A Robust Fusion Algorithm for Sensor Failure

Accurate multimodal and multisensor detection of a target phenomenon requires knowledge of probabilistic sensor characteristics to determine an appropriate fusion rule which optimizes an objective of interest, traditionally the expected Bayesian risk. However, a particular sensor characteristic can change online, introducing unaccounted additional risk to the fusion rule that was based on assumed sensor specifications. To mitigate such changes, we propose a sensor-failure-robust fusion rule assuming that only first order characteristics of a probabilistic sensor failure model are known. Under this failure model, we compute the expected Bayesian risk and minimize this risk to develop the proposed fusion method.