Study on particle swarm optimization (PSO) for aircraft parameter identification based on BeiDou satellite system and strapdown AHRS integrated navigation

Low-precision integrated navigation system of strapdown AHRS and BeiDou Satelite has poor adaptability in some cases. And the system module accuracy as well as noise statistics varies with the actual working conditions. To address these two issues, this paper presents a secondary heading and attitude computation method with the velocity information output by Air Data System (ADS). The algorithm, based on PSO for the parameter identification, estimates and revises the parameters of observation module, consequently achieves optimal estimation of heading and attitude. Although a vertical take-off and landing (VTOL) aircraft is a typical non-linear and underactuated system, the result show that, this algorithm can identify system parameters efficiently, even in the case of noises. The algorithm has important application value.