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The possibility of obtaining cross-range profiles of aerial targets is contemplated in this paper by applying inverse synthetic aperture radar (ISAR) techniques against FM-based passive radar data. The considered application is shown to pose a number of limitations, mostly related to the very long coherent processing interval required to attain a reasonable cross-range resolution. To mitigate such limitations, a suitable two-stage ISAR processing scheme is proposed for the estimation of the target motion induced phase history and its compensation. The results are shown against experimental data sets collected by a very high frequency (VHF) band passive radar receiver developed at Sapienza University of Rome. This allows to demonstrate the effectiveness of the proposed approach that provides the FM-based passive radar with advanced capabilities for air traffic surveillance applications.

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.

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.

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.

International audience; This paper presents research results in Space-Surface Multistatic Synthetic Aperture Radar (SS-MSAR) with non cooperative GPS satellites. The goal of this paper is to characterize such a system in an ISAR context, with a moving ground target. Point Spread Function (PSF) are defined and used in this work to estimate the performance in term of resolution. These criteria are computed, and compared, for several scenarios with targets of different velocities.