MPOS联邦实时组合算法

Micro position and orientation system (MPOS) is a key device to provide real-time and high-precision motion compensation information for imaging loads, and its measurement accuracy severely restricts the improvement of imaging accuracy. Aiming at MPOS real-time integrated filtering algorithm, based on dual-ARM (advanced RISC machines) hardware platform, this paper adopts federated filtering real-time integrated method to achieve optimal information fusion of multiple groups of sensor data. Micro inertial measurement unit is the common reference system, double antenna global navigation satellite system(GNSS) and magnetometer are the measuring information of subsystem. The local error covariance and state estimation obtained by each subsystem are fused in the main filter to obtain the optimal estimation value. The MPOS system based on real-time federated filtering integration method is verified by dynamic experiments. The accuracy of position, speed, heading and horizontal attitude can reach 0.6 m, 0.03 m/s, 0.15° and 0.04°.