Diego Cristallini

This work investigates the impact of motion estimation errors on passive inverse synthetic aperture radar (ISAR) images of rotating targets when back-projection algorithm (BPA) is employed to focus the data. Accurate target motion estimation can be quite challenging, especially in non-cooperative target scenarios. In these cases, BPA is applied under erroneous target kinematics information, entailing defocusing and distortions of the final image product. Starting from the evaluation of the image point spread function (PSF) and the resolution properties of the BPA image under ideally known target motion, it will be analytically shown as, at first order, the PSF under motion estimation errors is approximately a scaled and rotated version of the nominal one. Then, theoretical solutions to predict the location of the scatterers in the image will be provided to characterize in closed-form the distortion of the BPA plane. Numerical results under different use cases of practical interest are provided to analyze the level of accuracy required by the motion estimation task for a reliable focusing in the challenging passive radar scenario. Experimental results using both terrestrial and satellite signals of opportunity are also provided, showing the general validity of the approach in different passive ISAR systems. The present analysis is not limited to passive radars and it can be also applied to active bistatic radars having limited transmitted bandwidth.

Recently, several constellations of broadband low‐Earth orbit communication satellites, such as Starlink or OneWeb, have started to be deployed to provide global internet access. Based on performed analyses, these emerging constellations are considered promising candidates as space‐based transmitters of opportunity for passive radar applications due to their advantageous characteristics in terms of global coverage, high bandwidth (i.e. better resolution), high received power on Earth surface (i.e. increased maximum range), predictable trajectory, and network density and robustness. However, they also pose certain challenges for the development of passive radar systems due to the necessity to track the satellites with a narrow beam reference antenna, their fast‐relative dynamics which induce range and Doppler migration, and the use of non‐standardised signals with little publicly available information, which in addition are not optimised for radar usage. In this article, these capabilities and challenges are analysed, putting a special focus on the estimation of the achievable performance and on the experimental characterisation of the transmitted signals. To this end, the proposed passive radar architectures and the first developed prototypes are also presented. Showing the potential capabilities of these emerging illuminators of opportunity, the authors aim to promote further development of this technology for multiple applications.

Passive radar is a technology that has huge potential for airspace monitoring, taking advantage of existing transmissions. However, to predict whether particular targets can be measured in a particular scenario, it is necessary to be able to model the received signal. In this paper, we present the results of a campaign in which a Pilatus PC-12 single-engine aircraft was measured with a passive radar system relying on DVB-T transmission from a single transmitter. We then present our work to simulate the bistatic RCS of the aircraft along its flight track, using both the method of moments and the shooting and bouncing ray solvers, assess the uncertainty in the simulations, and compare against the measurements. We find that our simulated RCS values are useful in predicting whether or not detection occurs. However, we see poor agreement between simulated and measured RCS values where measurements are available, which we attribute primarily to the difficulties in extracting RCS measurements from the data and to unmodeled transmission and received path effects.

This paper deals with the problem of detection and direction of arrival (DOA) estimation of slowly moving targets against clutter in multichannel mobile passive radar. A dual cancelled channel space-time adaptive processing (STAP) scheme is proposed, aiming at reducing the system computational complexity, as well as the amount of required training data, compared to a conventional full array solution. The proposed scheme is shown to yield comparable target detection capability and DOA estimation accuracy with respect to the corresponding full array solution, despite the lower computational cost required. Moreover, it offers increased robustness against adaptivity losses, operating effectively even in the presence of a limited set of training data, as often available in the highly non-homogeneous clutter scenarios experienced in bistatic passive radar. The effectiveness of the proposed scheme and its suitability for passive GMTI are demonstrated against both simulated and experimental data collected by a DVB-T-based multichannel mobile passive radar.

This article addresses the problem of clutter cancelation for slowly moving target detection and localization in multichannel passive radar onboard mobile platforms. A post-Doppler space-time adaptive processing (STAP) approach is exploited in the case of an angle-dependent imbalance affecting the receiving channels. While the clutter suppression capability is ensured by the adaptivity of space-time filtering, different solutions are compared, aimed at recovering the detection performance losses associated with channel calibration errors. A space-time generalized-likelihood ratio test (GLRT) scheme is considered, where the steering vector is not specified in the spatial domain, resulting in a noncoherent integration of target echoes across the receiving channels. This is compared with a fully coherent GLRT scheme where echoes from the stationary scene are exploited for the proper calibration of spatial steering vector mismatch. The first scheme proves to be a simple solution for target detection in the passive radar case, offering comparable clutter cancelation capability. The second scheme, at the expense of an additional stage, offers slightly better detection performance and preserves target direction-of-arrival (DoA) estimation capability. Finally, the STAP scheme is employed for the maximum-likelihood estimation of target DoA, evaluating the role of the steering vector calibration against the negative impact of channel imbalance. The effectiveness of the proposed approaches is tested against both simulated and experimental data from a DVB-T-based mobile passive radar.

Research in passive radar has moved its focus towards passive radar on moving platforms in recent years with the purpose of moving target indication and ground imaging via synthetic aperture radar. This is also fostered by the progress in hardware miniaturization, which alleviates the installation of the required hardware on moving platforms. Terrestrial transmitters, commonly known as illuminators of opportunity in the passive radar community, usually emit the signals in the Very High Frequency (VHF) or Ultra High Frequency (UHF) band. Due to the long wavelengths of the VHF/UHF band, there are constraints on the size of the used antenna elements, and therefore, the number of antenna elements to be employed is limited, especially as the platform carrying the passive radar system is intended to be small, potentially even an unmanned aerial vehicle. In order to detect moving targets hidden by Doppler shifted clutter returns, one common approach is to suppress the clutter returns by applying clutter suppression techniques that rely on spatial and temporal degrees of freedom, such as Displaced Phase Center Antenna (DPCA) or Space-Time Adaptive Processing. It has been shown that the DPCA approach is a meaningful technique to suppress the clutter if two antenna elements are employed. However, if the employed receiving channels are not carefully calibrated, the clutter suppression is shown to be not effective. Here, we suggest a three-stage calibration technique in order to perform the calibration of two receiving channels, which involves the exploitation of the direct signal, a data-adaptive amplitude calibration, and finally, a data-adaptive calibration of phase mismatches between both receiving channels by the estimation of the Minimum Variance Power Spectrum of the clutter. The validity of the proposed approach is shown with simulated data and demonstrated on real data from a fast ground moving platform, showing improved clutter cancellation capabilities.

We address the problem of co‐channel interference (CCI) in multi‐channel airborne passive radars using digital broadcast signals of opportunity. A framework for suppressing the CCI is proposed, based on a two‐stage approach, which reflects the range–Doppler map being a function of both a reference and a surveillance signal. In the first stage, the multiple receiving channels are used to reduce the CCI and hence improve the reconstruction of the digital reference signal. In the second stage, multi‐channel processing in the range–Doppler domain is performed to further limit the effects of CCI. For each CCI suppression stage, several filters are proposed and their performances are evaluated against real data.

In this work, we focus on passive polarimetric ISAR for ship target imaging using DVB-S signals of opportunity. A first goal of the research is to investigate if, within the challenging passive environment, different scattering mechanisms, belonging to distinct parts of the imaged target, can be separated in the polarimetric domain. Furthermore, a second goal is at verifying if polarimetric diversity could enable the formation of ISAR products with enhanced quality with respect to the single channel case, particularly in terms of better reconstruction of the target shape. To this purpose, a dedicated trial has been conducted along the river Rhine in Germany by means of an experimental DVB-S based system developed at Fraunhofer FHR and considering a ferry as cooperative target. To avoid inaccuracies due to data-driven motion compensation procedures and to fairly interpret the polarimetric results, we processed the data by means of a known-motion back-projection algorithm obtaining ISAR images at each polarimetric channel. Then, different approaches in the polarimetric domain have been introduced. The first one is based on the well-known Pauli Decomposition. The others can be divided in two main groups: (i) techniques aimed at separating the different backscattering mechanisms, and (ii) image domain techniques to fuse the polarimetric information in a single ISAR image with enhanced quality. The different considered techniques have been applied to several data sets with distinct bistatic geometries. The obtained results clearly demonstrate the potentialities of polarimetric diversity that could be fruitfully exploited for classification purposes.

This paper addresses the problem of direct signal interference (DSI) and clutter cancellation for passive radar systems on moving platforms employing displaced phase centre antenna (DPCA) approach. Attention is focused on the development of signal processing strategies able to compensate for the limitations deriving from amplitude and phase imbalances that affect the two channels employed on receive. First, we show that using the signal received from the illuminator of opportunity as a source for channels calibration might be ineffective when DSI and clutter echoes have different directions of arrival, due to the effect of angle-dependent channel imbalance. Then, a two-stage strategy is proposed, consisting of a preliminary DSI removal stage at each receive channel, followed by a clutter-based calibration approach that basically enables an effective DPCA clutter suppression. Different strategies for channel calibration are proposed, aimed at compensating for potential angle and range dependent channel errors, based on the maximization of the cancellation performance. Effectiveness of this scheme is shown against experimental data from a DVB-T based moving passive radar, in the presence of both real and synthetic moving targets.