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

Krzystof Konopko; Dariusz Janczak

doi:10.1117/12.569069

22 July 2004 Maneuver detection algorithm based on probability density function estimation with use of RBF and HRBF neural network

Krzystof Konopko, Dariusz Janczak

Author Affiliations +

Proceedings Volume 5484, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments II; (2004) https://doi.org/10.1117/12.569069
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments II, 2003, Wilga, Poland

Abstract

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.

Citation Download Citation

Krzystof Konopko and Dariusz Janczak "Maneuver detection algorithm based on probability density function estimation with use of RBF and HRBF neural network", Proc. SPIE 5484, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments II, (22 July 2004); https://doi.org/10.1117/12.569069

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