编队行驶系统中基于Kalman滤波的相对定位算法研究

Research on relative location algorithm based on Kalman filter in formation driving system

编队行驶系统中车辆之间需要时刻保持安全的距离,基于绝对坐标定位计算两相邻车辆之间的距离时延较大,输出结果不够准确可靠.为了改善这一缺点,根据雷达的TOA测距原理,采用了一种不依赖绝对坐标的相对定位方法,能够快速计算出两相邻车辆之间的距离.为了保证测量结果的精度,采用了Kalman滤波算法降低了噪声的影响.仿真结果验证了该系统能够有效地减小测量误差,仿真数据对比分析表明,采用Kalman滤波后与滤波前相比,测量误差可以减小约37.82%,显著提高了测量精度.

In formation driving system,vehicles need keeping safe distance at all times.The time delay of calculating the distance between two adjacent vehicles based on absolute coordinate positioning is large,and the output result is not accurate and reliable.In order to improve this shortcoming,according to the principle of radar TOA ranging,the author adopts a relative positioning method that does not depend on absolute coordinates,which can quickly calculate the distance between two adjacent vehicles.To ensure the accuracy of measurement results,Kalman filtering algorithm is used to reduce the influence of noise.The simulation results verify that the system can effectively reduce the measurement error.The comparison and analysis of simulation data show that the measurement error can be reduced by about 37.82%after Kalman filtering compared with before filtering,and the measurement accuracy can be significantly improved.