Space-time adaptive processing techniques for multichannel mobile passive radar

Passive radar technology has reached a level of maturity for stationary sensor operations, widely proving the ability to detect, localize and track targets, by exploiting different kinds of illuminators of opportunity. In recent years, a renewed interest from both the scientific community and the industry has opened new perspectives and research areas. One of the most interesting and challenging ones is the use of passive radar sensors onboard moving platforms. This may offer a number of strategic advantages and extend the functionalities of passive radar to applications like synthetic aperture radar (SAR) imaging and ground moving target indication (GMTI). However, these benefits are paid in terms of motion-induced Doppler distortions of the received signals, which can adversely affect the system performance. In the case of surveillance applications, the detection of slowly moving targets is hindered by the Doppler-spread clutter returns, due to platform motion, and requires the use of space-time processing techniques, applied on signals collected by multiple receiving channels. Although in recent technical literature the feasibility of this concept has been preliminarily demonstrated, mobile passive radar is still far from being a mature technology and several issues still need to be addressed, mostly connected to the peculiar characteristics of the passive bistatic scenario. Specifically, significant limitations may come from the continuous and time-varying nature of the typical waveforms of opportunity, not suitable for conventional space-time processing techniques. Moreover, the low directivity of the practical receiving antennas, paired with a bistatic omni-directional illumination, further increases the clutter Doppler bandwidth and results in the simultaneous reception of non-negligible clutter contributions from a very wide angular sector. Such contributions are likely to undergo an angle-dependent imbalance across the receiving channels, exacerbated by the use of low-cost hardware. This thesis takes research on mobile passive radar for surveillance applications one step further, finding solutions to tackle the main limitations deriving from the passive bistatic framework, while preserving the paradigm of a simple system architecture. Attention is devoted to the development of signal processing algorithms and operational strategies for multichannel mobile passive radar, focusing on space-time processing techniques aimed at clutter cancellation and slowly moving target detection and localization. First, a processing scheme based on the displaced phase centre antenna (DPCA) approach is considered, for dual-channel systems. The scheme offers a simple and effective solution for passive radar GMTI, but its cancellation performance can be severely compromised by the presence of angle-dependent imbalances affecting the receiving channels. Therefore, it is paired with adaptive clutter-based calibration techniques, specifically devised for mobile passive radar. By exploiting the fine Doppler resolution offered by the typical long integration times and the one-to-one relationship between angle of arrival and Doppler frequency of the stationary scatterers, the devised techniques compensate for the angle-dependent imbalances and prove largely necessary to guarantee an effective clutter cancellation. Then, the attention is focused on space-time adaptive processing (STAP) techniques for multichannel mobile passive radar. In this case, the clutter cancellation capability relies on the adaptivity of the space-time filter, by resorting to an adjacent-bin post-Doppler (ABPD) approach. This allows to significantly reduce the size of the adaptive problem and intrinsically compensate for potential angle-dependent channel errors, by operating on a clutter subspace accounting for a limited angular sector. Therefore, ad hoc strategies are devised to counteract the effects of channel imbalance on the moving target detection and localization performance. By exploiting the clutter echoes to correct the spatial steering vector mismatch, the proposed STAP scheme is shown to enable an accurate estimation of target direction of arrival (DOA), which represents a critical task in system featuring few wide beam antennas. Finally, a dual cancelled channel STAP scheme is proposed, aimed at further reducing the system computational complexity and the number of required training data, compared to a conventional full-array solution. The proposed scheme simplifies the DOA estimation process and proves to be robust against the adaptivity losses commonly arising in a real bistatic clutter scenario, allowing effective operation even in the case of a limited sample support. The effectiveness of the techniques proposed in this work is validated by means of extensive simulated analyses and applications to real data, collected by an experimental multichannel passive radar installed on a moving platform and based on DVB-T transmission

Implementation of a DVB-T2 passive coherent locator demonstrator

Passive Coherent Locator (PCL) radar’s have seen extensive research in the past decade. PCL radars utilize illuminators of opportunity (IOO) as transmitters to perform target detection. Particular interests in FM (analogue) and DVB-T/T2, DAB (digital) radio frequency signals has seen significant focus as possible illuminators for radar processing. The University of Cape Town (UCT) , in particular, has extensive history on passive radar research including the implementation of a full narrowband FM PCL radar demonstrator. This dissertation details the design and implementation of a DVB-T2 Passive Coherent Locator radar demonstrator isolating a single DVB-T2 channel. This includes the design, construction, testing and evaluation of the full PCL radar system. System planning was implemented detailing the possible IOOs available in the Cape Town area. This was followed by signal propagation simulations to determine the effects the environment would have on the transmitted wave utilising Advanced Refractive Effects Prediction System (AREPS) model. A front-end design was simulated and implemented utilizing commercial-of-the-shelf (COTS) hardware including the National Instruments Ettus N210 software defined Radio (SDR) based on the system planning results. A processing chain for DVB-T2 based PCL radar was then investigated to determine the most optimal processing chain structure, with the mismatched filtering technique being proposed as an ideal choice for DVB-T2 PCL radar. The proposed processing chain was implemented and tested on both the Ettus N210 front-end as well as a commercial system. The full radar demonstrator was then tested by observing the air traffic surrounding the Cape Town International airport resulting in successful detections of aircraft in the surveyed environment

WAVEFORM AND TRANSCEIVER OPTIMIZATION FOR MULTI-FUNCTIONAL AIRBORNE RADAR THROUGH ADAPTIVE PROCESSING

Pulse compression techniques have been widely used for target detection and remote sensing. The primary concern for pulse compression is the sidelobe interference. Waveform design is an important method to improve the sidelobe performance. As a multi-functional aircraft platform in aviation safety domain, ADS-B system performs functions involving detection, localization and alerting of external traffic. In this work, a binary phase modulation is introduced to convert the original 1090 MHz ADS-B signal waveform into a radar signal. Both the statistical and deterministic models of new waveform are developed and analyzed. The waveform characterization, optimization and its application are studied in details. An alternative way to achieve low sidelobe levels without trading o range resolution and SNR is the adaptive pulse compression - RMMSE (Reiterative Minimum Mean-Square error). Theoretically, RMMSE is able to suppress the sidelobe level down to the receiver noise floor. However, the application of RMMSE to actual radars and the related implementation issues have not been investigated before. In this work, implementation aspects of RMMSE such as waveform sensitivity, noise immunity and computational complexity are addressed. Results generated by applying RMMSE to both simulated and measured radar data are presented and analyzed. Furthermore, a two-dimensional RMMSE algorithm is derived to mitigate the sidelobe effects from both pulse compression processing and antenna radiation pattern. In addition, to achieve even better control of the sidelobe level, a joint transmit and receive optimization scheme (JTRO) is proposed, which reduces the impacts of HPA nonlinearity and receiver distortion. Experiment results obtained with a Ku-band spaceborne radar transceiver testbed are presented

Waveform Diversity and Range-Coupled Adaptive Radar Signal Processing

Waveform diversity may offer several benefits to radar systems though often at the cost of reduced sensitivity. Multi-dimensional processing schemes are known to offer many degrees of freedom, which can be exploited to suppress the ambiguity inherent to pulse compression, array processing, and Doppler frequency estimation. Spatial waveform diversity can be achieved by transmitting different but correlated waveforms from each element of an antenna array. A simple yet effective scheme is employed to transmit different waveforms in different spatial directions. A new reiterative minimum mean squared error approach entitled Space-Range Adaptive Processing, which adapts simultaneously in range and angle, is derived and shown in simulation to offer enhanced performance when spatial waveform diversity is employed relative to both conventional matched filtering and sequentially adapting in angle and then range. The same mathematical framework is utilized to develop Time-Range Adaptive Processing (TRAP) algorithm which is capable of simultaneously adapting in Doppler frequency and range. TRAP is useful when pulse-to-pulse changing of the center frequency or waveform coding is used to achieve enhanced range resolution or unambiguous ranging, respectively. The inherent computational complexity of the new multi-dimensional algorithms is addressed by segmenting the full-dimension cost functions, yielding a reduced-dimensional variants of each. Finally, a non-adaptive approach based on the multi-dimensional TRAP signal model is utilized to develop an efficient clutter cancellation technique capable of suppressing multiple range intervals of clutter when waveform diversity is applied to pulse-Doppler radar

Development of passive bistatic radars based on orthogonal frequency-division multiplexing modulated signals for short and medium range surveillance

The main activity conducted during the research activity is the development of PBR systems based on OFDM signals of opportunity. In particular, a DAB based PBR for air traffic control (ATC) applications and a DVB-T based PBR for maritime surveillance have been objects of study

Modulation techniques for range measurements from satellites Final report

Modulation techniques for position fixing by range measurements from two or more satellite

Radar Technology

In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design

Enhanced Direction of Arrival Estimation through Electromagnetic Modeling

Engineering is a high art that balances modeling the physical world and designing meaningful solutions based on those models. Array signal processing is no exception, and many innovative and creative solutions have come from the field of array processing. However, many of the innovative algorithms that permeate the field are based on a very simple signal model of an array. This simple, although powerful, model is at times a pale reflection of the complexities inherent in the physical world, and this model mismatch opens the door to the performance degradation of any solution for which the model underpins. This dissertation seeks to explore the impact of model mismatch upon common array processing algorithms. To that end, this dissertation brings together the disparate topics of electromagnetics and signal processing. Electromagnetics brings a singular focus on the physical interactions of electromagnetic waves and physical array structures, while signal processing brings modern computational power to solve difficult problems. We delve into model mismatch in two ways; first, by developing a blind array calibration routine that estimates model mismatch and incorporates that knowledge into the reiterative superresoluiton (RISR) direction of arrival estimation algorithm; second, by examining model mismatch between a transmitting and receiving array, and assessing the impact of this mismatch on prolific direction of arrival estimation algorithms. In both of these studies we show that engineers have traded algorithm performance for model simplicity, and that if we are willing to deal with the added complexity we can recapture that lost performance