Direct signal recovery and masking effect removal exploiting sparsity for passive bistatic radar

Direct signal recovery and strong target cancellation are key techniques for weak target detection in passive bistatic radar. Exploiting the sparsity of the multipath channel, the approach of sparse blind equalizer based on constant modulus criteria is proposed against the multipath interference on the direct signal. The computational complexity of the sparse equalizer reduced greatly, accomplishing the direct signal recovery with acceptable performance degradation. Exploiting the sparsity of the strong targets, a type of two dimensional sparse adaptive filter is proposed based on the estimation of the time delay and Doppler shift of the strong targets. Weak returns detection is accomplished after the subtraction of the adaptive filter outputs from the main surveillance channel. The performance of the sparse blind equalizer and two-dimensional sparse canceller are validated by computer simulations.