Research on Boost-Phase Ballistic Missile Tracking Algorithm Using EM

XUE Gao-ru; LIANG Yan; QIAO Ping; YANG Liu-qing

doi:10.3969/j.issn.0372-2112.2017.07.030

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Research on Boost-Phase Ballistic Missile Tracking Algorithm Using EM

更新时间：2025-07-16

- Research on Boost-Phase Ballistic Missile Tracking Algorithm Using EM
- Acta Electronica Sinica Vol. 45, Issue 7, Pages: 1770-1774(2017)
- 作者机构：
  
  西北工业大学自动化学院,陕西,西安,710072
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61135001, No.61374023);Postgraduate Innovation Seed Funding of Northwestern Polytechnical University (No.Z2016141)
- DOI：10.3969/j.issn.0372-2112.2017.07.030
  CLC： V19
- Published Online：25 July 2017，
  
  Published：2017
- 稿件说明：
移动端阅览
XUE Gao-ru, LIANG Yan, QIAO Ping, et al. Research on Boost-Phase Ballistic Missile Tracking Algorithm Using EM[J]. Acta Electronica Sinica, 2017, 45(7): 1770-1774.
DOI：

XUE Gao-ru, LIANG Yan, QIAO Ping, et al. Research on Boost-Phase Ballistic Missile Tracking Algorithm Using EM[J]. Acta Electronica Sinica, 2017, 45(7): 1770-1774. DOI： 10.3969/j.issn.0372-2112.2017.07.030.

摘要

为了提高未知弹道参数下主动段目标跟踪的精度，提出基于期望最大化（Expectation Maximization，EM）的联合优化算法框架.首先在E步基于平滑器得到状态和未知参数的后验估计，然后在M步计算初始状态的均值、协方差以及过程噪声协方差等未知统计量，最后推导出基于URTS（Unscented Rauch-Tung-Striebel）的EM算法，并给出未知统计量的最优解析解，避免了非凸优化难以求解的问题.仿真结果表明：在相同量级的计算量下，本文算法的状态估计精度优于迭代UKF（Unscented Kalman Filter）算法.

Abstract

In this paper

framework of joint optimization algorithm based on EM (Expectation Maximization) is proposed for tracking a boost-phase ballistic target with unknown ballistic parameters.Firstly

the state and unknown parameters are estimated based on smoother in the E step.Then the mean and covariance of initial states

and the noise covariances are calculated in the M step.At last

URTS (Unscented Rauch-Tung-Striebel) based on EM is derived and the analytical forms of unknown statistics parameters are given

which makes the non-convex numerical optimization unnecessary.The result shows that the proposed algorithm is more accurate than iterative UKF (Unscented Kalman Filter) with the same order of magnitude of calculation.

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