Open AccessA Robust Space-time Adaptive Processing Algorithm based on Particle Swarm Optimization for Non-stationary Clutter Suppression
Author(s) -
Hanchao Wang,
Lili Fang,
Chuanfang Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1802/3/032145
Subject(s) - clutter , particle swarm optimization , algorithm , constant false alarm rate , computer science , space time adaptive processing , mathematical optimization , function (biology) , process (computing) , control theory (sociology) , mathematics , radar , artificial intelligence , continuous wave radar , telecommunications , control (management) , radar imaging , evolutionary biology , biology , operating system
A novel robust sparse recovery (SR) space-time adaptive processing (STAP) algorithm based on particle swarm optimization (PSO) for non-stationary clutter suppression is presented in this paper. A cost function for PSO in the presence of parameter errors is theoretically derived. An improved estimation process of clutter spectrum based on this cost function which is called PSO-SR is proposed and analyzed. A more accurate estimation result of clutter spectrum could be provided by this algorithm than the previous proposed algorithms in the presence of considerable parameter errors. Simulation results demonstrate the robust performance of this algorithm.