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基于协议同步水下传感器网络目标协同定位算法
引用本文:王彪,李宇,黄海宁.基于协议同步水下传感器网络目标协同定位算法[J].系统仿真学报,2010(9).
作者姓名:王彪  李宇  黄海宁
作者单位:1. 中国科学院声学所,北京100190;江苏科技大学,镇江212003
2. 中国科学院声学所,北京100190;
3. 江苏科技大学,镇江,212003
摘    要:为了解决水下目标的定位问题,讨论了一种基于水下传感器阵列网络的目标协同定位算法。该算法在实现水下节点同步的基础上,通过建立目标位置与距离差测量值的统计模型后依据最大似然准则完成目标定位。定位算法的实现采用分布-集中相结合的处理方法,在提高定位精度的同时大大节省了水下节点通信能耗。通过仿真实验验证了算法的有效性和可行性,实验结果表明该方法具有较好的同步及目标定位精度。
Abstract:
A collaborative target location algorithm for underwater acoustic sensor networks (UASN) was proposed. The algorithm was achieved based on time synchronization for high transmitting delay for UASN. Target location was estimated by maximum-likelihood methods based on proposed statistical model which was established by the relation between target position and measured range difference. The proposed algorithm adopts the distributed-centralized computation methods,which degrade the transmitting energy comparing with traditional centralized methods. The result of simulation shows the application validity and the more location performance of the algorithm.

关 键 词:水下声传感器网  时间同步  目标定位  最大似然估计

Target Collaborative Localization Based on Protocol Synchronization in Underwater Acoustic Sensor Networks
WANG Biao,HUANG Hai-ning,LI Yu.Target Collaborative Localization Based on Protocol Synchronization in Underwater Acoustic Sensor Networks[J].Journal of System Simulation,2010(9).
Authors:WANG Biao  HUANG Hai-ning  LI Yu
Abstract:A collaborative target location algorithm for underwater acoustic sensor networks (UASN) was proposed. The algorithm was achieved based on time synchronization for high transmitting delay for UASN. Target location was estimated by maximum-likelihood methods based on proposed statistical model which was established by the relation between target position and measured range difference. The proposed algorithm adopts the distributed-centralized computation methods,which degrade the transmitting energy comparing with traditional centralized methods. The result of simulation shows the application validity and the more location performance of the algorithm.
Keywords:underwater acoustic sensor networks  time synchronization  source location  ML
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