Title :
A threshold factor approach method for CFAR detector based on stochastic particle swarm optimization
Author :
Liu, Panzhi ; Han, Chongzhao ; Jie, Jing
Author_Institution :
Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ., Xian
Abstract :
Based on the perfect properties of stochastic particle swarm optimization (SPSO), such as the property of robust and quick convergence, a new scheme is applied to estimate scaling factor for radar constant false alarm rate (CFAR) detectors. Owing to few constraints, it can estimate scaling factor for single radar as well as radar netting system. The numerical results indicate that the particle swarm optimizer has been found to be accuracy and fast in searching the threshold factor T of CFAR detector under any designed probability of false alarm.
Keywords :
particle swarm optimisation; radar detection; stochastic processes; CFAR detector; radar constant false alarm rate detector; radar netting system; scaling factor; stochastic particle swarm optimization; threshold factor approach; Detectors; Monte Carlo methods; Numerical simulation; Particle swarm optimization; Probability density function; Radar clutter; Radar detection; Robustness; Stochastic processes; Testing; CFAR detector; Scaling factor; stochastic particle swarm optimization (SPSO);
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4634127
