基于kalman滤波的智能小车GPS轨迹跟踪  

Application of Kalman Filter in GPS Trajectory Tracking for Smart Car

作　　者：孙成正 SUN Cheng-zheng(Dept. of Information Institute University of Science and Technology of China, Anhui Hefei 230026;Dept. of Yun Gui Information Institute Anhui Finance and Trade Vocational College, Anhui Hefei 230061, China)

机构地区：[1]中国科学技术大学信息学院,安徽合肥230026 [2]安徽财贸职业学院云桂信息学院,安徽合肥230601

出　　处：《佳木斯大学学报（自然科学版）》2018年第6期867-871,共5页Journal of Jiamusi University：Natural Science Edition

基　　金：2017高校优秀青年骨干人才国内访学(gxfx2017166);安徽财贸职业学院科学研究基金资助项目(2017nhzra01);2017安徽省高等学校自然科学研究重点项目(KJ2017A859)

摘　　要：在满足线性高斯模型下,kalman滤波能够对目标状态进行最优化估计并能得到理想的跟踪效果。GPS导航卫星中信号被人为加入了高频振荡随机干扰信号后,可看成是GPS定位的观测噪声,会对卫星信号产生较高频率的抖动,从而影响智能小车轨迹跟踪的精度。通过建立系统状态方程,在matlab环境下建立仿真模型,对GPS轨迹跟踪中小车速度及位置的观测信号进行了kalman滤波,结果显示Kalman滤波比较明显地降低了干扰噪声的影响,提升了智能小车GPS跟踪的稳定性。Kalman filter can make the optimal estimation to the state of the target and also get a better tracking effect,under the condition of linear Gauss model.In the GPS system,the high frequency random disturbance signal added can be considered as the observation noise of GPS location,resulting in all satellite signals to produce high frequency jitter,which influence the precision of track tracking in smart car.By establishing the system state equation and building simulation model in Matlab environment,the Kalman filter is needed to observe the position and velocity of the GPS.The results show that the Kalman filter can obviously reduce the influence of interference noise and improve the stability of GPS tracking in smart car.

关 键 词：KALMAN滤波 智能小车 GPS定位 

分 类 号：G715[文化科学—职业技术教育学]