杂波环境下基于粒子滤波的微弱扩展目标检测前跟踪算法

吴孙勇; 薛秋条; 朱圣棋; 闫青竹; 孙希延

doi:10.12000/JR16128

杂波环境下基于粒子滤波的微弱扩展目标检测前跟踪算法

DOI: 10.12000/JR16128

吴孙勇^①,②,,
薛秋条^①, ,,
朱圣棋^③,
闫青竹^①,
孙希延^②

①.
桂林电子科技大学数学与计算科学学院桂林 541004
②.
广西精密导航技术与应用重点实验室桂林 541004
③.
西安电子科技大学雷达信号处理重点实验室西安 710071

基金项目: 国家自然科学基金项目(61261033, 61561016, 61362005)，广西自然科学基金资助项目(2014GXNSFAA118352, 2014GXNSFBA118280, 2016GXNSFAA380073)，广西精密导航技术与应用重点实验室开放基金项目(DH201502)，广西密码学与信息安全重点实验室研究课题(GCIS201611)

详细信息

作者简介:
吴孙勇(1981–)，男，广西桂林人，博士，现为桂林电子科技大学数学与计算科学学院副教授，研究方向为雷达信号处理、随机有限集、粒子滤波。E-mail: wusunyong121991@163.com

薛秋条(1978–)，女，河南灵宝人，现为桂林电子科技大学数学与计算科学学院讲师，研究方向为微弱目标检测，随机有限集、粒子滤波。E-mail: 475561774@qq.com

通讯作者:
薛秋条 475561774@qq.com

中图分类号: TP391
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- 被引次数: 0
出版历程
- 收稿日期: 2016-11-18
- 修回日期: 2017-01-26
- 网络出版日期: 2017-06-28

Track-Before-Detect Algorithm for Weak Extended Target Based on Particle Filter under Clutter Environment

Wu Sunyong^{①,②
,},
Xue Qiutiao^{①
, ,},
Zhu Shengqi^③,
Yan Qingzhu^①,
Sun Xiyan^②

①.
School of Computational Science and Mathematics, Guilin University of Electronic Technology, Guilin 541004, China
②.
Guangxi Key Laboratory of Precision Navigation Technology and Application, Guilin 541004, China
③.
National Lab of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds: The National Natural Science Foundation of China (61261033, 61561016, 61362005), The Natural Science Foundation of Guangxi (2014GXNSFAA118352, 2014GXNSFBA118280, 2016GXNSFAA380073), Guangxi Key Laboratory of Precision Navigation Technology and Application (DH201502), Guangxi Key Laboratory of Cryptography and Information Security (GCIS201611)

摘要

摘要: 针对杂波环境下微弱扩展目标的实时检测和跟踪问题，该文提出一种基于粒子滤波的检测前跟踪(TBD)算法。该算法以杆状物体作为研究对象，通过划分距离和方位上的单元格，提出了不同区域内含有Weibull杂波的量测模型。在TBD框架下，将二进制目标存在变量和目标形状参数加入到状态向量中，通过抽样得到散射点集合，并利用粒子滤波实现杂波环境下对扩展目标状态和形状参数的检测和估计。仿真实验表明，该算法具有较好的稳定性。
- 杂波 /
- Weibull分布 /
- 粒子滤波 /
- 检测前跟踪 /
- 扩展目标
Abstract: The Track-Before-Detect (TBD) algorithm based on the particle filter is proposed for weak extended target detection and tracking in low signal to clutter noise radio. The rod-shaped object is analyzed by dividing the cell on range and azimuth under the Weibull clutter. On the basis of a point target, the likelihood function and particle weights can be obtained by the target spread function. In the TBD algorithm, the binary target variable and the target shape parameters is added to the state vector and the scattering points in the sample collection is given based on the particle filter, which can detect and estimate the target state and the shape parameters under the clutter environment. Simulation results show that the stability of the algorithm is very good.
- Clutter /
- Weibull distribution /
- Particle filter /
- Track-Before-Detect (TBD) /
- Extended target

HTML全文

图 1 目标散射点

Figure 1. Target scatter point

下载: 全尺寸图片幻灯片

图 2 扩展目标真实航迹图

Figure 2. Real track of extended target

下载: 全尺寸图片幻灯片

图 3 目标的平均存在概率

Figure 3. Average existence probability of target

下载: 全尺寸图片幻灯片

图 4 目标位置的RMSE

Figure 4. RMSE of target position

下载: 全尺寸图片幻灯片

图 5 目标长度的RMSE

Figure 5. RMSE of target length

下载: 全尺寸图片幻灯片

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