Dual-Channel Particle Filter Based Track-Before-Detect for Monopulse Radar | Zendy

Fei Cai | Zendy; Hongqi Fan | Zendy; Qiang Fu | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Dual-Channel Particle Filter Based Track-Before-Detect for Monopulse Radar

Author(s) -

Fei Cai,

Hongqi Fan,

Qiang Fu

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/750279

Subject(s) - monopulse radar , particle filter , algorithm , detector , computer science , radar , track before detect , pulse repetition frequency , matched filter , amplitude comparison monopulse , quantization (signal processing) , radar tracker , point target , pulse doppler radar , filter (signal processing) , electronic engineering , engineering , artificial intelligence , computer vision , radar imaging , telecommunications , radar engineering details , synthetic aperture radar

A particle filter based track-before-detect (PF-TBD) algorithm is proposed for the monopulse high pulse repetition frequency (PRF) pulse Doppler radar. The actual measurement model is adopted, in which the range is highly ambiguous and the sum and difference channels exist in parallel. A quantization method is used to approximate the point spread function to reduce the computation load. The detection decisions of the PF-TBD are fed to a binary integrator to further improve the detection performance. Simulation results show that the proposed algorithm can detect and track the low SNR target efficiently. The detection performance is improved significantly for both the single frame and the multiframe detection compared with the classical detector. A performance comparison with the PF-TBD using sum channel only is also supplied

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research