Verification of the virtual bandwidth SAR (VB-SAR) scheme for centimetric resolution subsurface imaging from space

This work presents the first experimental demonstration of the virtual bandwidth synthetic aperture radar (VB-SAR) imaging scheme. VB-SAR is a newly-developed subsurface imaging technique which, in stark contrast to traditional close-proximity ground penetrating radar (GPR) schemes, promises imaging from remote standoff platforms such as aircraft and satellites. It specifically exploits the differential interferometric synthetic aperture radar (DInSAR) phase history of a radar wave within a drying soil volume to generate high- resolution vertical maps of the scattering through the soil volume. For this study, a stack of C-band VV polarisation DInSAR images of a sandy soil containing a buried target was collected in the laboratory whilst the soil moisture was varied - firstly during controlled water addition, and then during subsequent drying. The wetting image set established the moisture-phase relationship for the soil, which was then applied to the drying DInSAR image set using the VB-SAR scheme. This allowed retrieval of high resolution VB-SAR imagery with a vertical discrimination of 0.04m from a stack of 1m vertical resolution DInSAR images. This work unequivocally shows that the basic principles of the VB-SAR technique are valid and opens the door to further investigation of this promising technique

Adaptive Illumination Patterns for Radar Applications

The fundamental goal of Fully Adaptive Radar (FAR) involves full exploitation of the joint, synergistic adaptivity of the radar\u27s transmitter and receiver. Little work has been done to exploit the joint space time Degrees-of-Freedom (DOF) available via an Active Electronically Steered Array (AESA) during the radar\u27s transmit illumination cycle. This research introduces Adaptive Illumination Patterns (AIP) as a means for exploiting this previously untapped transmit DOF. This research investigates ways to mitigate clutter interference effects by adapting the illumination pattern on transmit. Two types of illumination pattern adaptivity were explored, termed Space Time Illumination Patterns (STIP) and Scene Adaptive Illumination Patterns (SAIP). Using clairvoyant knowledge, STIP demonstrates the ability to remove sidelobe clutter at user specified Doppler frequencies, resulting in optimum receiver performance using a non-adaptive receive processor. Using available database knowledge, SAIP demonstrated the ability to reduce training data heterogeneity in dense target environments, thereby greatly improving the minimum discernable velocity achieved through STAP processing

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

Development and performance evaluation of a multistatic radar system

Multistatic radar systems are of emerging interest as they can exploit spatial diversity, enabling improved performance and new applications. Their development is being fuelled by advances in enabling technologies in such fields as communications and Digital Signal Processing (DSP). Such systems differ from typical modern active radar systems through consisting of multiple spatially diverse transmitter and receiver sites. Due to this spatial diversity, these systems present challenges in managing their operation as well as in usefully combining the multiple sources of information to give an output to the radar operator. In this work, a novel digital Commercial Off-The-Shelf (COTS) based coherent multistatic radar system designed at University College London, named ‘NetRad’, has been developed to produce some of the first published experimental results, investigating the challenges of operating such a system, and determining what level of performance might be achievable. Full detail of the various stages involved in the combination of data from the component transmitter-receiver pairs within a multistatic system is investigated, and many of the practical issues inherent are discussed. Simulation and subsequent experimental verification of several centralised and decentralised detection algorithms in terms of localisation (resolution and parameter estimation) of targets was undertaken. The computational cost of the DSP involved in multistatic data fusion is also considered. This gave a clear demonstration of several of the benefits of multistatic radar. Resolution of multiple targets that would have been unresolvable in a conventional monostatic system was shown. Targets were also shown to be plotted as two-dimensional vector position and velocities from use of time delay and Doppler shift information only. A range of targets were used including some such as walking people which were particularly challenging due to the variability of Radar Cross Section (RCS). Performance improvements were found to be dependant on the type of multistatic radar, method of data fusion and target characteristics in question. It is likely that future work will look to further explore the optimisation of multistatic radar for the various measures of performance identified and discussed in this work

Nonlinear Suppression of Range Ambiguity in Pulse Doppler Radar

Coherent pulse train processing is most commonly used in airborne pulse Doppler radar, achieving adequate transmitter/receiver isolation and excellent resolution properties while inherently inducing ambiguities in Doppler and range. First introduced by Palermo in 1962 using two conjugate LFM pulses, the primary nonlinear suppression objective involves reducing range ambiguity, given the waveform is nominally unambiguous in Doppler, by using interpulse and intrapulse coding (pulse compression) to discriminate received ambiguous pulse responses. By introducing a nonlinear operation on compressed (undesired) pulse responses within individual channels, ambiguous energy levels are reduced in channel outputs. This research expands the NLS concept using discrete coding and processing. A general theory is developed showing how NLS accomplishes ambiguity surface volume removal without requiring orthogonal coding. Useful NLS code sets are generated using combinatorial, simulated annealing optimization techniques - a general algorithm is developed to extended family size, code length, and number of phases (polyphase coding). An adaptive reserved code thresholding scheme is introduced to efficiently and effectively track the matched filter response of a target field over a wide dynamic range, such as normally experienced in airborne radar systems. An evaluation model for characterizing NLS clutter suppression performance is developed - NLS performance is characterized using measured clutter data with analysis indicating the proposed technique performs relatively well even when large clutter cells exist

Sidelobe suppression techniques for near-field multistatic SAR

Multirotor Unmanned Air Systems (UAS) represent a significant improvement in capability for Synthetic Aperture Radar (SAR) imaging when compared to traditional, fixed-wing, platforms. In particular, a swarm of UAS can generate significant measurement diversity through variation of spatial and frequency collections across an array of sensors. In such imaging schemes, the image formation step is challenging due to strong extended sidelobe; however, were this to be effectively managed, a dramatic increase in image quality is theoretically possible. Since 2015, QinetiQ have developed the RIBI system, which uses multiple UAS to perform short-range multistatic collections, and this requires novel near-field processing to mitigate the high sidelobes observed and form actionable imagery. This paper applies a number of algorithms to assess image reconstruction of simulated near-field multistatic SAR with an aim to suppress sidelobes observed in the RIBI system, investigating techniques including traditional SAR processing, regularised linear regression, compressive sensing. In these simulations presented, Elastic net, Orthogonal Matched Pursuit, and Iterative Hard Thresholding all show the ability to suppress sidelobes while preserving accuracy of scatterer RCS. This has also lead to a novel processing approach for reconstructing SAR images based on the observed Elastic net and Iterative Hard Thresholding performance, mitigating weaknesses to generate an improved combined approach. The relative strengths and weaknesses of the algorithms are discussed, as well as their application to more complex real-world imagery

On the Potential of Adaptive Beamforming for Phased-Array Weather Radar

As the Weather Surveillance Radar 1988 Doppler network reaches the end of its expected life, a network of multifunction phased-array radars (MPAR) supporting both aircraft and weather surveillance missions has been proposed. A phased-array system should match the sensitivity, spatial resolution, and data quality of the WSR-88D while having a update time of 60 seconds for weather surveillance. Since an MPAR system must complete both weather and aircraft surveillance missions, the update time reduction provided by having multiple faces is insufficient to achieve the desired 60 second update time for weather surveillance. Therefore, it is likely that multiple simultaneous beams would be needed per face to meet the timeline requirements. An approach to achieve multiple receive beams is to use a spoiled transmit beam and to form a cluster of simultaneous receive beams. However, a significant challenge for this approach is the potential of high sidelobe levels in the two-way radiation pattern, which can result in significantly biased estimates of the radar variables in situations where the signal power has large spatial variation. This dissertation proposes an adaptive beamspace algorithm designed for phased-array weather radar that utilizes a spoiled transmit beam and a cluster of simultaneous receive beams to achieve the desired timeline. Taking advantage of the adaptive algorithm's ability to automatically adjust sidelobe levels to match the scene, the high-sidelobe problem associated with a spoiled transmit beam is mitigated. Through extensive simulations, it is shown that adaptive beamspace processing can produce accurate and calibrated estimates of weather radar variables. Furthermore, it is demonstrated that the adaptive beamspace algorithm can automatically reject interference signals and reduce their impact on the radar-variable estimates. Additionally, it is shown that, despite higher sidelobe levels, the adaptive beamspace algorithm can perform similarly to a conventional system based on a dish antenna in terms of biases when reflectivity gradients are present. Finally, the adaptive beamspace algorithm is shown to compare favorably to some alternative solutions that can also achieve the desired MPAR timeline requirement while preserving data quality

Nonlinear Suppression of Range-Ambiguous Clutter for Outdoor Radar Measurement Facilities

In the outdoor measurement facility, a certain amount of real estate is owned by the organization, and therefore can be groomed to keep clutter contributions to a minimum. As the transmit signal travels further down range, however, returns from long-range clutter sources are inevitable and can have a significant impact on measurement accuracy. This research effort investigates the effectiveness of employing nonlinear suppression (NLS) to abate long-range ambiguous clutter in these facilities. Initial testing provides an extended proof-of-concept for coincident point scatterers representing target and clutter sources. The NLS process is finally applied to simulated measured data from the National Radar Test Facility (NRTF), where five cases representing various target versus clutter signal power ratios are tested. Ratios are selected to cover the range of clutter signals having 0.25 times the power to 4 times the power of the target signal. Results show promise for employing NLS in this arena, as one of the techniques studied retained on average 95 percent of the target signal power while discarding 78 percent of the ambiguous signal power

Multistatic Passive Weather Radar

Practical and accurate estimation of three-dimensional wind fields is an ongoing challenge in radar meteorology. Multistatic (single transmitter / multiple receivers) radar architectures offer a cost effective solution for obtaining the multiple Doppler measurements necessary to achieve such estimates. In this work, the history and fundamental concepts of multistatic weather radar are reviewed. Several developments in multistatic weather radar enabled by recent technological progress, such as the widespread availability of high performance single-chip RF transceivers and the proliferation of phased array weather radars, are then presented. First, a network of compact, low-cost passive receiver prototypes is used to demonstrate a set of signal processing techniques that have been developed to enable transmitter / receiver synchronization through sidelobe radiation. Next, a pattern synthesis technique is developed which allows for the use of sidelobe whitening to mitigate velocity biases in multistatic radar systems. The efficacy of this technique is then demonstrated using a multistatic weather radar system simulator