Paper
6 November 2006 Neural adaptive Kalman filter's application in MIMU/GPS/MMC integrated navigation systems
Juanjuan Cao, Jiancheng Fang, Wei Sheng
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Abstract
This paper presents a novel method for sensors data fusion based on Neural Adaptive kalman filter. The method is applied in fusing data from MIMU, GPS and Micro magnetism compass integrated navigation system for Micro autonomous Uninhibited Aerial Vehicles (UAV).The noise covariance of kalman filter is modified "online" by the Neural Adaptive Controller in order to modulate kalman filter to be optimal and to improve the positioning, velocity and attitude angle accuracy of the integrated navigation system. To demonstrate the effectiveness and accuracy of this method, an example is outlined. By simulation in the MIMU/GPS/MMC integrated navigation system, it is proved that the Neural Adaptive Kalman Filter has better accuracy than the regular Extended Kalman Filter.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Juanjuan Cao, Jiancheng Fang, and Wei Sheng "Neural adaptive Kalman filter's application in MIMU/GPS/MMC integrated navigation systems", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63574V (6 November 2006); https://doi.org/10.1117/12.717488
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Cited by 1 scholarly publication.
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KEYWORDS
Filtering (signal processing)

Navigation systems

Global Positioning System

Digital filtering

Electronic filtering

Signal to noise ratio

Magnetism

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