带多普勒量测的序贯SCKF雷达目标跟踪算法

发布时间：2018-06-22 15:48

本文选题：雷达目标跟踪 + 序贯滤波　；参考：《电讯技术》2014年12期

【摘要】：为提高非线性观测条件下雷达目标的跟踪性能,将序贯处理方法引入均方根容积卡尔曼滤波(SCKF),提出一种带多普勒量测的序贯均方根容积卡尔曼滤波(SSCKF-D)雷达目标跟踪算法,该算法通过建立伪量测去除径向距离和径向速度量测误差方差之间的相关性。基于SCKF算法,按照量测精确度的高低顺序对方位角、俯仰角、径向距离和伪量测序贯处理。Monte Carlo仿真表明,与SCKF和带多普勒量测的均方根容积卡尔曼滤波(SCKF-D)算法相比,SSCKF-D算法跟踪精度更高,较后者提高20%以上,收敛速度更快,更适用于空间目标跟踪。
[Abstract]:In order to improve the tracking performance of radar targets under nonlinear observation, the sequential processing method is introduced into the root mean square volumetric Kalman filter (SCKF), and a sequential root mean square volume Kalman filter (SSCKF-D) radar target tracking algorithm with Doppler measurements is proposed. The correlation between radial distance and radial velocity measurement error variance is established. Based on SCKF algorithm, azimuth angle, pitch angle, radial distance and pseudo-quantity sequencing are processed according to the order of measurement accuracy. Monte Carlo simulation shows that, Compared with SCKF and root-mean-square volumetric Kalman filter (SCKF-D) with Doppler measurements, the tracking accuracy of SSCKF-D algorithm is higher than that of SCKF-D algorithm. Compared with the latter algorithm, the tracking accuracy of SSCKF-D algorithm is more than 20%, the convergence rate is faster, and it is more suitable for space target tracking.
【作者单位】：海军大连舰艇学院;
【基金】：海军大连舰艇学院2014年科研发展基金项目(2014024)~~
【分类号】：TN953

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