High-Resolution Radar via Compressed Sensing

TL;DR

This paper introduces a compressed sensing radar method that discretizes the time-frequency plane, enabling high-resolution target detection with fewer measurements, and demonstrates its effectiveness through theoretical bounds and simulations.

Contribution

It presents a novel compressed sensing approach for radar that improves resolution and provides theoretical bounds on sparsity, verified by numerical simulations.

Findings

Theoretical upper bound on target sparsity K.

Numerical simulations show improved performance.

Potential for better resolution than classical radar.

Abstract

A stylized compressed sensing radar is proposed in which the time-frequency plane is discretized into an N by N grid. Assuming the number of targets K is small (i.e., K much less than N^2), then we can transmit a sufficiently "incoherent" pulse and employ the techniques of compressed sensing to reconstruct the target scene. A theoretical upper bound on the sparsity K is presented. Numerical simulations verify that even better performance can be achieved in practice. This novel compressed sensing approach offers great potential for better resolution over classical radar.