基于IRWQS与模糊特征的位置预测算法

Position Prediction Algorithm Based on IRWQS and Fuzzy Features

针对现有二维位置预测算法难以反映地势因素给预测准确度带来的影响,提出一种基于IRWQS(Incremental Repetition Weighing Queue Strategy)与模糊特征相结合的位置预测方法。首先,将从北斗卫星导航系统获取的三维位置坐标信息进行提取转换后存入数据库,再利用数据库的链式操作进行在线增量式重复加权队列扫描运算;其次,通过模糊特征匹配算法获取最优的位置坐标,并得出较为准确的下一运动位置坐标点以及运动趋势。实验结果表明,相比MMTS算法和UCMBS算法,所提算法的预测准确率分别平均提高约9%和25%。

In view of the fact that the existing two-dimensional position prediction algorithm is difficult to reflect the influence of terrain factors on prediction accuracy,this paper proposed a position prediction algorithm based on IRWQS（Incremental Repetition Weighing Queue Strategy）and fuzzy feature.Firstly,the three-dimensional position coordinate information obtained from the Plough satellite navigation system is extracted and converted into a database,and then the online incremental weighting queue scan operation is performed by using the chained operation of the database.Secondly,the optimal position coordinates are obtained through the fuzzy feature matching algorithm to get the coordinate points and movement trends of the next moving position exactly.The experimental results show that compared with MMTS algorithm and UCMBS algorithm,the prediction accuracy of this algorithm increases by about 9% and 25% on average.