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光纤陀螺惯导系统在进行空间自主导航时,需要经历长期复杂的空间环境,这会使惯性仪表的某些性能发生变化,光纤陀螺仪的光功率下降是一种比较典型的失效模式,这会导致光纤陀螺仪的带宽下降,当航天器进行变轨或姿态机动时其导航精度会降低。针对上述问题,文中提出了微粒群优化的光纤陀螺仪动态补偿方法,根据光纤陀螺仪和参考模型在相同输入下的响应,优化得到补偿环节的参数。但微粒群算法存在过早陷入局部最优解的缺陷,为提高算法的全局搜索能力,采用模拟退火算法使其以较大的概率跳出局部最优解。通过光纤陀螺导航系统的动态导航试验验证了该方法能够有效地补偿光纤陀螺仪的动态特性,提高机动条件下的导航精度,具有较强的工程实用价值。
The FOGs’ inertial navigation system needs long-term and complex space environment for autonomous navigation, which will change certain properties of inertial instruments. The optical power reduction of fiber optic gyroscope is a typical failure mode. As a result, the bandwidth of the fiber optic gyroscope decreases. As the spacecraft moves in orbit, its navigation accuracy decreases. In order to solve the above problems, the paper proposes a particle swarm optimization algorithm for fiber optic gyroscope dynamic compensation. According to the response of fiber optic gyroscope and reference model under the same input, the parameters of the compensated links are optimized. However, the PSO has some defects such as premature falling into the local optimal solution. In order to improve the global search ability of the algorithm, the simulated annealing algorithm is used to jump out of the local optimal solution with a large probability. The dynamic navigation test of FOG navigation system verifies that this method can effectively compensate the dynamic characteristics of fiber optic gyro and improve the navigation accuracy under maneuvering conditions, which has strong engineering practical value.