| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 710221 | IFAC Proceedings Volumes | 2009 | 4 Pages |
Abstract
AbstractIn 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.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Shady M.K. Mohamed, Prof. Saeid Nahavandi,