针对可见光成像定位中目标位置估计所涉及的高维空间搜索收敛慢的问题, 引入降维设计思想, 联合惯导单元(IMU)的瞬时姿态估计, 将搜索空间缩小到带约束特征的样本空间, 据此提出一种联合目标瞬时姿态估计的高维空间搜索方法。该方法以瞬时姿态信息特征构建目标寻优函数作为约束条件, 缩小遗传算法中个体优秀基因的进化范围, 显著提高了进化速度, 同时规避了对初始样本空间的依赖性, 提高了算法的鲁棒性。仿真结果表明, 算法的位置估计均方误差优于40 mm。

As for slow convergence in high-dimensional space of object positioning estimation, a dimension reduction design idea is introduced, combined with instantaneous attitude estimation of inertial units, which reduces the search space to sample space with constrained features. Accordingly, a high-dimensional space search method of joint target instantaneous attitude estimation is put forward. The method takes instantaneous attitude information characteristics to build object optimization function as constraint condition, and reduces the evolution scope of individual good genes in genetic algorithm, which improves the evolution speed significantly, avoids the dependence on the initial sample space at the same time, and increases the robustness of algorithm. Simulation results show that with the same parameters, the mean square error of positioning estimation is no more than 40 mm.