Gain-constrained adaptive pulse compression via an MVDR framework

Abstract

Much work has been done to discover pulse compression methods that alleviate the effects of range sidelobes, though pulse compression filters that deviate from the matched filter suffer from varying degrees of mismatch loss. The Minimum Mean-Square Error (MMSE) based Adaptive Pulse Compression (APC) algorithm is capable of suppressing range sidelobes into the noise by employing a unique pulse compression filter for each range cell. Recently, Fast APC (FAPC) has been developed to reduce the computational cost of APC while maintaining much of the sidelobe suppression capability. This paper utilizes the MVDR framework to facilitate inclusion of a unity gain constraint within the APC and FAPC cost functions in an effort to mitigate mismatch loss. The APC algorithm exhibits almost no mismatch loss and, as such, the full-dimension algorithm benefits little from the gain constraint. However, FAPC occasionally suppresses small targets in dense scattering environments due to fewer degrees of freedom inherent to reduced-dimensionality processing. The constrained FAPC algorithm preserves gain on small targets consequently improving detection performance.