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

Passive radar on moving platforms exploiting DVB-T transmitters of opportunity

The work, effort, and research put into passive radar for stationary receivers have shown significant developments and progress in recent years. The next challenge is mounting a passive radar on moving platforms for the purpose of target detection and ground imaging, e.g. for covert border control. A passive radar on a moving platform has many advantages and offers many benefits, however there is also a considerable drawback that has limited its application so far. Due to the movement the clutter returns are spread in Doppler and may overlap moving targets, which are then difficult to detect. While this problem is common for an active radar as well, with a passive radar a further problem arises: It is impossible to control the exploited time-varying waveform emitted from a telecommunication transmitter. A conventional processing approach is ineffective as the time-varying waveform leads to residuals all over the processed data. Therefore a dedicated clutter cancellation method, e.g. the displaced phase centre antenna (DPCA) approach, does not have the ability to completely remove the clutter, so that target detection is considerably limited. The aim must be therefore to overcome this limitation by exploiting a processing technique, which is able to remove these residuals in order to cope with the clutter returns thus making target detection feasible. The findings of this research and thesis show that a reciprocal filtering based stage is able to provide a time-invariant impulse response similar to the transmissions of an active radar. Due to this benefit it is possible to achieve an overall complete clutter removal together with a dedicated DPCA stage, so that moving target detection is considerably improved, making it possible in the first place. Based on mathematical analysis and on simulations it is proven, that by exploiting this processing in principle an infinite clutter cancellation can be achieved. This result shows that the reciprocal filter is an essential processing stage. Applications on real data acquired from two different measurement campaigns prove these results. By the proposed approach, the limiting factor (i.e. the time-varying waveform) for target detection is negotiated, and in principle any clutter cancellation technique known from active radar can be applied. Therefore this analysis and the results provide a substantial contribution to the passive radar research community and enables it to address the next questions

Passive Synthetic Aperture Radar Imaging Using Commercial OFDM Communication Networks

Modern communication systems provide myriad opportunities for passive radar applications. OFDM is a popular waveform used widely in wireless communication networks today. Understanding the structure of these networks becomes critical in future passive radar systems design and concept development. This research develops collection and signal processing models to produce passive SAR ground images using OFDM communication networks. The OFDM-based WiMAX network is selected as a relevant example and is evaluated as a viable source for radar ground imaging. The monostatic and bistatic phase history models for OFDM are derived and validated with experimental single dimensional data. An airborne passive collection model is defined and signal processing approaches are proposed providing practical solutions to passive SAR imaging scenarios. Finally, experimental SAR images using general OFDM and WiMAX waveforms are shown to validate the overarching signal processing concept

Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

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Research progress on geosynchronous synthetic aperture radar

Based on its ability to obtain two-dimensional (2D) high-resolution images in all-time and all-weather conditions, spaceborne synthetic aperture radar (SAR) has become an important remote sensing technique and the study of such systems has entered a period of vigorous development. Advanced imaging modes such as radar interferometry, tomography, and multi-static imaging, have been demonstrated. However, current in-orbit spaceborne SARs, which all operate in low Earth orbits, have relatively long revisit times ranging from several days to dozens of days, restricting their temporal sampling rate. Geosynchronous SAR (GEO SAR) is an active research area because it provides significant new capability, especially its much-improved temporal sampling. This paper reviews the research progress of GEO SAR technologies in detail. Two typical orbit schemes are presented, followed by the corresponding key issues, including system design, echo focusing, main disturbance factors, repeat-track interferometry, etc, inherent to these schemes. Both analysis and solution research of the above key issues are described. GEO SAR concepts involving multiple platforms are described, including the GEO SAR constellation, GEO-LEO/airborne/unmanned aerial vehicle bistatic SAR, and formation flying GEO SAR (FF-GEO SAR). Due to the high potential of FF-GEO SAR for three-dimensional (3D) deformation retrieval and coherence-based SAR tomography (TomoSAR), we have recently carried out some research related to FF-GEO SAR. This research, which is also discussed in this paper, includes developing a formation design method and an improved TomoSAR processing algorithm. It is found that GEO SAR will continue to be an active topic in the aspect of data processing and multi-platform concept in the near future

Advances in Synthetic Aperture Radar from a Wavenumber Perspective

This dissertation examines the wavenumber domain of Synthetic Aperture Radar (SAR) images. This domain is the inverse Fourier transform domain of a SAR image. The dissertation begins with the radar receiver's signal model and develops equations describing the wavenumber domain of a SAR image produced by a generalized bistatic and monostatic SAR system. Then, closed form expressions for bistatic synthetic aperture radar spatial resolution of a generalized system from the wavenumber domain are developed. These spatial resolution equations have not previously appeared in the literature. From these equations, significant resolution is found in both range and cross-range forecasting a forward-scatter bistatic SAR image when the elevation angles of each bistatic platform are significantly different. Next, wavenumber and time domain image formation algorithms are discussed. Developed within this dissertation is a wavenumber preprocessing method that increases the speed of the Back Projection Algorithm (BPA). This preprocessing method takes advantage of deramped SAR radar returns and their polar wavenumber format. This new algorithm is called the Fast Decimated Wavenumber Back Projection Algorithm (FDWBPA). Matlab functions are included to implement this algorithm, simulate bistatic SAR images and process the data from anechoic chamber tests demonstrating forward scatter resolution

Reverse Backprojection Method for Simulation of Passive Bistatic SAR Data

Synthetic Aperture Radar (SAR) is a valuable tool for acquiring information about landscapes through forming two-dimensional images remotely. SAR has useful applications for defense, intelligence, humanitarian, and urban planning efforts, among others. Because of increased competition for suitable transmission frequencies in the electromagnetic spectrum from wireless communication corporations, passive bistatic radar has been extensively studied over the last few decades as a means of circumventing that obstacle. However, it does not come without its own introduced challenges - because telecommunication waveforms are continually changing, that variability introduces a large computational burden. In order to model data generation in a simulation environment, it is necessary to develop processing methods that will perform in a timely manner. In this work we present the Reverse Backprojection Algorithm, derived from the adaptable, commonly-used, yet brute force backprojection imaging algorithm, as a novel approach to generate simulated passive bistatic SAR data. To demonstrate the algorithm's effectiveness, we conduct a variety of simulations employing 4G Long Term Evolution (LTE) waveforms. Because LTE waveforms are not designed for radar usage, self-ambiguities within the waveform autocorrelation function degrade image quality. Simulations performed on point scatterers and distributed scenes illustrate these introduced artifacts, and meaningful comparisons are provided to determine which configurations more suited for SAR operation and identify additional processing needs

Signal Processing for Synthetic Aperture Sonar Image Enhancement

This thesis contains a description of SAS processing algorithms, offering improvements in Fourier-based reconstruction, motion-compensation, and autofocus. Fourier-based image reconstruction is reviewed and improvements shown as the result of improved system modelling. A number of new algorithms based on the wavenumber algorithm for correcting second order effects are proposed. In addition, a new framework for describing multiple-receiver reconstruction in terms of the bistatic geometry is presented and is a useful aid to understanding. Motion-compensation techniques for allowing Fourier-based reconstruction in widebeam geometries suffering large-motion errors are discussed. A motion-compensation algorithm exploiting multiple receiver geometries is suggested and shown to provide substantial improvement in image quality. New motion compensation techniques for yaw correction using the wavenumber algorithm are discussed. A common framework for describing phase estimation is presented and techniques from a number of fields are reviewed within this framework. In addition a new proof is provided outlining the relationship between eigenvector-based autofocus phase estimation kernels and the phase-closure techniques used astronomical imaging. Micronavigation techniques are reviewed and extensions to the shear average single-receiver micronavigation technique result in a 3 - 4 fold performance improvement when operating on high-contrast images. The stripmap phase gradient autofocus (SPGA) algorithm is developed and extends spotlight SAR PGA to the wide-beam, wide-band stripmap geometries common in SAS imaging. SPGA supersedes traditional PGA-based stripmap autofocus algorithms such as mPGA and PCA - the relationships between SPGA and these algorithms is discussed. SPGA's operation is verified on simulated and field-collected data where it provides significant image improvement. SPGA with phase-curvature based estimation is shown and found to perform poorly compared with phase-gradient techniques. The operation of SPGA on data collected from Sydney Harbour is shown with SPGA able to improve resolution to near the diffraction-limit. Additional analysis of practical stripmap autofocus operation in presence of undersampling and space-invariant blurring is presented with significant comment regarding the difficulties inherent in autofocusing field-collected data. Field-collected data from trials in Sydney Harbour is presented along with associated autofocus results from a number of algorithms