Joint Optimization of Signal Waveforms and Filters for Long-Range MIMO Radars

Abstract

This paper describes a new cyclic algorithm for minimization of signal sidelobes and crosstalk in multiple-input multiple-output (MIMO) radar. The designed algorithm, called SWAP by the authors, is suitable mainly for long-range radars, such as ground-based surveillance, approach, or weather radar. The minimization of energy or amplitude of side lobes, and crosstalk were used as the optimization criteria. The effect of the Doppler shift is also included in the optimization. Although the optimized signals do not maintain a strictly constant envelope, the peak-to-average power ratio (PAR) can be maintained below 1.7. This value is acceptable, especially for radars with modern transmitters based on GaN HEMTs. The algorithm allows for any arbitrary choice of elements weights, enabling the optimization of calculations for a wide range of applications. This paper also presents the results of algorithm testing under various conditions. The designed algorithm makes it possible to suppress the side lobes and crosstalk by up to 20 dB more than the matched filters. These results were achieved at the cost of a slight deterioration in signal-to-noise ratio (SNR) loss (less than 1 dB) and an increase in PAR (up to 2). The resolution of weak close targets is also slightly deteriorated. The algorithm converged quickly, and already after ten or 20 iterations, the results changed only minimally.