一种新型的GPS/DR组合定位系统数据融合算法

全球卫星定位系统定位和测速精度高,具有全天候、全球性且基本不受地域、时间限制,但常因为某种原因出现GPS卫星信号丢失情况,航迹推算算法正好能弥补这个问题,将两者结合可以很好地解决定位问题.传统的数据融合算法-卡尔曼滤波算法,在参数选择上要求较高,选择不当即导致较大误差,影响算法效果.建立了GPS/DR组合定位系统的模型,提出了一种新型实用的自适应扩展卡尔曼滤波算法和DR单独定位算法结合的定位算法.通过实际跑车实验,结果表明,较之传统的卡尔曼滤波定位算法,该算法实用性好,而且能很好的满足系统的定位精度及可靠性等方面的要求.

A New Data Fusion Algorithm of GPS/DR Combination Positioning System

GPS has a high precision of navigation and speed measurement,and can provide all-weather and global service without being restricted by location and time.But the signal of GPS is often missed by some reason,DR algorithm can just solve this problem.The combination of these two algorithms can well solve the navigation problem.The classical data fusion algorithm-Kalman algorithm needs a tight choice of the parameters,any improper choice may result in great error and lead to bad effect of the algorithm.In this article,a model of GPS/DR Combination Positioning system is founded,and an adaptive Kalman filtering integrated with single DR positioning algorithm is proposed.The experimental results show that,compared with the classical Kalman filtering algorithm,this algorithm has a good practicality,and can well meet the demand of positioning accuracy and reliability.