摘要
为提高基于到达时间TOA(Time of Arrival)的分布式声源定位系统在应用中的定位精度,推导出各节点测量性能存在差异条件下定位误差的CRLB(Cramer Rao Lower Bound),遵循探测区域定位误差的平均CRLB最小的最优准则,对目标以均匀分布和高斯分布概率出现的情形,采用自适应遗传算法进行最优布局仿真研究.仿真结果表明,基于节点观测性能的最优布局与声源出现的概率分布直接相关;且与不考虑节点性能时的最优布局相比,提高了定位区域的整体定位精度.
In order to improve the localization accuracy of TOA （Time of Arrival） in distributed acoustic source localization system,the CRLB （Cramer Rao Lower Bound） of localization error is deduced by taking the node performance difference into account.The adaptive genetic algorithm is used to study the optimal sensor placement by minimizing the average CRLB when the target is uniform probability distribution and Gauss distribution probability scenario in the field interested.The simulation results show that the optimal sensor placement based on the sensor observation performance is directly related to the probability distribution of sound source in the detection area.
作者
闫青丽
陈建峰
YAN Qing-li;CHEN Jian-feng(School of Marine Science and Technology,Northwestern Polytechnical University,Xi＇an,Shaanxi 710072,China)
出处
《电子学报》
EI
CAS
CSCD
北大核心
2018年第5期1186-1193,共8页
Acta Electronica Sinica
基金
国家自然科学基金(No.61501374)
NSFC-浙江两化融合联合基金(No.U1609204)
关键词
到达时间
最优布局
节点性能
自适应遗传算法
TOA（Time of Arrival）
optimal placement
sensor performance
adaptive genetic algorithm
