Litcius/Paper detail

High Resolution MIMO Radar Sensing With Compressive Illuminations

Nithin Sugavanam, Siddharth Baskar, Emre Ertin

2022IEEE Transactions on Signal Processing18 citationsDOI

Abstract

We present a compressive radar design that combines multitone linear frequency modulated (LFM) waveforms in the transmitter with a classical stretch processor and sub-Nyquist sampling in the receiver. The proposed compressive illumination scheme has fewer random elements resulting in reduced storage and complexity for implementation and calibration than previously proposed compressive radar designs based on stochastic waveforms. We analyze this illumination scheme for the task of a joint range-angle of arrival estimation in the multi-input and multi-output (MIMO) radar system. We present recovery guarantees for the proposed illumination technique. We show that for a sufficiently large number of modulating tones, the system achieves high-resolution in range and successfully recovers the range and angle-of-arrival of targets in a sparse scene. Furthermore, we demonstrate the stability of recovery of targets in range and angle of arrival domain in the continuum. Finally, we present simulation results to illustrate the recovery performance as a function of system parameters.

Topics & Concepts

Compressed sensingComputer scienceWaveformRadarMIMOAlgorithmTransmitterNyquist rateRange (aeronautics)Electronic engineeringSampling (signal processing)TelecommunicationsEngineeringChannel (broadcasting)DetectorAerospace engineeringSparse and Compressive Sensing TechniquesRadar Systems and Signal ProcessingMicrowave Imaging and Scattering Analysis
High Resolution MIMO Radar Sensing With Compressive Illuminations | Litcius