Target detection using sparsity based deconvolution in passive bistatic radars

We introduce a sparsity based deconvolution scheme to improve the range resolution of passive bistatic radar (PBR) systems. The two-dimensional matched filter output of a PBR system is further analyzed as a deconvolution problem. The deconvolution algorithm is based on making projections onto hyperplanes representing the time delay of a target and the epigraph set of a convex cost function such as the l₁ norm. The iterative algorithm is globally convergent because all constraint sets are closed and convex. Simulation results in a FM based PBR system are presented. The proposed method performs better than frequency domain deconvolution methods.