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Optimal Estimation for the Satellite Attitude using Star Tracker Measurements.

机译:利用星跟踪器测量优化卫星姿态估计。

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An optimal estimation scheme is presented, which determines the satellite attitude using the gyro readings and the star tracker measurements of a commonly used satellite attitude measuring unit. The scheme is mainly based on the exponential Fourier densities that have the desirable closure property under conditioning. By updating a finite and fixed number of parameters, the conditional probability density, which is an exponential Fourier density, is recursively determined. Simulation results indicate that the scheme is effective and robust. It is believed that this approach is applicable to many other attitude measuring units. As no linearization and approximation are necessary in the approach, it is ideal for systems involving high levels of randomness. When a system involves little randomness and linearization is not expected to incur much error, the approach can provide a benchmark against which such suboptimal estimators as the extended Kalman filter and the least-squares estimator can be compared. In this spirit, simulated data for HEAO-A were processed to compare the optimal scheme and the extended Kalman filter. The results are presented. (Author)

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