An improved multi-filter fusion indoor localization algorithm based on INS and UWB

With the increasing demand for indoor services based on location information, the importance of achieving accurate indoor positioning has become increasingly prominent. However, wireless sensor networks (WSNs) are impacted by non-line-of-sight (NLOS) transmissions when transmitting signals, resulting in decreased positioning accuracy. In contrast, The Inertial Navigation System (INS) operates independently without relying on external data, its positioning results are not affected by NLOS transmission, but it has the problem of error accumulation caused by integration. A joint positioning method combining INS and Ultra-wide band (UWB) is advanced to decrease the influence of NLOS error. When locating target nodes in UWB, an improved fuzzy clustering algorithm is employed to minimize the influence of NLOS transmission. Finally, the Multi-Filter Fusion method is used to fuse the positioning results of INS and UWB to obtain high-precision and robust position information. Simulation and experimental results show that the proposed algorithm owns better performance compared with existing algorithms.