Polarized light/MIMU integrated navigation SHKF attitude solving algorithm for motion acceleration suppression

The study examines the accurate establishment of an attitude angle calculation model for UAVs influenced by large motion accelerations. Accelerometer output shows a decreased proportion of effective gravity acceleration information，while polarization sensors exhibit jitter. First，polarization sensor integrated navigation was introduced，along with the orientation principle of polarization navigation. Then，a cascaded attitude solution algorithm was built using the double-vector Gauss-Newton method and the SHKF（Sage-Husa Kalman）algorithm. This algorithm observed UAV attitude information based on multiple sensors. Next，based on analyzing the accuracy of accelerometer measurements under motion acceleration，a trust factor was proposed to mitigate the impact of motion acceleration on attitude calculation. This algorithm could suppress the effects of motion acceleration generated by high-speed UAV bodies. To verify this algorithm's feasibility，experiments were conducted on a polarization/MIMU （Micro Inertial Measurement Unit） integrated navigation platform. Results indicate a 30% improvement over PI and EKF algorithms in static and dynamic environments. The algorithm suppressed attitude deviation caused by non-gravity acceleration under motion acceleration influence. It improved the accuracy of attitude calculation under motion acceleration，ensuring normal UAV flight. © 2024 Chinese Academy of Sciences. All rights reserved.