Radar waveform design based on improved particle swarm optimization algorithm

Wanhan Li; Xiaoming Liu

doi:10.1117/12.2673899

6 April 2023 Radar waveform design based on improved particle swarm optimization algorithm

Wanhan Li, Xiaoming Liu

Proceedings Volume 12615, International Conference on Signal Processing and Communication Technology (SPCT 2022); 1261523 (2023) https://doi.org/10.1117/12.2673899
Event: International Conference on Signal Processing and Communication Technology (SPCT 2022), 2022, Harbin, China

Abstract

It is a nonlinear programming problem to solve the radar waveform design model of maximum mutual information under the condition of limited signal to clutter ratio. The complex solving process of particle swarm optimization - sequential quadratic programming algorithm leads to a large increase in the time consumed to solve the model and poor real-time performance. To solve the above problems, this paper adopts an adaptive strategy to update the speed and position of particle swarm optimization algorithm, and dynamically adjusts the inertia weight and learning factor to solve the problems of falling into local optimal and slow convergence. The experimental results show that the improved particle swarm optimization algorithm, while retaining the efficiency of the original algorithm, has faster convergence, higher mutual information, stronger robustness and reduces the time spent in solving the model in the process of solving the optimal radar signal waveform, thus achieving the purpose of improving the performance of radar system target detection, estimation and tracking.

Citation Download Citation

Wanhan Li and Xiaoming Liu "Radar waveform design based on improved particle swarm optimization algorithm", Proc. SPIE 12615, International Conference on Signal Processing and Communication Technology (SPCT 2022), 1261523 (6 April 2023); https://doi.org/10.1117/12.2673899

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