基于高斯和滤波的高轨双星高超音速目标跟踪

doi:10.3969/j.issn.1006-2475.2017.10.018

计算机与现代化

基于高斯和滤波的高轨双星高超音速目标跟踪

1.江南大学物联网工程学院，江苏无锡214122；
2.江南大学轻工过程先进控制教育部重点实验室，江苏无锡214122；
3.国防科学技术大学电子科学与工程学院，湖南长沙410073

收稿日期:2017-03-07 出版日期:2017-10-30 发布日期:2017-10-31
作者简介:曹亚琴(1992-),女,江苏南通人, 江南大学物联网工程学院、江南大学轻工过程先进控制教育部重点实验室硕士研究生,研究方向：定位跟踪算法；通信作者：秦宁宁(1980-),女,副教授,研究方向：传感器网络，网络性能评估；杨乐(1979-),男,副教授,研究方向：检测与估计理论，无源定位跟踪；李曦(1990-),男, 国防科学技术大学电子科学与工程学院博士研究生,研究方向：估计理论，定位跟踪。
基金资助:
国家自然科学基金青年基金资助项目（61304264, 61305017）；江苏省“六大人才高峰”第十一批高层次人才项目(DZXX-026)； 2016年度“江苏省博士后科研资助计划”项目（1601012A）；中央高校基本科研业务费专项资金资助项目（JUSRP1509XNG）

Gaussian Sum-based Filtering for Hypersonic Object Tracking from Two Geosynchronous Satellites

1. School of Internet of Things (IoT) Engineering, Jiangnan University, Wuxi 214122, China;

2. Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education, Jiangnan University, Wuxi 214122, China;
3. School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China

Received:2017-03-07 Online:2017-10-30 Published:2017-10-31

摘要/Abstract

摘要： 针对基于高轨双星时频差观测的无源跟踪问题，提出一种适用于跟踪高超音速巡航目标GMM-AEKF算法，该算法使用基于Euler采样建立的WGS-84椭球下的目标离散时间运动方程，在已有的GMM-EKF跟踪框架的基础上引入时差均匀高斯混合（GMM）表示、替代扩展卡尔曼滤波（AEKF）和基于Kullback-Leibler散度的高斯分量管理。仿真实验结果表明，AEKF的引入使得跟踪算法的状态更新运算变为线性，其估计精度收敛速度较快，适用于高超音速目标跟踪。

关键词: 高斯和滤波, 替代扩展卡尔曼滤波, 时频差, 欧拉采样, Kullback-Leibler散度

Abstract: This paper considers tracking a cruising hypersonic object with known altitude using the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements obtained at two geosynchronous satellites. A new tracking algorithm, referred to as GMM-AEKF, is proposed. The algorithm utilizes a discrete-time process equation under the WGS-84 ellipsoidal Earth model, which is established through discretizing the continuous-time equation of target motion with Euler sampling. GMM-AEKF generalizes the existing GMM-EKF algorithm in the sense that it implicitly takes into account the object moving along the earth surface with known altitude. It also includes a new method that can yield a more uniform GMM representation of the TDOA measurement, the alternative extended Kalman filter (AEKF) for FDOA track update, and a Kullback-Leibler (KL) divergence-based Gaussian component management scheme. Simulation results reveal that with the use of AEKF, TDOA and FDOA track updates of GMM-AEKF are the same as the state update of standard linear Kalman filter (KF). GMM-AEKF is also shown to be able to converge faster, which makes it more suitable for hypersonic object tracking other state-of-art benchmarks.

Key words: Gaussian sum-based filtering, alternative extended Kalman filter, TDOA and FDOA, Euler sampling, Kullback-Leibler divergence

曹亚琴 1,2，秦宁宁 1,2，杨乐 1,2，李曦 3. 基于高斯和滤波的高轨双星高超音速目标跟踪[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2017.10.018.

CAO Ya-qin 1,2, QIN Ning-ning 1,2, YANG Le 1,2, LI Xi 3.

Gaussian Sum-based Filtering for Hypersonic Object Tracking from Two Geosynchronous Satellites

[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.10.018.

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基于高斯和滤波的高轨双星高超音速目标跟踪

Gaussian Sum-based Filtering for Hypersonic Object Tracking from Two Geosynchronous Satellites

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