粒子群优化算法在传递对准中的应用

给出了一种基于粒子群优化算法的捷联惯导传递对准算法。简单分析了传递对准任务要求和主子惯导惯性器件输出之间的关系,将传递对准问题作为参数优化问题进行求解,给出了基于粒子群优化算法进行传递对准的数学模型。定义了传递对准的优化目标函数,介绍了粒子群优化算法及其应用于传递对准的具体算法设置。用粒子群优化算法求解目标函数的最小值,可获得主子惯导之间的失准角,进行一次校正即可完成传递对准过程。通过计算机仿真对算法进行了验证分析,在仿真条件下（陀螺精度为0.1°/h）,能达到方位0.1°的精度。与其他对准算法一样,算法受载体机动条件的影响较大,一般需要姿态机动来提高陀螺的信噪比。

Application of particle swarm optimization algorithm in transfer alignment

A PSO(particle swarm optimization) algorithm-based transfer alignment method is presented. The transfer alignment requirement and the relation between the master inertial sensors and slave inertial sensors are analyzed. The transfer alignment problem is treated as a parameter optimization problem, and the PSO algorithm-based alignment mathematics model is given. The transfer alignment optimization function is defined, and the PSO algorithm is introduced. The PSO algorithm is employed to search the global minima, then the misalignment can be estimated. The algorithm is validated by simulation. The heading error can be <0.1° under the simulation condition that the gyro's accuracy is 0.1 (°)/h. The algorithm is greatly affected by the maneuver as other alignment methods. Attitude maneuver is usually needed to increase the gyro's signal-to-noise rate.