Debora Pastina

Adaptive polarimetric target detection with coherent radar. II. Detection against non-Gaussian background

The derivation of a completely adaptive polarimetric coherent scheme to detect a radar target against a Gaussian background is presented. A previously proposed Generalized Likelihood Ratio Test (GLRT) polarimetric detector is extended to the case of a general number of channels; this exploits the polarimetric characteristics of the received radar echoes to improve the detection performance. Together with the fully adaptive scheme, a model-based detector is derived that has a lower estimation loss. A complete theoretical expression is derived for the detection performance of both proposed polarimetric detectors. They are shown to have Constant False Alarm Rate (CFAR) when operating against Gaussian clutter, but to be sensitive to deviations from the Gaussian statistic. The application to recorded radar data demonstrates the performance improvement achievable in practice.

Multistatic and MIMO Distributed ISAR for Enhanced Cross-Range Resolution of Rotating Targets

In this paper, we present a new technique to exploit the data acquired simultaneously by multiple radar sensors carried by multiple air platforms to increase the cross-range resolution of inverse synthetic aperture radar (ISAR) images of rotating targets. This distributed ISAR technique is devised for two different cases: 1) multiple-input-multiple-output (MIMO) case with each platform carrying an active radar that transmits and receives RF waveforms and 2) multistatic case with a single platform carrying an active radar (transmitting and receiving) and the remaining platforms equipped with passive sensors (namely, receiving only). The processing chain proposed for the distributed ISAR is shown, together with the results obtained against simulated ISAR data for both the MIMO and the multistatic cases. The performance analysis shows that the proposed technique is able to provide an increase of the cross-range resolution up to the number of platforms in the multistatic case and even higher in the MIMO case, if the platforms are properly located. This is of great benefit in applications where the target rotation angle is insufficient to guarantee the desired resolution. A typical case is the imaging of ship targets with rotation induced by the sea swell structure under low sea state conditions. To make the results appealing for practical application, the performance degradation is also analyzed arising from errors in the knowledge of both the target rotation motion and the acquisition geometry. Experimental data collected by a ground-based radar operating together with a rotating platform are processed by following the presented distributed ISAR technique to validate the proposed approach.

Exploiting MIMO SAR Potentialities With Efficient Cross-Track Constellation Configurations for Improved Range Resolution

In this paper, an innovative technique is presented for synthetic aperture radar (SAR) ground range resolution improvement using multiple transmit and receive platforms with adequate cross-track displacement. Using orthogonal waveforms, which occupy the same bandwidth in the range frequency domain, for the different platforms of the constellation, a multiple-input-multiple-output SAR system is configured. The proposed technique allows one to achieve a maximum theoretical range resolution improvement factor that is significantly greater than the number of operating SAR sensors by jointly exploiting both mono- and bistatic acquisitions. This can be exploited to obtain a ground range resolution that is much higher than the resolution corresponding to the frequency bandwidth transmitted by the single platform. After illustrating the proposed technique and its system requirements, a simulated data set is used to show the effectiveness of the proposed approach.

Efficient Detection and Imaging of Moving Targets in SAR Images Based on Chirp Scaling

An innovative scheme is presented for moving target detection and high-resolution focusing that exploits a bank of chirp scaling algorithms (CSA), each one matched to a different along track target velocity component. The new scheme is thought for multichannel (MC) synthetic aperture radar systems, to provide a high-resolution focusing of the moving targets. Adequate target detection capability is ensured by integrating the aforementioned bank of CSA with a post-Doppler space-time adaptive processing clutter cancellation step. The presented scheme is very efficient from a computational point of view and is able to achieve sub-clutter visibility for the moving targets. The effectiveness of the proposed techniques is shown with reference to an emulated MC data set.

Multiband coherent radar detection against compound-Gaussian clutter

A Multiband GLRT-LQ (Generalized Likelihood Ratio Test-Linear Quadratic), MBGLRT-LQ, detector is derived for the coherent radar target detection against a compound-Gaussian clutter background. This scheme is an extension to the multiband case of the Asymptotically Optimum Detector (AOD), also derived under the name of GLRT-LQ in. The proposed multiband version of the algorithm shows two main advantages with respect to the original single-band algorithm. 1) For the adaptive implementation, it requires a much smaller area of homogeneous clutter echoes to estimate the covariance matrix of the interference; 2) it provides an optimum processing of the radar echoes when the radar operates in frequency agility, as electronic counter-countermeasure (ECCM) strategy. A closed form performance analysis is provided for the MBGLRT-LQ detector, which is used to compare it with the single-band version. An application to live recorded data is also presented to validate the obtained results.

Parasitic Exploitation of Wi-Fi Signals for Indoor Radar Surveillance

In this paper, we examine the potentiality of passive coherent location (PCL) for indoor area monitoring. In particular, we show that Wi-Fi transmissions can be successfully exploited as waveforms of opportunity to perform moving target detection and localization based on the passive radar principle. Moreover, we investigate the advanced capability to obtain high-resolution cross-range profiles of the observed targets via inverse-synthetic-aperture-radar (ISAR) techniques. To these purposes, appropriate processing techniques are introduced to cope with the limitations resulting from the indoor applications such as the strong returns from the stationary scene and the high density of potential targets. The proposed system concept has been tested against both simulated and real data sets. The reported results clearly show that using few receiving channels connected to properly dislocated antennas allows an accurate target localization and tracking. In addition, reliable and stable profiles are obtained for the targets moving in the surveyed scene, which might fruitfully feed a classification stage. This contributes to the demonstration of the effective applicability of the passive radar concept for improving internal and external security of private/public premises.

Point Spread Function Analysis for GNSS-Based Multistatic SAR

This letter presents an analysis of the multistatic point-spread function (MPSF) for passive synthetic aperture radar (SAR) with navigation satellites as opportunity transmitters and a stationary receiver. It is shown that a noncoherent combination of bistatic SAR images, obtained by multiple, spatially separated satellites, can yield multistatic imagery that may be essentially improved in terms of resolution when compared with a single bistatic SAR image. The MPSF is derived analytically, for an arbitrary number of bistatic acquisitions and for any bistatic topologies. Analytical results are confirmed using both simulated and experimental data. The obtained result could be applied for the analysis of spatial resolution in multistatic real time radar, thus enabling the adaptive selection of the more suitable opportunity transmitters.

WiFi-Based Passive ISAR for High-Resolution Cross-Range Profiling of Moving Targets

This paper presents an effective signal processing scheme to track moving vehicles and to obtain their cross-range profiles with a passive bistatic radar (PBR) based on the signals of opportunity emitted by a WiFi router. While the target detection using WiFi-based PBR has already been studied by the authors, this paper focuses on the targets moving with a low radial velocity component. These are especially interesting since they might have a reasonable cross-range velocity component, which allows us to apply inverse synthetic aperture radar (ISAR) techniques to provide a high-resolution cross-range profile. A specific problem for these targets is the presence of possibly strong echoes from the stationary background (clutter), which tend to mask their contributions. In such cases, the standard Doppler processing does not help in separating the targets from this clutter. Therefore, appropriate clutter cancellation schemes are applied, and their effectiveness and impact are analyzed both on the tracking and on the ISAR profiling. An appropriate ISAR scheme for cross-range profiling is introduced, tailored for the typical short-range and possibly bistatic surveillance scenarios of the WiFi-based PBR; this scheme comprises the automatic estimation from the data of the target motion components up to a higher order than in usual long-range imaging and their compensation. The reliability of the obtained profiles is also investigated, for both the monostatic and bistatic cases, which is essential both for the vehicle size/characteristics estimation and for the automatic recognition schemes based on vehicle databases. The results obtained using an experimental setup developed and fielded at the University of Rome “La Sapienza,” Rome, Italy, show that the considered approach is effective and that the obtained cross-range profiles achieved by ISAR processing with WiFi-based passive radar are quite reliable both in the monostatic and bistatic cases.

Polarimetric detectors of extended targets for ship detection in SAR images

This paper deals with polarimetric detection of ships in SAR images of medium/high resolution (about meters). The aim is to develop detection techniques able to exploit the polarimetric information in order to improve the detection capability of ships or generally man-made targets modelled as extended targets (i.e. occupying multiple pixels). Both a decentralized and a centralized approach are considered for the fusion of the polarimetric information and their performance are characterized.

Adaptive polarimetric target detection with coherent radar

A CFAR adaptive polarimetric generalized likelihood ratio test (GLRT) detector is proposed for the coherent detection of radar targets against a Gaussian background and its performance is fully characterized. A model based version of such a detector is also derived by applying a similar GLRT approach to a structured covariance matrix. This latter detector is shown to reduce the adaptivity losses and thus to reduce the homogeneous region, which is required to estimate the clutter covariance matrix. The application to live radar data demonstrates the performance improvement achievable in practice by exploiting the polarimetric information. In particular adding the HV channel to the two co-polarized channels can provide a sensible performance increase with respect to the HH and VV only. This is especially true for man-made targets having cross-polarized response higher than the clutter. When the target has a lower cross-polarized return than the clutter, a much lower improvement is available but there is not a sensible adaptivity loss and the CFAR characteristic is always enforced against the Gaussian background.