面向仓库内货运车的低成本航迹修正定位算法

Localization and track correction algorithm with low cost for freight car in warehouse

为解决现有定位方法成本高、精度低以及存在累计误差等问题,面向仓库内的固定线路货运车辆的低成本、高精度定位需求,提出了融合航位推算(dead reckoning, DR)、运动状态识别以及修正点与传感器信息的车辆定位方法.该方法使用DR算法推算车辆的大致位置,结合运动状态识别技术判断车辆是否位于修正点,再根据修正点信息与传感器数据纠正车辆轨迹.通过仿真模拟低精度惯性传感器采集的数据并进行轨迹追踪.结果表明:所提方法通过在修正点消除累计误差,能够有效提高定位精度,满足无GPS(global positioning system)场合下低精度惯性传感器车辆的定位需求.

To solve the problems of the existing indoor localization methods with high cost, low precision and accumulated error, a vehicle localization method integrating dead reckoning(DR) algorithm, motion state identification and correction points and sensors information was proposed. The DR algorithm was used to calculate the approximate position of the vehicle for detecting the vehicle whether at correction point, and the trajectory was corrected according to the correction point information and sensor data by the motion state recognition technology. The data collected by low precision inertial sensor were simulated, and the trajectory was tracked. The results show that by eliminating the cumulative error at the correction point, the proposed method can effectively improve the localization accuracy and meet the localization needs of vehicles using low-accuracy inertial sensor without global positioning system(GPS).