A General and Yet Efficient Scheme for Sub-Nyquist Radar Processing

TL;DR

This paper introduces a versatile and efficient sub-Nyquist radar processing scheme that improves target parameter estimation accuracy and reduces computational load, applicable to various analog-to-information conversion systems.

Contribution

It proposes a general, sequential, and decomposed estimation framework that enhances accuracy and efficiency for sub-Nyquist radar target parameter estimation.

Findings

High estimation accuracy for off-grid targets

Reduced computational complexity

Effective in diverse AIC systems

Abstract

We study the target parameter estimation for sub-Nyquist pulse-Doppler radar. Several past works have addressed this problem but either have low estimation accuracy for off-grid targets, take large computation load, or lack versatility for analog-to-information conversion (AIC) systems. To overcome these difficulties, we present a general and efficient estimation scheme. The scheme first formulates a general model in the sense that it is applicable to all AICs regardless of whether the targets are on or off the grids. The estimation of Doppler shifts and delays is performed sequentially, in which the Doppler estimation is formulated into a spatial spectrum estimation problem and the delay estimation is decomposed into a series of compressive parameter estimation problems with each corresponding to an estimated Doppler shift. By the sequential and decomposed processing, the computational complexity is substantially reduced, and by the parametric estimation techniques, the high accurate estimation is obtained. Theoretical analyses and numerical experiments show the effectiveness and the correctness of the proposed scheme.