Reduced Complexity Angle-Doppler-Range Estimation for MIMO Radar That Employs Compressive Sensing

TL;DR

This paper introduces a decoupled estimation method for MIMO radar using compressive sensing that reduces computational complexity while maintaining high resolution in angle, Doppler, and range measurements.

Contribution

It proposes a novel decoupled approach to joint angle-Doppler-range estimation in MIMO radar with compressive sensing, reducing computational burden.

Findings

Achieves high range resolution with step frequency and CS

Significantly reduces computational complexity

Maintains super-resolution performance

Abstract

The authors recently proposed a MIMO radar system that is implemented by a small wireless network. By applying compressive sensing (CS) at the receive nodes, the MIMO radar super-resolution can be achieved with far fewer observations than conventional approaches. This previous work considered the estimation of direction of arrival and Doppler. Since the targets are sparse in the angle-velocity space, target information can be extracted by solving an l1 minimization problem. In this paper, the range information is exploited by introducing step frequency to MIMO radar with CS. The proposed approach is able to achieve high range resolution and also improve the ambiguous velocity. However, joint angle-Doppler-range estimation requires discretization of the angle-Doppler-range space which causes a sharp rise in the computational burden of the l1 minimization problem. To maintain an acceptable complexity, a technique is proposed to successively estimate angle, Doppler and range in a decoupled fashion. The proposed approach can significantly reduce the complexity without sacrificing performance.