In this paper an advanced version of the extensive cancellation algorithm (ECA) is proposed for robust disturbance cancellation and target detection in passive radar. Firstly some specific limitations of previous ECA versions are identified when dealing with a highly time-varying disturbance scenario in the presence of slowly moving targets. Specifically, the need to rapidly adapt the filter coefficients is shown to yield undesired effects on low Doppler target echoes, along with the expected partial cancellation. Therefore a sliding version of the ECA is presented which operates on partially overlapped signal batches. The proposed modification to the original ECA is shown to appropriately counteract the limitations above by taking advantage of a smooth estimate of the filter coefficients. An efficient implementation is also discussed to limit the corresponding computational load. The benefits of the proposed approach are demonstrated against real data sets accounting for quite different passive radar applications

In this paper we present a low cost sub-optimum technique for the evaluation of the two-dimensional (Delay-Doppler) Cross-Correlation Function in passive radar. Its performance is characterized both in terms of computational load and expected signal-to-noise ratio (SNR) loss, compared to optimum efficient algorithms and alternative sub-optimum approaches. The comparison is conducted with reference to typical case studies representative of aerial or maritime surveillance applications. The proposed approach is shown to allow a better control of the SNR loss to be accepted that can be more flexibly traded with the computational burden. Therefore it can be regarded as an effective solution for real time operation in computationally intensive scenarios as those expected for passive radar based on digital video broadcast transmissions

In this paper an advanced version of the Extensive Cancellation Algorithm (ECA) is proposed for robust disturbance cancellation and target detection in passive radar. Firstly some specific limitations of previous ECA versions are identified when dealing with a highly time-varying disturbance scenario in the presence of slowly moving targets. Specifically, the need to rapidly adapt the filter coefficients is shown to yield undesired effects on low Doppler target echoes, along with the expected partial cancellation. Therefore a sliding version of the ECA is presented which operates on partially overlapped signals batches. The proposed modification to the original ECA is shown to appropriately counteract the limitations above by taking advantage of a smooth estimate of the filter coefficients. The benefits of the proposed approach are demonstrated against experimental data sets accounting for quite different passive radar applications.I.

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