基于时间序列分析的动态精确定位算法

对卫星导航定位系统的应用前景进行深入分析，针对目前存在定位精度漂移和站点报站漏报或司机人工操作繁琐与复杂等问题，采用求解平均值、均方差和估计值等数理统计理论，建立基于时间序列分析的动态精确定位数学模型，进行动态求解，精确定位，并利用扁平多叉树动态向二叉树转换的自动站点匹配模型设计了比较优化可靠的算法，保证匹配算法的复杂度为O（n），减少计算资源的占用，提高数据处理的实时性；且通过实时的GPS数据采集进行实际反复验证，能满足定位精度和智能自动报站的时间与位置要求，实际测试结果证明该算法性能稳定、运行可靠，且应用范围广阔。

Dynamic Precision Orientation Algorithm Based on Time Sequence Analysis

The paper analyzes the application prospect about the satellite guided navigation position system.In order to disposing of the problems on position precision drift,and omitting speech stations,or complexity of operation,a mathematical statistics theory on computing average value,including mean square error(MSE) value and estimate value,is utilized.It constructs a dynamic precision orientation mathematic model based on time sequence analysis,including dynamic resolve and precision position.At the same time,an automatic station match model from thin and flat variance tree to a binary tree is utilized to design an optimize reliable algorithm,its complexity degree is O(n),which has been tested and verified by a group evidence globe position system(GPS) data repeatedly.The algorithm can be satisfied the requirements on time and position of precision position and intelligent automatic speech station.The practice test result proves that the algorithm is stable and reliable,and it can be applied wide-ranging.