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针对航天器姿态确定中的非线性非高斯的滤波问题,提出一种基于遗传算法的粒子滤波的航天器姿态估计方法。该方法将姿态四元数作为采样粒子进行粒子滤波,并将小生境遗传算法(NGA)引入粒子滤波算法中,以改善粒子滤波的性能;用遗传算法单独进行陀螺偏差估计,以减少粒子滤波的状态维数。该姿态估计方法保持了四元数的归一化性质,通过引入小生境遗传算法解决了重采样阶段的粒子退化问题,并且由于单独估计陀螺偏差避免了粒子滤波状态的扩展。该方法能够在较少粒子的情况下实现高效率高精度的定姿,仿真结果说明了方法的有效性。
Aiming at the problem of nonlinear non-Gaussian filter in spacecraft attitude determination, a genetic algorithm-based particle filter attitude estimation method is proposed. In the method, the quaternion of pose is used as the particle filter, and the niche genetic algorithm (NGA) is introduced into the particle filter to improve the performance of the particle filter. The genetic algorithm is used to separate the gyro bias to reduce the particle filter Status dimension. The attitude estimation method preserves the normalization property of quaternions. The niche genetic algorithm is introduced to solve the problem of particle degeneracy in the resampling stage, and the particle filter state is avoided due to the gyro bias estimation alone. The method can achieve high-efficiency and high-accuracy pose with fewer particles, and the simulation results show the effectiveness of the method.