Neural Network Algorithm for Installation Error Identification Based on Bearing-only Target Motion Analyses

被引：0
|
作者：
Wen, Lin [1 ]
Liu, Zhong [1 ]
Luo, Ya-song [1 ]
Fu, Xue-zhi [1 ]
机构：
[1] Naval Univ Engn, Elect Engn Coll, Wuhan 430033, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 1, PROCEEDINGS | 2009年 / 5551卷
关键词：
Unmanned aerial vehicle; Photo-electricity device; Neural network; Installation error identification;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
It is quite strict with the degree of installation precision of photo-electricity device (PED) carried by unmanned aerial vehicle (UAV) when conducting bearing-only target motion analyses (BTMA), because of the existence of the installation error of PED, the precision of target location is bound to be affected. In order to solve this problem mentioned above, a neural network algorithm for installation error identification based oil BTMA is put forward in this paper, consulting the target surveillance technology of PED to identify the installation error thought neural network algorithm, which is worthy to be put into practical applications.
引用
收藏
页码：893 / 900
页数：8
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