Frequency diverse waveforms for compressive radar sensing

Abstract

High range resolution radar systems use wideband frequency modulated waveforms to estimate the spatial distribution of the scatterers in the scene. Estimation of range profiles from backscatter energy is a linear inverse problem. The emerging field of compressive sensing has provided provable performance guarantees and signal recovery algorithms for random sub-sampling of sparse or compressible signals. In this paper a novel compressive sensing strategy for radar is introduced which relies on using waveforms with frequency diversity on transmit and random aliasing on receive, that shifts the burden of the sampling operator from the receiver to the transmitter. The transmitter and receiver structure for compressive sensing is described and the sensing matrix for the proposed compressive sensing strategy is derived for use in compressive sensing recovery algorithms based on sparsity regularized inversion. A preliminary experimental demonstration of the compressive sensing strategy is given through sampling of staggered multifrequency linear FM signals through a single low rate A/D.