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

fYear

2008

fDate

1-8 June 2008

Firstpage

2371

Lastpage

2376

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);

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on

Conference_Location

Hong Kong

ISSN

1098-7576

Print_ISBN

978-1-4244-1820-6

Electronic_ISBN

1098-7576

Type

conf

DOI

10.1109/IJCNN.2008.4634127

Filename

4634127