中南大学学报（自然科学版）Issue(2)：503-507,5.DOI:10.11817/j.issn.1672-7207.2016.02.021
基于自适应迭代UKF的纯距离目标定位算法
Range-only target location algorithm based on adaptive IUKF
摘要
Abstract
Since the iterated unscented Kalman filter(IUKF ) has the problem of setting iterative times , according to the fitness function from genetic algorithm, an adaptive iterated unscented Kalman filter(AIUKF) was proposed. The new algorithm calculated the fitness of the predicted values and the observed values, the fitness of the sampling points and the observed values, then adaptive adjust whether iteration or not based on the ratio of fitness functions. The simulation results indicate that the AIUKF has better performance than standard UKF in range-only target motion analysis, and can solve the problem of setting iterative times in IUKF.关键词
迭代测量更新/IUKF算法/遗传算法/适应度函数/自适应/纯距离/UKF算法Key words
iterated measurement update/iterated unscented Kalman filter (IUKF)/genetic algorithm/fitness function/adaptive/range-only/unscented Kalman filter (UKF)分类
信息技术与安全科学引用本文复制引用
王璐,刘忠..基于自适应迭代UKF的纯距离目标定位算法[J].中南大学学报（自然科学版）,2016,(2):503-507,5.基金项目
总装预研基金资助项目(9140A01060113JB11001)(Project (9140A01060113JB11001) supported by GAD advanced Research Found) （9140A01060113JB11001）
