IMM Kalman滤波前馈补偿技术在搜索跟踪系统中的应用
作者:
作者单位:

(1. 中国科学院西安光学精密机械研究所,西安710119;2. 中国科学院大学,北京100049)

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E-mail: lindi@opt.ac.cn.

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TP273

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Implementation of IMM Kalman filtering feed-forward compensation technology in search and track systems
Author:
Affiliation:

(1. Xián Institute of Optics and Precision Mechanics,Chinese Academy of Sciences,Xián 710119,China;2. University of Chinese Academy of Sciences,Beijing 100049,China)

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    摘要:

    空中低慢小目标存在机动和角速率运动较大的情况,对地面搜索跟踪系统的跟踪精度提出很高要求,为了提高跟踪系统的跟踪精度,需加入伺服前馈补偿技术,精确的目标速度和加速度估计成为前馈补偿控制的难点.鉴于此,提出采用IMM卡尔曼滤波技术估计目标运动速度和加速度信息,并作为伺服前馈补偿的输入量,以消除由于目标速度和加速度运动引起的脱靶量误差.实际系统测试实验表明,搜索跟踪系统采用IMM卡尔曼滤波前馈补偿技术使得系统跟踪精度较常规卡尔曼滤波补偿提高3倍以上,模型验证有效.

    Abstract:

    The UAV has large maneuver and angular velocity motions, which puts high requirments on the servo tracking accuracy of the ground search and tracking system. In order to improve the tracking accuracy of the ground search and tracking system, servo feed-forward compensation technology is often added. Accurate target velocity and acceleration estimation becomes the difficulty of feed-forward compensation control. IMM Kalman filtering is used to estimate the velocity and acceleration information of the target, and it is used as the input of servo feed-forward compensation system to eliminate the miss distance error caused by the velocity and acceleration of the target. The actual system test results show that the tracking accuracy of the search and tracking system is more than three times higher than that of the conventional Kalman filter compensation by using the IMM Kalman filter feed-forward compensation technology, and the model verification is effective.

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引用本文

林俤,吴易明,朱帆. IMM Kalman滤波前馈补偿技术在搜索跟踪系统中的应用[J].控制与决策,2020,35(5):1253-1258

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  • 在线发布日期: 2020-03-25
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