ICCP中单纯形优化的误匹配检测

Mismatching judgment in simplex optimization for ICCP algorithm

在迭代最近等值点ICCP(Iterative Closest Contour Point)算法的地形辅助导航中,利用单纯形优化方法实现对最优航迹的估计,但在匹配中往往得到的只是局部最优解,导致误匹配发生,严重时导致匹配发散.以ICCP算法为研究对象,研究并建立了ICCP方法的误匹配判断准则,以减小误匹配误差的影响和提高匹配精度.利用概率数据关联建立ICCP算法的误匹配判断准则,仿真结果表明,与无误匹配方法匹配结果相比,提高了其收敛性和精度;与M/N方法相比,降低了误匹配概率的30%,提高了导航的精度和算法的稳定性.

Iterative closest contour point （ICCP） algorithm was applied into map aided navigation, in which simplex algorithm was used to estimate the optimal trace of vehicle. However, simplex algorithm was usually convergent at the local optimization so that there was mismatching or even diverging. The rule of mismatching judgment for ICCP was established to reduce mismatching probability. The rule of mismatching judgment for ICCP was established by probability data association filter（PDAF）. Simulation shows that PDAF improves the convergence and precision compared with the ICCP algorithm without mismatching judgment, and its mismatching probability decreases 30 percent compared with M/N method. The PDAF method for mismatching judgment increases precision and stabilization.