An efficient fault-tolerant sensor fusion algorithm for accelerometers

Accelerometers are vital parts of many industrial and biomedical applications. Such applications have high demands for accuracy. Multi-sensor fusion is an efficient approach to deliver accurate sensor readouts that are tolerant to multiple faults. This paper proposes an efficient data fusion algorithm, which minimizes Mean-Square-Error (MSE) and keeps the overall precision of the system high. We make use of a convex optimization scheme to tackle the problem. Furthermore, a pre-processing step called screening is used to exclude the potentially faulty sensors from the data fusion. The screening process makes it possible to quickly detect multiple faulty sensors. Our data fusion approach is applicable to any multi-sensor system, for which the post-calibration statistical characteristics of sensors can be measured experimentally. However, the results are presented for accelerometers.