In the airborne passive radar system, space-time adaptive processing (STAP) employs the reference signal for clutter covariance matrix estimation. However, the clutter caused by the multipath signals involved in the reference channel (MP clutter) can corrupt the estimated covariance matrix. When the target under detection and the MP clutter have the same Doppler frequencies and spatial frequencies, the STAP would mistake the target as clutter and target detection performance would degrade. To cope with this problem, a novel cascaded clutter suppression method is proposed. In the proposed algorithm, based on the sparsity of the MP clutter in the range-Doppler domain, the cost function with a sparse constraint is first introduced. Then, an l1-based recursive least squares algorithm is used to solve the resulting optimization problem, and MP clutter can be eliminated by the derived weight vector. Finally, the residual clutter is suppressed by the existing STAP algorithm. A range of simulations demonstrates that the proposed algorithm has superior performance in the presence of a contaminated reference signal.
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