利用小生境遺傳算法, 對(duì)不同檢測(cè)窗長(zhǎng)度和檢測(cè)信噪比的三傳感器分布式O S2CFAR 檢測(cè)系統(tǒng)進(jìn)行了優(yōu)化設(shè)計(jì), 給出了一組針對(duì)不同檢測(cè)環(huán)境與融合方式的搜索結(jié)果。分析表明, 對(duì)于非一致環(huán)境下分布式O S2CFAR 檢測(cè)系統(tǒng), 小生境遺傳算法是一種良好的優(yōu)化算法。利用搜索結(jié)果, 研究了不同融合方式下環(huán)境變化對(duì)分布式O S2CFAR 檢測(cè)系統(tǒng)的性能影響, 結(jié)果表明,“或”融合對(duì)檢測(cè)環(huán)境的非一致變化具有較強(qiáng)的魯棒性, 而“3 選2”融合和“與”融合對(duì)檢測(cè)環(huán)境的變化比較敏感。
關(guān)鍵詞: 遺傳算法; 小生境; 非一致環(huán)境; 分布式恒虛警檢測(cè); 數(shù)據(jù)融合
Abstract: In th is paper, niche genet ic algo rithm s are used to op t im ize the perfo rmance of a dist ributed 32sen2 so r O S2CFAR detect ion system w ith different reference length s and signal2to2no ise rat io s. A set of quasi2op2 t imum results is given and analyzed, w h ich p roves that niche genet ic algo rithm s are efficient fo r th is op t im iza2 t ion. The influences of the nonident ity in environment on the perfo rmance of the dist ributedO S2CFAR detec2
to r fo r different fusion rules are discussed subsequent ly. The results indicate that w hen OR fusion is em2 p loyed, the system is robust to the nonident ical variety of detect ion environment, w h ile 2 of 3 and AND fu2 sion are sensit ive in the same situat ion.
Key words: genet ic algo rithm s; niche; nonident ical environments; dist ributed CFAR detect ion; data fusion