基于转换量测容积卡尔曼滤波器带多普勒量测的目标跟踪算法
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1.中科院声学所北海站;2.中科院声学所

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TN953

基金项目:

高速高精度海底地貌测绘技术研究


Converted measurement cubature kalman filter for Doppler-assisted target tracking
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Qingdao Branch of Institute of Acoustics, Chinese Academy of Sciences

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    摘要:

    摘 要:针对带多普勒量测的目标跟踪问题,本文提出了一种基于转换量测容积卡尔曼滤波器的序贯滤波目标跟踪算法。本文首先对具有量测误差相关性的距离和多普勒量测进行解相关处理,构造出新的解相关量测方程,进而基于贝叶斯方法,提出了带多普勒量测的序贯处理算法的统一理论框架,实现了对位置量测和多普勒量测的序贯滤波。在该理论框架下,本文提出了基于转换量测容积卡尔曼滤波器的序贯滤波目标跟踪算法。该算法先采用转换量测容积卡尔曼滤波器和位置量测对目标状态进行估计,再利用经典容积卡尔曼滤波器对新构造的伪多普勒量测进行量测更新以实现目标跟踪。通过对所提出算法的性能分析,证明了该算法具有良好的一致性和收敛性。仿真结果表明,该算法与其他跟踪算法相比,具有更高的跟踪精度。

    Abstract:

    Abstract: In this paper, a new sequential filtering target tracking algorithm based on converted measurement cubature Kalman filter is proposed to solve the problem of Doppler-assisted target tracking. Firstly, a new measurement function was reconstructed by decorrelating the range measurement error with Doppler measurement error, in this paper. Then, based on the Bayesian method, the unified theoretical framework of sequential processing algorithm with Doppler measurement is proposed, and the sequential filtering of range measurement and Doppler measurement is realized. Under this framework, the new sequential filtering target tracking algorithm based on converted measurement cubature Kalman filter is proposed. In this algorithm, the target state is estimated by converted cubature Kalman filter and position measurement, and then the final state estimation is a combination of pseudo-Doppler measurement estimation and the measurement update of classical cubature Kalman filter. By analyzing the performance of the proposed algorithm, it is proved that the algorithm has good consistency and convergency. Simulation results show that this algorithm has higher tracking accuracy than other tracking algorithms. Keywords: converted measurement, Doppler measurement, sequential filtering, consistency, convergency, cubature Kalman filter

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  • 收稿日期:2019-07-24
  • 最后修改日期:2020-11-26
  • 录用日期:2020-02-29
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