Joint Optimization of Waveform Covariance Matrix and Antenna Selection for MIMO Radar

TL;DR

This paper presents a joint optimization framework for MIMO radar systems that enhances transmit beampattern accuracy and reduces cross-correlation by optimizing waveform covariance and antenna placement, suitable for real-time applications.

Contribution

It introduces a novel cyclic and local optimization approach for jointly designing waveform covariance and antenna positions in MIMO radar systems.

Findings

Effective approximation of desired beampatterns

Reduced cross-correlation of reflected signals

Suitable for real-time radar processing

Abstract

In this paper, we investigate the problem of jointly optimizing the waveform covariance matrix and the antenna position vector for multiple-input-multiple-output (MIMO) radar systems to approximate a desired transmit beampattern as well as to minimize the cross-correlation of the received signals reflected back from the targets. We formulate the problem as a non-convex program and then propose a cyclic optimization approach to efficiently tackle the problem. We further propose a novel local optimization framework in order to efficiently design the corresponding antenna positions. Our numerical investigations demonstrate a good performance both in terms of accuracy and computational complexity, making the proposed framework a good candidate for real-time radar signal processing applications.