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模糊灰色聚类评估方法在导航滤波中的应用
徐照钱, 赵方方, 陈翠桥
电子科技大学计算机学院 机器人研究中心, 成都 611731
摘要:
目前针对深空探测导航中滤波算法的综合评估的方法种类繁多,但是仍然有较多评估方法由于其单一性,存在或多或少的问题。提出了一套反映滤波算法优劣程度的评估指标体系,并为其建立相应的数学模型。深空探测器采样点数据通过该数学模型计算后,由模糊灰色聚类方法进行综合评估。该方法是以灰色系统理论为基础,结合模糊综合评估方法所建立的评估模型。该模型可以摒弃二者单一使用时的缺点,提升评估结果的准确性。评估结果表明,此评估模型能够对滤波算法进行比较准确、合理、全面的评估。
关键词:  滤波算法;模糊灰色聚类;综合评估;深空探测
DOI:10.15982/j.issn.2095-7777.2017.04.0011
分类号:
基金项目:国家重点基础研究发展计划资助项目(2014CB744206);上海市深空探测技术重点实验室开放课题(DS201504-001)
Application of Fuzzy Grey Clustering Evaluation Method in Navigation Filter
XU Zhaoqian, ZHAO Fangfang, CHEN Cuiqiao
China Robotics Institute, School of Computer University of Electronic Science and Technology, Chengdu 611731, China
Abstract:
At present, there are many kinds of methods for the comprehensive evaluation of filtering algorithms in deep space exploration, but most of them have problems more or less because of their singleness. In this case, a set of index system that reflects the degree of the filtering algorithm was put forward,and the corresponding mathematical model for the algorithm was established. The data of deep space probe sampling points were calculated by the model, and then synthetically evaluated by the fuzzy grey clustering method. The proposed evaluation model combines the grey system theory with the fuzzy comprehensive evaluation method. The model overcomes the shortcomings when the two methods are used seperately, and improves the accuracy of the evaluation results. The evaluation results show that the evaluation model is more accurate, and reasonable, which can evaluate the filtering algorithm comprehensively.
Key words:  filtering algorithm;fuzzy grey clustering;comprehensive evaluation;deep space exploration