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基于空间谱估计的无人机协同目标方位感知算法

吴鑫炜 胡明华 毛继志 王扬

吴鑫炜, 胡明华, 毛继志, 王扬. 基于空间谱估计的无人机协同目标方位感知算法[J]. 西南交通大学学报. doi: 10.3969/j.issn.0258-2724.20230438
引用本文: 吴鑫炜, 胡明华, 毛继志, 王扬. 基于空间谱估计的无人机协同目标方位感知算法[J]. 西南交通大学学报. doi: 10.3969/j.issn.0258-2724.20230438
WU Xinwei, HU Minghua, MAO Jizhi, WANG Yang. Collaborative Target Azimuth Perception Algorithm of Unmanned Aerial Vehicles Based on Spatial Spectrum Estimation[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230438
Citation: WU Xinwei, HU Minghua, MAO Jizhi, WANG Yang. Collaborative Target Azimuth Perception Algorithm of Unmanned Aerial Vehicles Based on Spatial Spectrum Estimation[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230438

基于空间谱估计的无人机协同目标方位感知算法

doi: 10.3969/j.issn.0258-2724.20230438
基金项目: 国家重点研发计划(2022YFB4300900)
详细信息
    作者简介:

    吴鑫炜(1985—),男,高级工程师,博士研究生,研究方向为无人机智能化运行,E-mail:wxw8237@163.com

  • 中图分类号: V279;TN911.7

Collaborative Target Azimuth Perception Algorithm of Unmanned Aerial Vehicles Based on Spatial Spectrum Estimation

  • 摘要:

    无人机协同目标感知技术是有人机无人机混合运行的重要安全保障. 针对复杂空域环境下的感知可靠性问题,分析大中型无人机的复杂融合空域运行场景,并确定无人机协同目标感知的精准性、高实时性、抗干扰性和低载荷性等需求,提出一种四单元阵列天线和数字化射频体制的无人机协同目标感知系统架构;同时,结合空管雷达信号特性和天线体制,设计方位感知算法,通过修正协方差矩阵、信号子空间加权和噪声子空间加权等方法,设计基于多信号分类(multiple signal classification,MUSIC)的空间谱估计算法,并提出基于子空间分解的幅相误差在线估计算法;最后,开展算法仿真试验和实际空域环境飞行试验. 研究结果表明:相比传统MUSIC算法,优化算法的方位感知高分辨性能提升23.3%,并改善了无人机协同目标方位感知的高实时性、抗干扰性和低载荷性.

     

  • 图 1  空管雷达C/S模式信号(单位:us)

    Figure 1.  C/S mode signal from ATC radar (unit: us)

    图 2  无人机协同目标感知系统架构

    Figure 2.  Collaborative target perception system architecture of UAVs

    图 3  四单元阵列天线示意

    Figure 3.  Four-unit array antenna

    图 4  非相干信源空间谱

    Figure 4.  Spatial spectrum of incoherent information sources

    图 5  相干信源空间谱

    Figure 5.  Spatial spectrum of coherent information sources

    图 6  成功分辨概率

    Figure 6.  Successful resolution probability

    图 7  成功分辨概率

    Figure 7.  Successful resolution probability

    图 8  误差统计分析

    Figure 8.  Statistical analysis of errors

    图 9  校准前后空间谱

    Figure 9.  Spatial spectra before and after calibration

    图 10  不同信噪比条件下的算法估计偏差

    Figure 10.  Algorithm estimation deviation under different signal-to-noise ratios

    图 11  硬件验证平台

    Figure 11.  Hardware verification platform

    图 12  近距离协同目标

    Figure 12.  Close-range collaborative target

    图 13  远距离协同目标

    Figure 13.  Long-range collaborative target

    表  1  幅相误差

    Table  1.   Amplitude-phase error

    通道 设计值 估计值
    1 1.0000 1.0000
    2 0.2249 + 1.178 7i 0.1727 + 1.103 9i
    3 −0.8229−1.132 6i −0.7198−1.012 8i
    4 −1.5874 + 0.200 5i −1.3692 + 0.158 8i
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出版历程
  • 收稿日期:  2023-09-06
  • 修回日期:  2024-01-03
  • 网络出版日期:  2024-05-11

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