科研之友
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摘要
Satellite motion included in gyro output disturbs the estimation of Allan variance coefficients of fiber optic gyro on board. Moreover, as a standard method for noise analysis of fiber optic gyro, Allan variance has too large offline computational effort and data storages to be applied to online estimation. In addition, with the development of deep space exploration, it is urged that satellite requires more autonomy including autonomous fault diagnosis and reconfiguration. To overcome the barriers and meet satellite autonomy, we present a new autonomous method for estimation of Allan variance coefficients including rate ramp, rate random walk, bias instability, angular random walk and quantization noise coefficients. In the method, we calculate differences between angle increments of star sensor and gyro to remove satellite motion from gyro output, and propose a state-space model using nonlinear adaptive filter technique for quantities previously measured from offline data techniques such as the Allan variance method. Simulations show the method correctly estimates Allan variance coefficients, R = 2.7965exp - 4 degrees/h(2), K = 1.1714exp - 3 degrees/h(1.5), B = 1.3185exp - 3 degrees/h, N = 5.982exp - 4 degrees/h(0.5) and Q = 5.197exp - 7 degrees in real time, and tracks degradation of gyro performance from initail values, R = 0.651 degrees/h(2), K = 0.801 degrees/h(1.5), B = 0.385 degrees/h, N = 0.0874 degrees/h(0.5) and Q = 8.085exp - 5 degrees, to final estimations, R = 9.548 degrees/h(2), K = 9.524 degrees/h(1.5), B = 2.234 degrees/h, N = 0.5594 degrees/h(0.5) and Q = 5.113exp - 4 degrees, due to gamma radiation in space. The technique proposed here effectively isolates satellite motion, and requires no data storage and any supports from the ground.
- 出版日期2011-9
- 单位北京航空航天大学
