基于核密度估计的极短弧定轨的分布估计方法

Estimation of Distribution Algorithm for Initial Orbit Determination of Too-short-arc Based on Kernel Density Estimation

采用分布估计算法,通过建立解空间的概率模型,实现了一种测角资料的极短弧初轨计算方法.在概率模型建立中,采用非参数核密度估计,无需对分布进行任何假设.不同于遗传算法、粒子群算法等进化算法,方法不仅考虑解的适值优劣,同时考虑了解的整体特性.根据基于实测数据的数值计算表明:方法在没有任何约束条件情况下对于一般观测精度仍可获得有效解.

A new approach of the initial orbit determination for too-short-arc with angular measurements is implemented by building the probabilistic model in the so- lution space with the estimation of distribution algorithm. Without any assumption of distribution, the non-parametric kernel density estimation is employed in the model building. The method, unlike other evolutionary algorithms, such as genetic algorith- m and particle swarm optimization, considers the fitness as well as the characteristic of solution space. Numerical check with real observations indicates that without any constraints, the proposed technique has a good performance for the measurements of general accuracy.