oportunidad (transmisores DVB-T, satélites DVB-S y señales GPS). Las soluciones propuestas han sido integradas en el demostrador tecnológico IDEPAR, desarrollado y actualizado bajo los proyectos mencionados, y validadas en escenarios reales declarados de interés por potenciales usuarios finales (Direccion general de armamento y material, instituto nacional de tecnología aeroespacial y la armada española). Para el desarrollo y evaluación de cadenas de las cadenas de procesado, se plantean dos casos de estudio: blancos terrestres en escenarios semiurbanos edificios y pequeños blancos aéreos en escenarios rurales y costeros. Las principales contribuciones se pueden resumir en los siguientes puntos: • Diseño de técnicas de seguimiento 2D en el espacio de trabajo rango biestático-frecuencia Doppler: se desarrollan técnicas de seguimiento para los dos casos de estudio, localización de blancos terrestres y pequeños drones. Para es último se implementan técnicas capaces de seguir tanto el movimiento del dron como su firma Doppler, lo que permite implementar técnicas de clasificación de blancos. • Diseño de técnicas de seguimiento de blancos capaces de integrar información en el espacio 3D (rango, Doppler y acimut): se diseñan técnicas basadas en procesado en dos etapas, una primera con seguimiento en 2D para el filtrado de falsas alarmas y la segunda para el seguimiento en 3D y la conversión de coordenadas a un plano local cartesiano. Se comparan soluciones basadas en filtros de Kalman para sistemas tanto lineales como no lineales. • Diseño de cadenas de procesado para sistemas multiestáticos: la información estimada del blanco sobre múltiples geometrías biestáticas es utilizada para incremento de las capacidades de localización del blanco en el plano cartesiano local. Se presentan soluciones basadas en filtros de Kalman para sistemas no lineales explotando diferentes medidas biestáticas en el proceso de transformación de coordenadas, analizando las mejoras de precisión en la localización del blanco. • Diseño de etapas de procesado para radares pasivos basados en señales satelitales de las constelaciones GPS DVB-S. Se estudian las características de las señales satelitales identificando sus inconvenientes y proponiendo cadenas de procesado que permitan su utilización para la detección y seguimiento de blancos terrestres. • Estudio del uso de señales DVB-T multicanal con gaps de transmisión entre los diferentes canales en sistemas radares pasivos. Con ello se incrementa la resolución del sistema, y las capacidades de detección, seguimiento y localización. Se estudia el modelo de señal multicanal, sus efectos sobre el procesado coherente y se proponen cadenas de procesado para paliar los efectos adversos de este tipo de señales

Doppler-only target tracking for a multistatic radar exploiting FM band illuminators of opportunity

Includes bibliographical referencesCommensal Radar (CR), defined as a subclass of Passive Radar (PR), is a receive only radar that exploits non-cooperative illuminators of opportunity for target detection, location and subsequent tracking. The objective of this thesis is to evaluate the feasibility of using a Frequency Modulation (FM) Broadcast band CR system as a cost effective solution for Air Traffic Control (ATC). An inherent complication by exploiting FM is the low range resolution due to the low bandwidth of FM radio signals. However, due to typical long integration times associated with CR, the frequency domain resolution is typically very good. As a result, measurements of the target's Doppler shift are highly accurate and could potentially make FM illuminators a viable source for ATC purposes. Accordingly, this thesis aims to obtain a comprehensive understanding of using high resolution Doppler measurements to accurately track the position of a target. This objective have been addressed b by performing a comprehensive mathematical analysis for a Doppler only tracking CR system. The analysis is verified with a tracking simulation, in which the Recursive Gauss Newton Filter (RGNF) is used and lastly, a field experiment was conducted to produce tracking results based on real measurement data. Results demonstrated that Doppler only target tracking from real measurement data is possible, even when the initial target state vector is initialised from real measurement data. A good degree of correlation is achieved between the theoretical, simulated and measured results, hence verifying the theoretical findings of this thesis. Ensuring that the observation matrix is properly conditioned in Doppler only tracking applications is important, as failure to do so results in tracking instability. Factors that influence the conditioning of the observation matrix are; the number of receivers used (assuming the basic observation criteria is met) and the placement of the receivers, keeping in mind the possibility of Doppler correlation in the measurements. The possibility of improving an ill-conditioned observation matrix is also demonstrated. In general, tracking filters, for example the RGNF, typically employ time history information and therefore, a direct comparison to the Cramer Rao Lower Bound (CRLB) is unrealistic and accordingly a new theoretical lower bound, called the Cumulative CRLB was derived that does account for time history measurements. Although the best results for this thesis are achieved by using long integration periods (4 s), the effect of Doppler walk was not compensated for and is an aspect that requires further investigation to potentially further improve on the results obtained in this thesis. As a final conclusion for this thesis; the Doppler only target tracking delivered some encouraging results, however a qualification test in the form of an extensive trial period is next required to motivate Doppler only tracking for ATC purposes

Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging Systems

Increasing attention is being paid to millimeter-wave (mmWave), 30 GHz to 300 GHz, and terahertz (THz), 300 GHz to 10 THz, sensing applications including security sensing, industrial packaging, medical imaging, and non-destructive testing. Traditional methods for perception and imaging are challenged by novel data-driven algorithms that offer improved resolution, localization, and detection rates. Over the past decade, deep learning technology has garnered substantial popularity, particularly in perception and computer vision applications. Whereas conventional signal processing techniques are more easily generalized to various applications, hybrid approaches where signal processing and learning-based algorithms are interleaved pose a promising compromise between performance and generalizability. Furthermore, such hybrid algorithms improve model training by leveraging the known characteristics of radio frequency (RF) waveforms, thus yielding more efficiently trained deep learning algorithms and offering higher performance than conventional methods. This dissertation introduces novel hybrid-learning algorithms for improved mmWave imaging systems applicable to a host of problems in perception and sensing. Various problem spaces are explored, including static and dynamic gesture classification; precise hand localization for human computer interaction; high-resolution near-field mmWave imaging using forward synthetic aperture radar (SAR); SAR under irregular scanning geometries; mmWave image super-resolution using deep neural network (DNN) and Vision Transformer (ViT) architectures; and data-level multiband radar fusion using a novel hybrid-learning architecture. Furthermore, we introduce several novel approaches for deep learning model training and dataset synthesis.Comment: PhD Dissertation Submitted to UTD ECE Departmen

The economic and risk constraints in the feasibility analysis of wireless communications in Marine Corps Combat Operation Centers

This thesis will provide Marine Corps acquisitions and communications personnel a general understanding of wireless communications capabilities, financial feasibility, benefits and the risks of implementing a wireless solution into the current existing communications infrastructure in particular, the Combat Operations Center (COC) CapSet models already employed and deployed throughout the Marine Corps Air Ground Task Force. The content of this thesis is of an unclassified nature. This thesis is intended to serve as a reference for acquisitions or communications personnel dealing with the acquisition, procurement, planning, and implementation of wireless technologies in the Marine Corps, so that they will be able to intelligently articulate the financial feasibility, benefits, and risks of adopting or implementing a wireless solution to the Marine Corps Enterprise Network and COC infrastructure, and make informed decisions on the subject.http://archive.org/details/theeconomicndris1094537735Captain, United States Marine CorpsApproved for public release; distribution is unlimited

People counting using multistatic passive WiFi radar with a multi-input deep convolutional neural network

Accurately counting numbers people is useful in many applications. Currently, camera-based systems assisted by computer vision and machine learning algorithms represent the state-of-the-art. However, they have limited coverage areas and are prone to blind spots, obscuration by walls, shadowing of individuals in crowds, and rely on optimal positioning and lighting conditions. Moreover, their ability to image people raises ethical and privacy concerns. In this paper we propose a distributed multistatic passive WiFi radar (PWR) consisting of 1 reference and 3 surveillance receivers, that can accurately count up to six test subjects using Doppler frequency shifts and intensity data from measured micro-Doppler (µ-Doppler) spectrograms. To build the person-counting processing model, we employ a multi-input convolutional neural network (MI-CNN). The results demonstrate a 96% counting accuracy for six subjects when data from all three surveillance channels are utilised

Spatial Identification Methods and Systems for RFID Tags

Disertační práce je zaměřena na metody a systémy pro měření vzdálenosti a lokalizaci RFID tagů pracujících v pásmu UHF. Úvod je věnován popisu současného stavu vědeckého poznání v oblasti RFID prostorové identifikace a stručnému shrnutí problematiky modelování a návrhu prototypů těchto systémů. Po specifikaci cílů disertace pokračuje práce popisem teorie modelování degenerovaného kanálu pro RFID komunikaci. Detailně jsou rozebrány metody měření vzdálenosti a odhadu směru příchodu signálu založené na zpracování fázové informace. Pro účely lokalizace je navrženo několik scénářů rozmístění antén. Modely degenerovaného kanálu jsou simulovány v systému MATLAB. Významná část této práce je věnována konceptu softwarově definovaného rádia (SDR) a specifikům jeho adaptace na UHF RFID, která využití běžných SDR systémů značně omezují. Diskutována je zejména problematika průniku nosné vysílače do přijímací cesty a požadavky na signál lokálního oscilátoru používaný pro směšování. Prezentovány jsou tři vyvinuté prototypy: experimentální dotazovač EXIN-1, měřicí systém založený na platformě Ettus USRP a anténní přepínací matice pro emulaci SIMO systému. Závěrečná část je zaměřena na testování a zhodnocení popisovaných lokalizačních technik, založených na měření komplexní přenosové funkce RFID kanálu. Popisuje úzkopásmové/širokopásmové měření vzdálenosti a metody odhadu směru signálu. Oba navržené scénáře rozmístění antén jsou v závěru ověřeny lokalizačním měřením v reálných podmínkách.The doctoral thesis is focused on methods and systems for ranging and localization of RFID tags operating in the UHF band. It begins with a description of the state of the art in the field of RFID positioning with short extension to the area of modeling and prototyping of such systems. After a brief specification of dissertation objectives, the thesis overviews the theory of degenerate channel modeling for RFID communication. Details are given about phase-based ranging and direction of arrival finding methods. Several antenna placement scenarios are proposed for localization purposes. The degenerate channel models are simulated in MATLAB. A significant part of the thesis is devoted to software defined radio (SDR) concept and its adaptation for UHF RFID operation, as it has its specialties which make the usage of standard SDR test equipment very disputable. Transmit carrier leakage into receiver path and requirements on local oscillator signals for mixing are discussed. The development of three experimental prototypes is also presented there: experimental interrogator EXIN-1, measurement system based on Ettus USRP platform, and antenna switching matrix for an emulation of SIMO system. The final part is focused on testing and evaluation of described positioning techniques based on complex backscatter channel transfer function measurement. Both narrowband/wideband ranging and direction of arrival methods are validated. Finally, both proposed antenna placement scenarios are evaluated with real-world measurements.