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一种双重积累自反馈优化的三维多目标检测前跟踪算法

薄钧天 张嘉毫 王国宏 于洪波 张翔宇 王万田 王衡峰

薄钧天, 张嘉毫, 王国宏, 于洪波, 张翔宇, 王万田, 王衡峰. 一种双重积累自反馈优化的三维多目标检测前跟踪算法[J]. 电子与信息学报. doi: 10.11999/JEIT240057
引用本文: 薄钧天, 张嘉毫, 王国宏, 于洪波, 张翔宇, 王万田, 王衡峰. 一种双重积累自反馈优化的三维多目标检测前跟踪算法[J]. 电子与信息学报. doi: 10.11999/JEIT240057
BO Juntian, ZHANG Jiahao, WANG Guohong, YU Hongbo, ZHANG Xiangyu, WANG Wantian, WANG Hengfeng. A 3D Multi Targets Track before Detect Algorithm with Self-feedback Optimization of Dual Accumulation[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240057
Citation: BO Juntian, ZHANG Jiahao, WANG Guohong, YU Hongbo, ZHANG Xiangyu, WANG Wantian, WANG Hengfeng. A 3D Multi Targets Track before Detect Algorithm with Self-feedback Optimization of Dual Accumulation[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240057

一种双重积累自反馈优化的三维多目标检测前跟踪算法

doi: 10.11999/JEIT240057
基金项目: 国家杰出青年科学基金(52025072),中国科协青年人才托举工程项目(2021-JCJQ-QT-009),国家自然科学基金(62271498),山东省自然科学基金面上项目(ZR2020MF015, ZR2020QF010)
详细信息
    作者简介:

    薄钧天:男,博士生,研究方向为抗干扰技术,目标检测与跟踪等

    张嘉毫:男,副教授,研究方向为抗干扰技术,天线设计技术等

    王国宏:男,教授,研究方向为目标检测与跟踪、信息融合与雷达组网等

    于洪波:男,副教授,研究方向为信息融合技术、信号与信息处理等

    张翔宇:男,讲师,研究方向为信息融合技术、目标检测与跟踪等

    王万田:男,讲师,研究方向为雷达抗干扰技术、目标检测与识别等

    王衡峰:男,讲师,研究方向为阵列信号处理、雷达抗干扰技术等

    通讯作者:

    张嘉毫 jiahao.z@hotmail.com

  • 中图分类号: TN957

A 3D Multi Targets Track before Detect Algorithm with Self-feedback Optimization of Dual Accumulation

Funds: The National Fund for Distinguished Young Scholars (52025072), The Young Elite Scientists Sponsorship Program by CAST (2021-JCJQ-QT-009), The National Natural Science Foundation of China (62271498), Shandong Provincial Natural Science Foundation, China (ZR2020MF015, ZR2020QF010)
  • 摘要: 针对3维微弱多目标检测问题,该文提出一种双重积累自反馈优化的3级平行线坐标变换(PT)检测前跟踪(TBD)算法。通过将平行线坐标变换引入至TBD技术,依次在规格化的径向距离-时间、方位角-时间和俯仰角-时间平面对量测点进行投影变换和双重非相参积累,同时利用功率累积结果反馈优化二值积累,有效缓解强目标淹没弱目标和编队目标串扰问题。仿真结果表明,当整体信杂比达到10 dB时,所提算法的全局检测概率接近80%,证明了该算法的有效性。
  • 图  1  优化积累结果

    图  2  3级检测结果

    图  3  最终检测结果

    图  4  不同目标检测概率

    图  5  不同目标数目检测概率

    表  1  目标参数

    序号 初始位置(km) 初始速度(m/s) 加速度(m/s2) RCS(m2) 信杂比(dB)
    1 $ \left({15,25},{5}\right) $ $\left( {{{180, - 20,5}}} \right)$ $\left( {{{0,0,0}}} \right)$ ${{0}}{{.2}}$ ${{10}}{{.2}}$
    2 $ \left({13,18},{7}{.5}\right) $ $\left( {{{180, - 200, - 10}}} \right)$ $\left( {{{2,1}}{{.5,0}}} \right)$ ${{0}}{{.15}}$ ${{13}}{{.2}}$
    3 $ \left({25,17},{4}\right) $ $\left( {{{ - 30,200,12}}} \right)$ $\left( {{{ - 1,3,0}}} \right)$ ${{0}}{{.2}}$ ${{9}}{{.6}}$
    4 $ \left({18,19}{.5},{6}\right) $ $\left( {{{200,180,0}}} \right)$ $ \left( {{{0,0,0}}} \right) $ ${{0}}{{.1}}$ ${{8}}{{.5}}$
    5 $ \left({18,20},{6}\right) $ $\left( {{{200,180,0}}} \right)$ $\left( {{{0,0,0}}} \right)$ ${{0}}{{.1}}$ ${{8}}{{.0}}$
    6 $ \left({18,20}{.5},{6}\right) $ $\left( {{{200,180,0}}} \right)$ $\left( {{{0,0,0}}} \right)$ ${{0}}{{.1}}$ ${{7}}{{.7}}$
    下载: 导出CSV

    表  2  算法运行时间随杂波密度变化

    杂波密度 30 60 90 120 150
    时间(s) 11.0 16.4 26.4 37.3 46.9
    杂波密度 180 210 240 270 300
    时间(s) 53.8 59.6 68.7 75.2 80.2
    下载: 导出CSV
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  • 收稿日期:  2024-01-26
  • 修回日期:  2024-04-17
  • 网络出版日期:  2024-05-18

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