針對一個3 傳感器分布式O S2CFAR 檢測系統, 本文分別使用了基本遺傳算法和改進的遺傳模擬退火算法、小生境遺傳算法進行優化搜索, 給出了一組不同檢測條件下的準最優搜索結果。結果表明, 對于這一優化問題, 遺傳模擬退火算法和小生境遺傳算法都具有較好的適應性, 其中小生境遺傳算法在搜索質量、穩定性和搜索速度上相對更好一些, 是一種較理想的多傳感器分布式O S2CFAR 檢測系統參數優化算法。
關鍵詞: 分布式檢測;O S2CFAR; 遺傳算法; 模擬退火算法; 小生境; 系統優化
Abstract　Fo r a dist ribu ted o rdered stat ist ics (O S) con stan t false alarm (CFAR) detect ion sys2 tem , the search ing of the op t im um detecto r param eters and detect ion perfo rm ance under com2 p licated detect condit ion s is a typ ical non linear op t im izat ion p rob lem. A 32stat ion dist ribu ted O S2CFAR detect ion system is op t im ized by u sing simp le genet ic algo rithm s, genet ic sim u lated annealing algo rithm s and n iche genet ic algo rithm s, respect ively. A set of quasi2op t im um detec2 t ion p robab ility resu lt s of the system under differen t detect condit ion s are given. Resu lt s show that the genet ic sim u lated annealing algo rithm s and n iche genet ic algo rithm s are all su itab le fo r th is op t im izat ion. Among the two algo rithm s, n iche genet ic algo rithm s have bet ter search quality, stab ility and are mo re effect ively, it is an ideal op t im um too l fo r the op t im izat ion of dist ribu ted O S2CFAR detect ion system s.
Key words: dist ribu ted detect ion; O S2CFAR; genet ic algo rithm s; sim u lated annealing algo2
rithm s; n iche; system op t im izat ion