EKF算法在机动模型中的应用研究

Application of EKF algorithm in mechanical model

针对大多数情况下,对目标机动的先验知识了解很少,且目标在机动过程中受人为作用力的影响,很难用数学公式准确描述,只能在各种假设条件下用近似方法描述该问题,因此假设了一种机动目标模型:初始匀速直线阶段、匀速圆周运动阶段、返回匀速直线阶段,在此过程中线速度大小v保持不变。利用扩展卡尔曼(extended kalmanfilter,EKF)滤波算法进行定位跟踪,仿真结果表明,该假设模型既符合机动实际,又便于数学处理,并且滤波算法过程稳定,具有较快的收敛速度和较高的定位精度,提高了机动目标跟踪的精度和系统的实时性。

In most cases, the knowledge of objective dynamic is little known and the object is influenced by man-made factors in the course of maneuver, so it＇s hard to give an accurate description via any mathematic formula. This paper proposes a maneuver target model： the initial phase of the uniform linear, uniform circular motion stage, returning to uniform linear stage, and the size of the line speed v remaining unchanged in this process. The extended Kalman filter （EKF） was used to track position, and simulation results show that the model is in line with the actual motor and easy to deal with the mathematics. The algorithm is stable and has rapid convergence rate and high positioning accuracy to improve the accuracy of the mobile target tracking and real-time system.