Attitude estimation method of maneuvering acceleration-assisted extended Kalman filter (EKF) attitude and heading reference system (AHRS)

Abstract

The invention provides an attitude estimation method of a maneuvering acceleration-assisted extended Kalman filter (EKF) attitude and heading reference system (AHRS). The state quantity of the EKF contains an error of three attitude angles, a null bias error of a three-axis gyroscope and a three-axis carrier maneuvering acceleration error of a carrier system, and the observed quantity of the EKF contains a three-axis acceleration error and a three-axis earth magnetic field error. A strapdown attitude algorithm and the nine-state EKF algorithm are subjected to data fusion to acquire attitude estimation of the AHRS. A single-axis turntable experiment, a vehicle-mounted dynamic experiment and a flight experiment prove that the maneuvering acceleration-assisted nine-state EKF data fusion algorithm has stable attitude angle accuracy under different maneuvering conditions, and the mean square deviation of the attitude angle can be limited within 2 degrees.

Description

technical field [0001] The invention relates to a strapdown inertial attitude system attitude estimation technology, in particular to a nine-state extended Kalman filter attitude estimation method utilizing carrier maneuvering acceleration assistance. Background technique [0002] Due to the limited gyro accuracy of the open-loop IFOG heading and attitude system, after initialization, only relying on the traditional strapdown algorithm, the attitude will quickly diverge, and the information of the accelerometer and magnetic compass needs to be used for correction. Existing methods are more effective when the carrier is maneuverable, but when applied to UAVs, helicopters and other carriers, due to the long maneuvering time and the requirement that the attitude can still maintain high accuracy, the influence of the maneuvering acceleration of the carrier itself cannot Eliminate, so that more accurate pitch angle and roll angle estimation cannot be obtained according to the acc...

AI Technical Summary

Problems solved by technology

Existing methods are more effective when the carrier is maneuverable, but when applied to UAVs, helicopters and other carriers, due to the long maneuvering time and the requirement that the attitude can still maintain high accuracy, the influence of the maneuvering acceleration of the carrier itself cannot Eliminate, so that the accurate pitch angle and roll angle estimation cannot be obtained according to the accelerometer information, and the heading angle information cannot be accurately estimated according to the magne

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