Genetic Algorithms for Distributed MIMO Radar Antenna Position Optimization

This is the authors' abstract. We don't add key points for this paper.

In multiple-input multiple-output (MIMO) radars, carrier frequency, signal bandwidth and antenna geometry have a deep impact on the ambiguity function (AF). In particular for systems employing widely separated antennas, sidelobes and azimuth ambiguities may appear in the MIMO-AF, potentially leading to a degradation of the system detection and localization capabilities.The aim of this paper is to optimize antenna positions along the MIMO baseline using genetic algorithms (GAs). Key performance indicators (KPIs), such as the peak-to-maximum and peak-to-average sidelobe ratios, as well as the range and cross-range resolutions are investigated as potential optimization criteria.As a practical study case, a MIMO radar working the in Xband is simulated. The system employs two transmitters (TXs) and four receivers (RXs), with free-located TX-RX antenna pairs. The analysis is conducted for a point-like target at different positions. The optimization is carried out by means of the GA-based function library available in MATLAB©, selecting both single and multiple KPIs as optimization criteria. In this latter case, the advantage is the optimization of more KPIs at the same time, however at the expense of a larger computation time.