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.

This paper addresses the problem of direct signal interference (DSI) and clutter cancellation for passive radar systems on moving platforms using displaced phase centre antenna (DPCA) approach in the presence of receive channels imbalance. First, we show that using the signal emitted by the illuminator of opportunity as a source for channels calibration might be ineffective when DSI and clutter echoes have different directions of arrival. Then, a calibration approach is presented, based on supervised selection of clutter areas in the range-Doppler map. Finally, a two-stage strategy is presented, composed of an ECA-based DSI removal prior to DPCA clutter cancellation, which doesn't require supervised selection of the calibration area. The effectiveness of this scheme in the joint suppression of DSI and clutter is shown against real data.

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 Manuscript

This paper addresses the problem of clutter cancellation for ground moving target indication (GMTI) in multi-channel passive radar on mobile platforms. Specifically, the advantages of a space-time adaptive processing (STAP) approach are presented, compared to a displaced phase centre antenna (DPCA) approach, in the case of an angle-dependent imbalance affecting the receiving channels. The schemes are tested against simulated clutter data. Finally, a space-time GLRT detection scheme is proposed, where steering vector is not specified in the spatial domain, resulting in a non-coherent integration of target echoes across the receiving channels. Such solution offers comparable clutter cancellation capability and is more robust against significant calibration errors compared to a conventional GLRT detector, which suffers from spatial steering vector mismatches.

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.