系统仿真学报 ›› 2016, Vol. 28 ›› Issue (11): 2804-2812.doi: 10.16182/j.issn1004731x.joss.201611023

• 仿真应用工程 • 上一篇    下一篇

基于GMPHD的雷达组网检测跟踪算法研究

赵温波, 丁海龙   

  1. 解放军陆军军官学院,合肥 230031
  • 收稿日期:2015-03-04 修回日期:2015-06-03 出版日期:2016-11-08 发布日期:2020-08-13
  • 作者简介:赵温波(1972-),男,满族,吉林吉林,博士,副教授,硕导,研究方向为数据融合、目标跟踪、统计信号处理。
  • 基金资助:
    国家自然科学基金(61273001),安徽省自然科学基金资助项目(11040606M130)

Study on Track and Detect Algorithm in Radar Networking Based on GMPHD

Zhao Wenbo, Ding Hailong   

  1. Amy Officer Academy of PLA, Hefei 230031, China
  • Received:2015-03-04 Revised:2015-06-03 Online:2016-11-08 Published:2020-08-13

摘要: 将高斯混合概率假设密度算法(Gaussian mixture probability hypothesis density algorithm,GMPHDA)成功应用于多雷达组网跟踪检测弱信噪比多目标,能估计得到所有目标状态与数量,但其跟踪结果是估计值随机集,未与各真实目标分别对应,目前未出现相关完整算法。因此提出对估计航迹进行辨识,包括航迹区分、继续、新生与恢复,给出了一整套航迹辨识算法流程,完善了多雷达组网跟踪检测目标算法。仿真结果表明,能跟踪检测到弱信噪比环境下所有目标,提出的航迹辨识算法能够形成与各真实目标一一对应、逼近的航迹。

关键词: 航迹辨识, 高斯混合概率假设密度滤波, 概率假设密度滤波, 多雷达组网

Abstract: The states and number of WSNR multi-target are tracked accurately by Gaussian mixture probability hypothesis density algorithm (GMPHDA) application. But tracking result is random set of target states, it doesn't correspond one to one with real targets. And the complete algorithm about corresponding has not been proposed. To get target tracks corresponding with real targets, a suite of algorithm about identifying target tracks is proposed, called track identification algorithm, which contains track distinction, continuance, newborn and restoration. The track identification algorithm improves track and detect algorithm in multi-radar networking. Simulation results show that WSNR multi-target is tracked in multi-radar networking, which gets target tracks corresponding one to one with real targets by the proposed identification algorithm.

Key words: track identification, Gaussian mixture probability hypothesis density filter, probability hypothesis density filter, multi-radar networking

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