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Maneuvering Acceleration Estimation Algorithm Using Doppler Radar Measurement

机译：多普勒雷达测量的机动加速度估计算法

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摘要

An algorithm to estimate the tangential and normal accelerations directly using the Doppler radar measurement in an online closed loop form is proposed. Specific works are as follows: first, the tangential acceleration and normal acceleration are taken as the state variables to establish a linear state transition equation; secondly, the decorrelation unbiased conversion measurement Kalman filter (DUCMKF) algorithm is proposed to deal with the strongly nonlinear measurement equation; thirdly, the geometric relationship between the range rate and the velocity direction angle is used to obtain two estimators of the velocity direction angle; finally, the interactive multiple model (IMM) algorithm is used to fuse the estimators of the velocity direction angle and then the adaptive IMM of current statistical model based DUCMKF (AIMM-CS-DUCMKF) is proposed. The simulation experiment results show that the accuracy and stability of DUCMKF are better than the sequential extended Kalman filter algorithm, the sequential unscented Kalman filter algorithm, and converted measurement Kalman filter algorithms; on the other hand they show that the AIMM-CS-DUCMKF can obtain the high accuracy of the tangential and normal accelerations estimation algorithm.
机译：提出了一种在线闭环形式的多普勒雷达测量直接估计切向和法向加速度的算法。具体工作如下：首先，以切向加速度和法向加速度为状态变量，建立线性状态转移方程。其次，提出了去相关无偏转换测量卡尔曼滤波器（DUCMKF）算法来处理强非线性测量方程。第三，利用测距率与速度方向角之间的几何关系得到两个速度方向角估计量。最后，采用交互式多模型（IMM）算法融合速度方向角的估计量，然后提出了基于当前统计模型的DUCMKF（AIMM-CS-DUCMKF）自适应IMM。仿真实验结果表明，DUCMKF算法的精度和稳定性优于顺序扩展卡尔曼滤波算法，顺序无味卡尔曼滤波算法和转换测量卡尔曼滤波算法。另一方面，它们表明AIMM-CS-DUCMKF可以获得切向和法向加速度估计算法的高精度。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第6期|4984186.1-4984186.13|共13页
  • 作者

    Liu Hongqiang; Zhou Zhongliang; Yu Lei;

  • 作者单位

    Air Force Engn Univ, Aeronaut & Astronaut Engn Coll, Xian, Shaanxi, Peoples R China;

    Air Force Engn Univ, Aeronaut & Astronaut Engn Coll, Xian, Shaanxi, Peoples R China;

    Air Force Engn Univ, Aeronaut & Astronaut Engn Coll, Xian, Shaanxi, Peoples R China;

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  • 入库时间 2022-08-18 04:07:39

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