The rapidity and accuracy of the initial alignment influence the performance of the strapdown inertial navigation system (SINS), compass alignment is one of the most important methods for initial alignment. The selection of the parameters of the compass alignment loop directly affects the result of alignment. Nevertheless, the optimal parameters of the compass loop of different SINS are also different. Traditionally, the alignment parameters are determined by experience and trial-and-error, thus it cannot ensure that the parameters are optimal. In this paper, the Genetic Algorithm-Particle Swarm Optimization (GA-PSO) algorithm is proposed to optimize the compass alignment parameters so as to improve the performance of the initial alignment of strapdown gyrocompass. The experiment results showed that the GA-PSO algorithm can find out the optimal parameters of the compass alignment circuit quickly and accurately and proved the effectiveness of the proposed method.

初始对准的速度和准确性会影响捷联惯性导航系统（SINS）的性能，指南针对准是进行初始对准最重要的方法之一。指南针对准环的参数选择直接影响对准的结果。尽管如此，不同SINS的罗盘循环的最佳参数也不同。传统上，对齐参数是由经验和反复试验确定的，因此无法确保参数是最佳的。本文提出了一种遗传算法-粒子群算法（GA-PSO）来优化罗盘对准参数，以提高捷联陀螺罗盘的初始对准性能。