基于扩展卡尔曼滤波的车位智能定位方法

Research on Intelligent Parking Location Based on Extended Kalman Filter

为了解决当前车位自动定位过程中存在的定位误差大,定位效率低等难题,以获得更优的车位自动定位结果,提出基于扩展卡尔曼滤波的车位智能定位方法。首先对车位定位的相关信息进行采集,并对信息进行一定的预处理,去除其中一些无用信息,然后引入扩展卡尔曼滤波算法计算车位的位置和角度偏移情况,并根据结果进行车位智能定位,最后与其他车位智能定位方法进行了对比测试,结果表明,相对于其他车位智能定位方法,扩展卡尔曼滤波算法可以提升车位智能定位精度,不仅减少了车位智能定位误差,而且缩短了车位智能定位时间,可以更快实现车位智能定位。

In order to solve the problems of large positioning error and low positioning efficiency in the current parking space automatic positioning process,and obtain better parking space automatic positioning results,this paper proposes an intelligent parking space positioning method based on extended Kalman filter.Firstly,the relevant information of parking location is collected and preprocessed to remove some useless information.Then,the extended Kalman filter algorithm is introduced to calculate the position and angle offset of parking space,and the intelligent positioning of parking space is carried out according to the results.Finally,it is compared with other intelligent positioning methods,and the results show that the proposed method is more effective.The extended Kalman filter algorithm can improve the parking intelligent positioning accuracy,reduce the parking intelligent positioning error,and shorten the parking intelligent positioning time,can realize the parking intelligent positioning faster.