An Estimation Method of Satellite Interference Moment Based on Augmented Kalman Filter

Abstract

The invention discloses a method for estimating satellite interference moment based on augmented Kalman filtering, which includes the following steps: S1, extracting the satellite flywheel rotational speed and the satellite inertial angular velocity measured by the gyroscope within one orbit period in the steady state from the satellite in-orbit data, and using the flywheel The rotation speed is converted into flywheel angular momentum, and the flywheel angular momentum is numerically differentiated to obtain the approximate value of the flywheel output torque; S2, the approximate value of the flywheel output torque and the satellite inertial angular velocity measured by the gyroscope are used as the input of the Kalman filter, and the satellite is subjected to the environment in orbit The disturbance torque is regarded as a state quantity, and the state update equation and measurement equation of the augmented system are established to obtain the Kalman filter algorithm of the environmental disturbance torque; S3, the Kalman filter is performed on the augmented system to obtain the estimated value of the environmental disturbance torque, and the The estimated value of the environmental disturbance moment mentioned above is added to the satellite attitude controller as the feed-forward signal of the satellite control system.

Description

technical field [0001] The invention relates to an optimal estimation technology of external interference moment received by satellites, in particular to a method for estimating satellite interference moment based on augmented Kalman filtering. Background technique [0002] Kalman filtering is one of the most commonly used algorithms in information fusion algorithms, and it is mainly used for real-time fusion of dynamic multi-sensor redundant data. The main point is to correct the uncertainty of the model by means of measurement, overcome the discreteness of measurement with the continuity of the model, and suppress the uncertainty of the model with the certainty of measurement. When the state equation and the measurement equation of the system are both linear and the system noise and sensor measurement noise are both Gaussian white noise, the application of the classical Kalman filter algorithm can provide the only statistically optimal estimate for the fused data. After t...

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Problems solved by technology

[0004] New space missions put forward higher requirements on the control accuracy of satellites. However, due to the influence of large-scale low-frequency flexible accessories on the current star, as well as the performance limitations of attitude measurement sensors and attitude control actuators, the bandwidth of satellite attitude controllers cannot be too large. High, which in turn restricts the anti-interference ability of the system

Since the ground cannot accurately model the external disturbance torque on the satellite, if only the disturbance torque model established on the ground is used to apply the feedforward signal to the controller, the accurate compensation for the disturbance cannot be realized, so the feedforward information has a great impact on the control accuracy. The improvement is not ideal

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