摘要
为了解决迭代最近点算法的定位精度和实时性问题,提出了一种基于混沌优化搜索的迭代最近点算法。在该算法中,以参考导航系统测量位置为中心规划真实位置的搜索范围,从参考地形图上提取相应的地形高程数据,与对应经纬度位置一起定义成模式类,将模式识别的过程转化成函数优化问题,然后运用混沌优化算法搜索目标函数最小值进行全局寻优,从而获得匹配最近点。仿真结果表明,在保证寻优性能的情况下,可以减少匹配次数,提高识别速度,满足地形匹配精度和实时性的要求。
In order to solve the problem of positioning accuracy and real-time, an iterative closest point algorithm based on chaos optimization was proposed. In the algorithm, a searching area of real position was plotted centering on the indication of the refer navigation system, and then the terrain altitude data was extracted from the reference terrain map. These terrain data, along with corresponding latitude and longitude position, were defined as several patterns. The patterns are transformed to the function optimization problem, which search the minimum value of object function by chaotic optimization algorithm in order to acquire optimal match point. The simulation results prove that the number of match may be reduced, the identification may be accelerated, and requirements to terrain matching system are satisfied under the circumstances of ensuring optimizing performances.
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2009年第2期156-158,164,共4页
Journal of Chinese Inertial Technology
基金
国家自然科学基金项目(60874092)
国家自然科学基金项目(50575042)
总装备部预研项目(51309060402)
总装备部预研项目(51309020503)
原国防科工委基础科研项目(C1420080224)
教育部博士点专项科研基金项目(20050286026)
