Random filtering structure-based compressive sensing radar

Abstract

Recently with an emerging theory of 'compressive sensing' (CS), a radically new concept of compressive sensing radar (CSR) has been proposed in which the time-frequency plane is discretized into a grid. Random filtering is an interesting technique for efficiently acquiring signals in CS theory and can be seen as a linear time-invariant filter followed by decimation. In this paper, random filtering structure-based CSR system is investigated. Note that the sparse representation and sensing matrices are required to be as incoherent as possible; the methods for optimizing the transmit waveform and the FIR filter in the sensing matrix separately and simultaneously are presented to decrease the coherence between different target responses. Simulation results show that our optimized results lead to smaller coherence, with higher sparsity and better recovery accuracy observed in the CSR system than the nonoptimized transmit waveform and sensing matrix. © 2014 Zhang et al.