Adaptable sensor fusion using multiple Kalman filters

This paper presents an integrated sensor fusion strategy for the positioning of an underwater ROV. The use of multiple Kalman filters makes the system highly adaptable by allowing different combinations of sensors without any modification of the models. This algorithm can handle any number of redundant sensors by using multi-filter fusion and can work asynchronously with different sensor data rates through a filter switching process