卡尔曼滤波在无人水面艇双天线GPS定位测向系统中的应用

Application of Kalman Filter in Dual Antenna GPS Positioning System of Unmanned Surface Vessel

摘要:

针对无人水面艇双天线GPS定位测向系统的定位误差问题,利用卡尔曼滤波算法对GPS数据进行滤波处理；根据位置与速度及航向的关系,建立数学模型,然后利用卡尔曼滤波算法对定位测向系统的测量值进行滤波处理；首先,对无人水面艇在静止、低速及高速运动状态的GPS数据进行了处理；仿真结果表明,在这三种情况下卡尔曼滤波方法能够提高GPS定位精度,在定点实验中观测值的均方误差为0.5259,滤波后变为0.0536；最后,在干扰情况下的无人艇运动仿真实验中,经过卡尔曼滤波后测量数据的均方误差由0.5043降低为0.3553；实验说明卡尔曼滤波能获得很好的滤波效果。

Abstract:

In order to improve the accuracy of the USV’s (unmanned surface vessel) dual antenna GPS positioning system, the Kalman Filter was used to deal with the GPS data. According to the relationship of position ,speed and heading, this paper sets up a mathematical model, then the Kalman Filter is used to process GPS data. First the USV is simulated in the case of still water ,low and high speed. The experiment show that the Kalman filter can achieve the desired result. For example, the mean square error is reduced from 0.5259 to 0.0536 in the case of still water. At last in the case of the disturbance, the experimental results show that the Kalman Filter can also improve the positioning accuracy and significantly reduced the mean square error from 0.5043 to 0.3553. The experiments illustrate that Kalman filter can get a desired effect.