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中文摘要：
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。
英文摘要：
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.
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