Optimal linear data fusion for systems with missing measurements
Mohamed, Shady M.K. and Nahavandi, Saeid 2009, Optimal linear data fusion for systems with missing measurements, in ICONS 2009 : Proceedings of The 2nd IFAC International Conference on Intelligent Control and Signal Processing, International Federation of Automatic Control, Laxenburg, Austria, pp. 1-4.
In this paper, we provide the optimal data fusion filter for linear systems suffering from possible missing measurements. The noise covariance in the observation process is allowed to be singular which requires the use of generalized inverse. The data fusion process is made on the raw data provided by two sensors observing the same entity. Each of the sensors is losing the measurements in its own data loss rate. The data fusion filter is provided in a recursive form for ease of implementation in real-world applications.
Field of Research
090699 Electrical and Electronic Engineering not elsewhere classified