A clustering localization algorithm with adaptive threshold in passive sensor network

被引：0
|
作者：
He Y. [1 ]
Wang B.-C. [1 ]
Wang G.-H. [1 ]
Xiu J.-J. [1 ]
机构：
[1] Institute of Information Fusion, Naval Aeronautical and Astronautical University
来源：
Yuhang Xuebao/Journal of Astronautics | 2010年 / 31卷 / 04期
关键词：
Clustering; DQ; Localization; Sensor network; Threshold;
D O I：
10.3873/j.issn.1000-1328.2010.04.030
中图分类号：
学科分类号：
摘要：
With the help of a sensor network which is fixed on the ground, a clustering localization algorithm with adaptive threshold based on Data Quality (DQ) analyzing is presented in order to enhance localization precision in a jamming scenario. Taking full advantage of sensor network and DQ analysis, estimated positions of target can be obtained from sensors' measurements firstly, and the DQ of each position is scaled according to the Distance Square Sum method. Secondly, a testing statistics is constructed from which the DQ of certain estimated positions' center is scaled by means of adjusting the clustering threshold adaptively, and the threshold is relative with the number of estimated positions. Finally, the sort of high quality positions is confirmed and the target position can be obtained. By eliminating the possible influence produced by low quality data, the presented algorithm can improve localization precision effectively in comparison with the MMSE algorithm. Simulation results verify the clustering localization algorithm based on DQ analysis presented in this paper.
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页码：1125 / 1130
页数：5
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