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A UKF algorithm with two arrays in bearings-only tracking

机译:仅方位角跟踪中具有两个数组的UKF算法

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One condition of the target's maneuver is coordinated type turning motion, with the characteristic that the size of the angular velocity and the velocity stay the same, while the direction of the velocity varies from time to time. It is a special kind of maneuver. This turning motion of target is actually a part of the uniform circular motion. In response to this situation, we assume that the motion model of the target is the uniform circular motion. In this case, to ensure the observability in passive target tracking, we propose bearings-only unscented kalman filtering (UKF) algorithm with two arrays to locate and track the target. In this paper, we propose UKF algorithm with two arrays to do passive tracking and compare with extended kalman filtering (EKF) algorithm. Simulation results show that bearings-only UKF algorithm with two arrays has faster convergence and better tracking accuracy than EKF algorithm.
机译:目标机动的一种条件是协调型转向运动,其特征在于角速度的大小和速度保持不变,而速度的方向则不时变化。这是一种特殊的机动。目标的这种旋转运动实际上是匀速圆周运动的一部分。针对这种情况,我们假设目标的运动模型是匀速圆周运动。在这种情况下,为了确保在被动目标跟踪中具有可观察性,我们提出了带有两个阵列的纯方位无味卡尔曼滤波(UKF)算法来定位和跟踪目标。在本文中,我们提出了具有两个阵列的UKF算法进行被动跟踪​​,并与扩展卡尔曼滤波(EKF)算法进行了比较。仿真结果表明,与EKF算法相比,仅带两个阵列的UKF算法具有更快的收敛速度和更好的跟踪精度。

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