针对星敏感器光学误差两步法标定局部寻优能力强, 但标定结果受初值影响大的问题, 基于粒子群算法, 提出一种改进的星敏感器光学误差参数标定方法。该方法首先利用粒子群算法全局搜索能力强的优点, 为光学误差的两步法标定提供一组次优的初值条件, 然后将其代入两步法中, 得到标定值。仿真结果表明: 该方法能够有效解决两步法标定受初值条件影响大的不足, 并能够提高标定结果的稳定性。

Aiming at the problem that the calibration result of two-step calibration method for star sensor optical error depends on the initial value too much, a modified calibration method was proposed based on particle swarm optimization (PSO) algorithm. Taking advantage of the global searching ability of PSO algorithm, a set of suboptimal initial value for two-step calibration of optical errors was provided via optimization. In sequence, the two-step calibration method was utilized to obtain the final calibration result. Numerical simulations demonstrate the effectiveness of the proposed method in overcoming the shortages that two-step calibration method is heavily influenced by initial values as well as the improvement of the stability of the calibration.