High Resolution MIMO Radar Sensing With Compressive Illuminations

• Published in: IEEE transactions on signal processing Vol. 70; pp. 1448 - 1463
• Main Authors: Sugavanam, Nithin, Baskar, Siddharth, Ertin, Emre
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Angle of arrival; Compressive sensing; Estimation; High resolution; Illumination; linear frequency modulated waveform; Microprocessors; MIMO radar; mutual coherence; Radar; Radar equipment; Receivers; Recovery; restricted isometry property; Scattering; Sensors; structured measurement matrix; Transmitters; Waveforms
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2022.3156731

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.