Maneuver detection algorithm based on probability density function estimation with use of RBF and HRBF neural network

被引：0
|
作者：
Konopko, K [1 ]
Janczak, D [1 ]
机构：
[1] Bialystok Tech Univ, Fac Elect Engn, PL-15351 Bialystok, Poland
来源：
PHOTONICS APPLICATIONS IN ASTRONOMY, COMMUNICATIONS, INDUSTRY, AND HIGH-ENERGY PHYSICS EXPERIMENTS II | 2004年 / 5484卷
关键词：
maneuvering target tracking; maneuver detection; pdf estimation; RBF neural network;
D O I：
10.1117/12.569069
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
The paper presents a new maneuver detection algorithm used in variable state dimension estimator. The proposed method is based on statistical test of two hypothesis which checks probability density function of innovation process of a tracking filter. The neural networks with radial and hyperradial basis functions are applied as probability density function and distribution function estimators. The results of numerical simulations are presented. The presented approach is also suitable for fault detection and diagnosis in dynamical systems.
引用
收藏
页码：625 / 629
页数：5
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