（南京航空航天大學計算機科學與技術學院，江蘇南京 210016）

 

摘 要：針對MCB移動定位算法在實時信息采樣方面的不足，本文提出了EMCB（Enhanced Monte-Carlo localization boxed）定位算法。該算法在MCB基礎之上，引入遺傳算法中的變異和交叉操作，使樣本向后驗密度值較大的區域轉移，有效地克服原算法存在的成功采樣率較低的問題。仿真實驗結果表明，本文算法同MCB算法相比，平均采樣數減少了約30%，定位精度提高了約17%。      

關鍵字：無線傳感器網絡；移動定位；蒙特卡洛；遺傳算法(GA)

Ruiheng Zhang, Yi Zhuang

(College Of Computer Science and Technology, NanJing University Of Aeronautics and Astronautics, NanJing 210016, China)

Abstract: In view of low real-time sampling efficiency of Monte-Carlo localization boxed, a new localization method named Enhanced Monte-Carlo localization boxed is proposed. Based on MCB, EMCB introduces the crossover and mutation operations in GA, in order to make samples move towards regions with large value of posterior density distribution. So the problem of low sampling efficiency is solved. Simulation results show that compared with MCB, the localization accuracy of the EMCB is improved by about 17%, while the cost is reduced by about 30%.

Key words: Wireless Sensor Network; Mobile Localization; Monte Carlo; GA

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作者簡介：

張銳恒，男，1987年生，碩士研究生，就讀于南京航空航天大學計算機應用技術專業，研究領域為無線傳感器定位。