Multi-Sensor Fusion Positioning Method Based on Batch Inverse Covariance Intersection and IMM

For mass application positioning demands, the current single sensor cannot provide reliable and accurate positioning. Herein, we present batch inverse covariance intersection (BICI) BICI with interacting multiple model (BICI-IMM) multi-sensor fusion methods, which are based on form of sequential (SICI) method. Meanwhile, it is proved that robust. Compared SICI, BICI-IMM reduces estimation error variance motion has less conservativeness. The algorithm improves accuracy local filtering by models realizes global BICI. validity demonstrated two simulations experiments in open semi-open scenes, its relations shown. In addition, can improve actual scenes.