作者中心
专家审稿
责编办公
编辑办公
-
摘要: 随着低空经济、低空安防及无人机监管需求的持续增长，低空目标探测已成为雷达感知领域的重要研究方向。由于地面、建筑立面、植被及道路设施等散射体的存在，低空目标回波呈现出强多径、强相干与场景依赖性等复杂特性，给目标检测、参数估计、定位与跟踪带来了显著挑战。同时，多径传播也可作为补充观测信息，为非视距探测、低仰角测高、弱目标增强及协同感知提供新的信息维度与实现可能。该文系统综述了低空场景下的多径传播机理、典型信号模型及其对探测任务的影响，并在“面向任务的信息表征与决策”框架下梳理了相关研究进展。其中，多径抑制部分重点分析检测、参数估计、定位与跟踪中的典型性能退化问题；多径利用部分从能量聚焦与回波增强、几何约束下的参数反演与定位，以及信息融合驱动的持续感知3个层面，总结代表性技术路径。在此基础上，结合相关任务分析多输入多输出(MIMO)雷达的波形分集、虚拟孔径、多视角观测等体制特征对多径分离、参数估计、协同感知及资源优化的影响。最后，探讨了真实场景建模、任务驱动处理、物理先验与数据驱动融合、协同系统工程实现等未来研究方向。Abstract: With the continued growth of the low-altitude economy, rising demand for low-altitude security applications, and expanding regulations on unmanned aerial vehicles, low-altitude target detection has become an important research direction in radar sensing. Owing to the presence of scattering objects such as the ground, building facades, vegetation, and road infrastructure, echoes from low-altitude targets are often characterized by strong multipath effects, high coherence among multipath components, and pronounced scene dependence. These characteristics pose significant challenges to target detection, parameter estimation, localization, and tracking. Meanwhile, multipath propagation can also be exploited as complementary observational information, providing new information dimensions and enabling potential solutions for non-line-of-sight detection, low-elevation height estimation, weak-target enhancement, and cooperative sensing. This paper systematically reviews the propagation mechanisms, representative signal models, and impacts of multipath in low-altitude scenarios, and organizes existing studies under a task-oriented framework of information representation and decision-making. Specifically, the discussion on multipath suppression focuses on typical performance degradation issues in detection, parameter estimation, localization, and tracking, whereas multipath exploitation is summarized from three aspects: energy focusing and echo enhancement, geometry-constrained parameter retrieval and localization, and information-fusion-driven persistent sensing. On this basis, the effects of multiple-input multiple-output radar characteristics—including waveform diversity, virtual aperture, and multi-view observations—on multipath separation, parameter estimation, cooperative sensing, and resource optimization are analyzed in conjunction with different sensing tasks. Finally, future research directions are discussed, including realistic scene modeling, task-driven processing, the integration of physical priors with data-driven methods, and the system-level implementation of cooperative sensing.
-
图 2 面向任务的低空多径处理机制框架
Figure 2. Task-oriented framework for low-altitude multipath processing
表 1 多径对不同低空目标探测任务的影响及关键处理因素
Table 1. Multipath effects and key processing factors for different low-altitude target sensing tasks
任务类型 多径的主要作用形式 典型任务后果 处理时的关键判据 目标检测 改变目标回波幅相及检测统计量，
并可能形成额外峰值检测概率变化、门限失配、
虚警或鬼点产生多径分量与真实目标的相关性
及其对检测统计量的净贡献参数估计与
低仰角测高直达径与反射径相干叠加，引起角度、
时延、多普勒等参数耦合测角、测高及联合参数估计偏差 路径可分辨性、相干程度以及
传播模型可辨识性目标定位 非直达传播改变传播距离和观测方向，
并可能形成附加传播几何按LOS模型处理时产生定位偏差；具备可靠
路径模型时可形成附加位置约束路径几何可解释性及路径-
目标配对可靠性目标跟踪 多径量测随时间持续或消失，
并进入数据关联和状态更新虚假航迹、错误关联、状态跳变或
观测连续性变化跨帧稳定性、量测可关联性及其
与目标运动状态的一致性
下载: 导出CSV
表 2 面向不同低空探测任务的多径处理方法对比
Table 2. Comparison of multipath processing methods for different low-altitude sensing tasks
任务/场景 典型体制 处理方向 代表方法 关键依据与适用条件 主要特点 目标检测；LOS条件下多径鬼点或
复杂背景单站/共址MIMO 抑制 FDA-MIMO、稀疏MIMO鬼点辨识；协方差重构、知识辅助检测、STAP及学习方法 真实目标与多径在距离、角度、速度或DOD/DOA等维度具有可分辨结构，或背景统计与训练数据具有一定可靠性 可直接抑制鬼点和虚警，对复杂背景具有一定适应性；参数高度重叠、模型失配或跨场景泛化时性能易退化 弱目标/NLOS检测 单站/MIMO/协同系统 利用 时间反转、联合GLRT、绕角探测及多径特征利用 非直达路径与真实目标之间具有较可靠对应关系，目标相关附加能量及传播结构在处理时间内具有一定稳定性 可增强弱目标检测能力并拓展LOS之外的感知范围；路径不稳定或与杂波难以区分时可能增加虚警 低仰角测角与测高 单站/MIMO/稀疏阵列 抑制 ESPRIT、SBL、张量分解、稀疏/互质阵列及波束空间方法 阵列模型较可靠，目标与多径具有一定参数可辨识性，可利用阵列流形或多维参数结构进行解耦 可缓解强相干多径导致的参数估计退化；对阵列误差、模型失配及计算复杂度较敏感 参数反演与
NLOS定位单站/双基地/MIMO 利用 多维联合估计、几何反演、多径辅助定位及稀疏重构 时延、角度、多普勒及反射几何可解释或可恢复，路径来源及路径—目标配对关系较可靠 可引入附加几何和参数约束，改善遮挡条件下的可观测性；对路径配对、环境模型准确性及优化复杂度较敏感 目标跟踪 单站/多站 抑制 路径辨识、数据关联、状态级滤波及资源调度 多径量测与真实目标在跨帧运动一致性、量测统计或传播模型上存在可辨识差异 可降低错误关联、虚假航迹和状态跳变；当鬼点与真实目标短时运动特征接近时区分困难 持续跟踪与环境感知；LOS不稳定
或遮挡分布式MIMO/多节点/SAR 利用 时序状态建模、多站融合、NLOS成像及认知资源配置 多径具有稳定跨帧关联或跨节点互补性，并满足同步、几何配对和通信等基本条件 可提高遮挡环境下的观测连续性与空间覆盖能力；同步、通信、关联误差及实时性约束更加突出
下载: 导出CSV
-
[1] 中华人民共和国国务院, 中华人民共和国中央军事委员会. 无人驾驶航空器飞行管理暂行条例[J]. 中华人民共和国国务院公报, 2023(20): 6–16.State Council of the People’s Republic of China and Central Military Commission of the People’s Republic of China. Interim regulations on flight management of unmanned aircraft[J]. Gazette of the State Council of the People’s Republic of China, 2023(20): 6–16. [2] YANG Yong and YANG Boyu. Overview of radar detection methods for low altitude targets in marine environments[J]. Journal of Systems Engineering and Electronics, 2024, 35(1): 1–13. doi: 10.23919/JSEE.2024.000026. [3] 胡晓琴, 陈建文, 王永良. 米波雷达测高多径模型研究[J]. 电波科学学报, 2008, 23(4): 651–657. doi: 10.13443/j.cjors.2008.04.036.HU Xiaoqin, CHEN Jianwen, and WANG Yongliang. Research on meter-wave radar height-finding multipath model[J]. Chinese Journal of Radio Science, 2008, 23(4): 651–657. doi: 10.13443/j.cjors.2008.04.036. [4] 孔令讲, 郭世盛, 陈家辉, 等. 多径利用雷达目标探测技术综述与展望[J]. 雷达学报(中英文), 2024, 13(1): 23–45. doi: 10.12000/JR23134.KONG Lingjiang, GUO Shisheng, CHEN Jiahui, et al. Overview and prospects of multipath exploitation radar target detection technology[J]. Journal of Radars, 2024, 13(1): 23–45. doi: 10.12000/JR23134. [5] KROLIK J L, FARRELL J, and STEINHARDT A. Exploiting multipath propagation for GMTI in urban environments[C]. 2006 IEEE Conference on Radar, Verona, NY, USA, 2006: 4. doi: 10.1109/RADAR.2006.1631777. [6] SETLUR P, AMIN M, and AHMAD F. Multipath model and exploitation in through-the-wall and urban radar sensing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(10): 4021–4034. doi: 10.1109/TGRS.2011.2128331. [7] 刘永祥, 师俊朋, 黎湘. 稀疏阵列MIMO雷达参数估计研究进展[J]. 中国科学: 信息科学, 2022, 52(8): 1560–1576. doi: 10.1360/SSI-2021-0209.LIU Yongxiang, SHI Junpeng, and LI Xiang. Research progress on sparse array MIMO radar parameter estimation[J]. Scientia Sinica Informationis, 2022, 52(8): 1560–1576. doi: 10.1360/SSI-2021-0209. [8] 齐铖, 谢军伟, 张浩为, 等. 基于防空目标探测与跟踪的雷达资源管理技术研究综述[J]. 信号处理, 2024, 40(11): 1972–1989. doi: 10.12466/xhcl.2024.11.004.QI Cheng, XIE Junwei, ZHANG Haowei, et al. Review of radar resource management technology for air defense target detection and tracking[J]. Journal of Signal Processing, 2024, 40(11): 1972–1989. doi: 10.12466/xhcl.2024.11.004. [9] FISHLER E, HAIMOVICH A, BLUM R, et al. MIMO radar: An idea whose time has come[C]. 2004 IEEE Radar Conference, Philadelphia, PA, USA, 2004: 71–78. doi: 10.1109/NRC.2004.1316398. [10] GUERCI J R, WICKS M C, BERGIN J S, et al. Theory and application of optimum and adaptive MIMO radar[C]. 2008 IEEE Radar Conference, Rome, Italy, 2008: 1–6. doi: 10.1109/RADAR.2008.4721122. [11] 何子述, 程子扬, 李军, 等. 集中式MIMO雷达研究综述[J]. 雷达学报, 2022, 11(5): 805–829. doi: 10.12000/JR22128.HE Zishu, CHENG Ziyang, LI Jun, et al. A survey of collocated MIMO radar[J]. Journal of Radars, 2022, 11(5): 805–829. doi: 10.12000/JR22128. [12] LI Songlin, CUI Guolong, GUO Shisheng, et al. On the electromagnetic diffraction propagation model and applications[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 884–895. doi: 10.1109/JSTARS.2020.2974529. [13] LIN Yuqing, QIU Yuqing, LUO Yitong, et al. Viability of multipath exploitation in urban canyon: Range profiles analysis in Tomosar imaging[C]. 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024: 10902–10906. doi: 10.1109/IGARSS53475.2024.10641147. [14] JAGTAP S G and KUNTE A S. Novel approaches for target parameter extraction with eigenvalue thresholding and Dolph–Chebyshev windowing in multiple‐input multiple‐output (MIMO) radar system[J]. International Journal of Communication Systems, 2024, 37(16): e5912. doi: 10.1002/dac.5912. [15] YANG Yong and WANG Xuesong. Enhanced radar detection in the presence of specular reflection using a single transmitting antenna and three receiving antennas[J]. Remote Sensing, 2023, 15(12): 3204. doi: 10.3390/rs15123204. [16] THAI K P H, RABASTE O, BOSSE J, et al. Detection–localization algorithms in the Around-the-Corner radar problem[J]. IEEE Transactions on Aerospace and Electronic Systems, 2019, 55(6): 2658–2673. doi: 10.1109/TAES.2019.2897031. [17] GUO Shisheng, ZHAO Qingsong, CUI Guolong, et al. Behind corner targets location using small aperture millimeter wave radar in NLOS urban environment[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 460–470. doi: 10.1109/JSTARS.2020.2963924. [18] LIANG Yuanyuan, WEN Gongjian, ZHU Lingxiao, et al. Target detection performance of distributed MIMO radar systems under nonideal conditions[J]. IEEE Transactions on Aerospace and Electronic Systems, 2024, 60(2): 1951–1969. doi: 10.1109/TAES.2023.3344553. [19] YOON Y S. Elevation angle estimation in a multipath environment using MIMO-OFDM signals[J]. Remote Sensing, 2024, 16(23): 4490. doi: 10.3390/rs16234490. [20] LUO Haolan, ZHU Zhihao, JIANG Meiqiu, et al. An effective multipath ghost recognition method for sparse MIMO radar[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5111611. doi: 10.1109/TGRS.2023.3335454. [21] POURJOULA M, KARBASI M, NAYEBI M M, et al. Resolving target and image in low altitude scenarios in synthetic impulse and aperture radars[J]. Signal Processing, 2025, 228: 109754. doi: 10.1016/j.sigpro.2024.109754. [22] QIN Cong, ZHANG Qin, ZHENG Guimei, et al. Low angle estimation in MIMO radar based on unitary ESPRIT under spatial smoothing[J]. IET Radar, Sonar & Navigation, 2024, 18(10): 1829–1836. doi: 10.1049/rsn2.12619. [23] 刘旗, 郭瑞, 王佳佳, 等. 低仰角目标高精度波束空间DOA估计方法[J]. 雷达学报(中英文), 2026, 15(3): 860–875. doi: 10.12000/JR25173.LIU Qi, GUO Rui, WANG Jiajia, et al. A high-accuracy beamspace DOA estimation method for low-elevation angle targets[J]. Journal of Radars, 2026, 15(3): 860–875. doi: 10.12000/JR25173. [24] XIONG Jian, XIE Xin, GUAN Xujun, et al. Research on radio altimetry in urban environments based on electromagnetic simulation echo modeling technology[J]. Sensors, 2026, 26(6): 1932. doi: 10.3390/s26061932. [25] WANG Zhaolong, TONG Chuangming, WANG Tong, et al. A new radar echo generation model for ultra-low altitude targets in far-field conditions[J]. International Journal of Antennas and Propagation, 2022, 2022: 5145743. doi: 10.1155/2022/5145743. [26] CAO Chun, FAN Chongyi, WANG Jian, et al. The knowledge-aided generalized multipath adaptive detector[J]. Signal Processing, 2024, 220: 109468. doi: 10.1016/j.sigpro.2024.109468. [27] XIONG Chao, FAN Chongyi, and HUANG Xiaotao. Multipath exploitation with time reversal waveform covariance matrix for SNR maximization[J]. Remote Sensing, 2020, 12(21): 3565. doi: 10.3390/rs12213565. [28] CAO Chun, FAN Chongyi, DU Huagui, et al. Adaptive detection for resolvable multipath signal under heterogeneous clutter[J]. IET Radar, Sonar & Navigation, 2023, 17(1): 139–152. doi: 10.1049/rsn2.12330. [29] MA Jianjun, LIU Hongwei, and MA Hui. Low-elevation target DOA estimation based on multi-scattering center equivalent model[J]. Remote Sensing, 2022, 14(15): 3533. doi: 10.3390/rs14153533. [30] TANG Derui, ZHAO Yongbo, and ZHANG Shuaijie. Meter-wave radar height estimation based on sparse Bayesian learning under refined reflection model[J]. Signal Processing, 2026, 239: 110267. doi: 10.1016/j.sigpro.2025.110267. [31] MA Jianjun, MA Hui, LIU Hongwei, et al. A novel DOA estimation for low-elevation target method based on multiscattering center equivalent model[J]. IEEE Geoscience and Remote Sensing Letters, 2023, 20: 3501605. doi: 10.1109/LGRS.2023.3242977. [32] LV Fan, ZHANG Xiaokuan, LIU Yuan, et al. Target localization method via ANM-ADMM adapted to fluctuant multipath environment without prior knowledge[J]. Signal Processing, 2026, 244: 110527. doi: 10.1016/j.sigpro.2026.110527. [33] LIU Yibin, WANG Chunyang, GONG Jian, et al. Robust suppression of deceptive jamming with VHF-FDA-MIMO radar under multipath effects[J]. Remote Sensing, 2022, 14(4): 942. doi: 10.3390/rs14040942. [34] FENG Ruoyu, DE GREEF E, RYKUNOV M, et al. Multipath ghost recognition for indoor MIMO radar[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5104610. doi: 10.1109/TGRS.2021.3109381. [35] FU Zhenzhuo, FANG Yu, and WU Daoqing. Research on radar system compatibility and data processing of low-altitude small target detection[C]. 2024 4th International Conference on Electronic Information Engineering and Computer Science, Yanji, China, 2024: 543–547. doi: 10.1109/EIECS63941.2024.10800679. [36] FANG Xin, ZHU Jing, HUANG Darong, et al. E2DTF: An end-to-end detection and tracking framework for multiple micro-UAVs with FMCW-MIMO radar[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 2000916. doi: 10.1109/TGRS.2023.3262062. [37] WANG Hongzhen, ZHENG Guimei, LIU Yibin, et al. Low elevation and range joint estimation method with metre wave frequency diverse array‐multiple input multiple output radar based on sparse array[J]. IET Radar, Sonar & Navigation, 2022, 16(7): 1176–1187. doi: 10.1049/rsn2.12252. [38] 王佳佳, 郭瑞, 刘旗, 等. 复杂地形MIMO雷达低仰角估计方法[J]. 电子与信息学报, 2025, 47(10): 3691–3701. doi: 10.11999/JEIT250236.WANG Jiajia, GUO Rui, LIU Qi, et al. Low elevation angle estimation method for MIMO radar in complex terrain[J]. Journal of Electronics & Information Technology, 2025, 47(10): 3691–3701. doi: 10.11999/JEIT250236. [39] GUO Rui, PENG Xiangyu, TIAN Biao, et al. Low elevation target altitude measurement for ubiquitous radar based on known transmitted waveform and sparse representation[J]. IET Radar, Sonar & Navigation, 2022, 16(2): 346–355. doi: 10.1049/rsn2.12187. [40] QIN Cong, ZHANG Qin, ZHENG Guimei, et al. Height measurement for meter-wave MIMO radar based on sparse array under multipath interference[J]. Remote Sensing, 2024, 16(22): 4331. doi: 10.3390/rs16224331. [41] WANG Hongzhen, ZHENG Guimei, and SONG Yuwei. Height measurement method of monostatic metre wave multiple input multiple output radar based on coprime array[J]. IET Signal Processing, 2022, 16(4): 479–489. doi: 10.1049/sil2.12121. [42] TANG Derui, ZHAO Yongbo, and ZHANG Shuaijie. A height estimation method based on a beamspace joint alternating iterative algorithm in MIMO radar[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(9): 1742–1753. doi: 10.1631/fitee.2500030. [43] CHEN Sheng, ZHAO Yongbo, HU Yili, et al. Beamspace scene classification algorithm for low-angle estimation in MIMO radar[J]. Remote Sensing, 2022, 14(8): 1917. doi: 10.3390/rs14081917. [44] ZHAO Yongbo, PANG Xiaojiao, and CHEN Sheng. A reduced-dimension RML method for transmit beamspace-based MIMO radar[J]. Digital Signal Processing, 2021, 114: 103072. doi: 10.1016/j.dsp.2021.103072. [45] DING Rui, WANG Zhuang, JIANG Libing, et al. A target localisation method with monostatic radar via multi‐observation data association[J]. IET Radar, Sonar & Navigation, 2023, 17(1): 99–116. doi: 10.1049/rsn2.12327. [46] DING Rui, WANG Zhuang, JIANG Libing, et al. Radar target localization with multipath exploitation in dense clutter environments[J]. Applied Sciences, 2023, 13(4): 2032. doi: 10.3390/app13042032. [47] 滕旭, 张林昌, 蒋忠涌. 高层建筑对脉冲多径时延展宽影响分析与建模[J]. 铁道学报, 1999, 21(4): 47–50. doi: 10.3321/j.issn:1001-8360.1999.04.012.TENG Xu, ZHANG Linchang, and JIANG Zhongyong. Analyzing and modeling for the digital signal multipath propagation time delay spread suffered from huge buildings in a city in mobile communication system[J]. Journal of the China Railway Society, 1999, 21(4): 47–50. doi: 10.3321/j.issn:1001-8360.1999.04.012. [48] 蒋美秋, 罗皓蓝, 郭世盛, 等. 基于多径扩展投影的毫米波雷达室内目标跟踪方法[J]. 雷达学报(中英文), 2026. doi: 10.12000/JR25245.JIANG Meiqiu, LUO Haolan, GUO Shisheng, et al. Indoor target tracking method for millimeter-wave radar based on multipath extension mapping[J]. Journal of Radars, 2026. doi: 10.12000/JR25245. [49] LI Hongbin, WANG Fangzhou, ZENG Cengcang, et al. Signal detection in distributed MIMO radar with non-orthogonal waveforms and sync errors[J]. IEEE Transactions on Signal Processing, 2021, 69: 3671–3684. doi: 10.1109/TSP.2021.3087897. [50] YANG Shixing, JAKOBSSON A, and YI Wei. Moving target detection using a distributed MIMO radar system with synchronization errors[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5107417. doi: 10.1109/TGRS.2023.3299233. [51] 蒋留兵, 张泽, 车俐. 基于毫米波雷达的非视距目标探测和定位方法研究[J]. 雷达科学与技术, 2024, 22(1): 5–13. doi: 10.3969/j.issn.1672-2337.2024.01.002.JIANG Liubing, ZHANG Ze, and CHE Li. Research on NLOS target detection and localization method based on millimeter wave radar[J]. Radar Science and Technology, 2024, 22(1): 5–13. doi: 10.3969/j.issn.1672-2337.2024.01.002. [52] YANG Yiping, CHEN Chuan, JIA Yong, et al. Non-line-of-sight target detection based on dual-view observation with single-channel UWB radar[J]. Remote Sensing, 2022, 14(18): 4532. doi: 10.3390/rs14184532. [53] WU Peilun, CHEN Jiahui, GUO Shisheng, et al. NLOS positioning for building layout and target based on association and hypothesis method[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5101913. doi: 10.1109/TGRS.2023.3250831. [54] YANG Xiaqing, FAN Shihao, GUO Shisheng, et al. NLOS target localization behind an L-shaped corner with an L-band UWB radar[J]. IEEE Access, 2020, 8: 31270–31286. doi: 10.1109/ACCESS.2020.2973046. [55] 刘永龙, 邹旺, 葛富超, 等. 基于多站协同显著路径筛选的多径利用雷达遮蔽目标成像方法[J]. 电讯技术, 2026, 66(3): 455–464. doi: 10.20079/j.issn.1001-893x.241214002.LIU Yonglong, ZOU Wang, GE Fuchao, et al. Multipath exploitation radar imaging method for shadowed targets based on multi-station cooperative dominant path screening[J]. Telecommunication Engineering, 2026, 66(3): 455–464. doi: 10.20079/j.issn.1001-893x.241214002. [56] ZHANG Wanyu, ZENG Xiaolu, YANG Yifei, et al. Rotor unmanned aerial vehicle localization in the building sheltered area based on millimetre‐wave frequency‐modulated continuous wave radar[J]. IET Radar, Sonar & Navigation, 2024, 18(10): 1937–1951. doi: 10.1049/rsn2.12630. [57] LIN Yuqing, QIU Xiaolan, LUO Yitong, et al. Multipath exploitation: Non-line-of-sight target relocation in Array-InSAR 3-D imaging[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024, 62: 4708414. doi: 10.1109/TGRS.2024.3463003. [58] 林雨青, 仇晓兰, 彭凌霄, 等. 基于多径模型的建筑区SAR三维成像中非视距目标重定位方法[J]. 雷达学报(中英文), 2024, 13(4): 777–790. doi: 10.12000/JR24057.LIN Yuqing, QIU Xiaolan, PENG Lingxiao, et al. Non-line-of-sight target relocation by multipath model in SAR 3D urban area imaging[J]. Journal of Radars, 2024, 13(4): 777–790. doi: 10.12000/JR24057. [59] HAIMOVICH A M, BLUM R S, and CIMINI L J. MIMO radar with widely separated antennas[J]. IEEE Signal Processing Magazine, 2008, 25(1): 116–129. doi: 10.1109/MSP.2008.4408448. [60] FAN Chongyi, XIE Zhuang, WANG Jian, et al. Robust MIMO waveform design in the presence of unknown mutipath return[J]. Remote Sensing, 2022, 14(17): 4356. doi: 10.3390/rs14174356. [61] WANG Hongyan, ZHOU He, GUO Qinghua, et al. Joint allocation of transmit-receive resource for MIMO-STAP[J]. Signal Processing, 2023, 209: 109008. doi: 10.1016/j.sigpro.2023.109008. [62] CHENG Jie, JIA Yizhen, WANG Wenqin, et al. Multipath identification and mitigation with FDA-MIMO radar[J]. Digital Signal Processing, 2026, 168: 105519. doi: 10.1016/j.dsp.2025.105519. [63] PARK J K, PARK J H, and KIM K T. Multipath signal mitigation for indoor localization based on MIMO FMCW radar system[J]. IEEE Internet of Things Journal, 2024, 11(2): 2618–2629. doi: 10.1109/JIOT.2023.3292349. [64] ESPOSITO G, CATAPANO I, LUDENO G, et al. A deep learning strategy for multipath ghosts filtering via microwave tomography[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024, 62: 5100314. doi: 10.1109/TGRS.2023.3337893. [65] CAI Lingping, QIAN Haonan, XING Linger, et al. A software-defined radar for low-altitude slow-moving small targets detection using transmit beam control[J]. Remote Sensing, 2023, 15(13): 3371. doi: 10.3390/rs15133371. [66] WANG Zhaolong, ZHANG Xiaokuan, FENG Weike, et al. Multipath and deep learning-based detection of ultra-low moving targets above the sea[J]. Remote Sensing, 2024, 16(24): 4773. doi: 10.3390/rs16244773. [67] LI Sijia, WANG Huake, LIAO Guisheng, et al. Robust sparse recovery-based STAP for clutter suppression under multipath effect in low-altitude environments[J]. IEEE Transactions on Aerospace and Electronic Systems, 2026, 62: 3711–3720. doi: 10.1109/TAES.2025.3649187. [68] LI Haodong, LIAO Guisheng, XU Jingwei, et al. Multi-resolution STAP for enhanced ultra-low-altitude target detection[J]. Remote Sensing, 2021, 13(21): 4212. doi: 10.3390/rs13214212. [69] WU Zeyang, PENG Yuexing, and WANG Wenbo. Deep learning-based unmanned aerial vehicle detection in the low altitude clutter background[J]. IET Signal Processing, 2022, 16(5): 588–600. doi: 10.1049/sil2.12133. [70] 项厚宏, 王永良, 李雨曦, 等. 基于特征博弈预处理的多径抑制与高精度测角方法[J]. 雷达学报(中英文), 2025, 14(2): 269–279. doi: 10.12000/JR24215.XIANG Houhong, WANG Yongliang, LI Yuxi, et al. Multipath suppression and high-precision angle measurement method based on feature game preprocessing[J]. Journal of Radars, 2025, 14(2): 269–279. doi: 10.12000/JR24215. [71] HU Yili, ZHAO Yongbo, CHEN Sheng, et al. Direction of arrival estimation of airborne multiple‐input multiple‐output radar in multipath environment[J]. IET Radar, Sonar & Navigation, 2021, 15(10): 1173–1180. doi: 10.1049/rsn2.12099. [72] LIU Yuan and LIU Hongwei. Target height measurement under complex multipath interferences without exact knowledge on the propagation environment[J]. Remote Sensing, 2022, 14(13): 3099. doi: 10.3390/rs14133099. [73] KWON D, KO H, HONG S, et al. Elevation estimation algorithm for low-altitude targets in multipath environment[J]. Journal of Electromagnetic Engineering and Science, 2024, 24(4): 341–349. doi: 10.26866/jees.2024.4.r.234. [74] XIANG Houhong, CHEN Baixiao, YANG Minglei, et al. Altitude measurement based on characteristics reversal by deep neural network for VHF radar[J]. IET Radar, Sonar & Navigation, 2019, 13(1): 98–103. doi: 10.1049/iet-rsn.2018.5121. [75] CHEN Sheng, ZHAO Yongbo, HU Yili, et al. Target height and multipath attenuation joint estimation with complex scenarios for very high frequency radar[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(6): 937–949. doi: 10.1631/FITEE.2100003. [76] WANG Xianchao, WEI Yanping, LI Shaoyi, et al. Altitude measurement method of VHF radar based on spatial smoothing of correlation matrix[J]. Scientific Reports, 2023, 13(1): 22211. doi: 10.1038/s41598-023-47294-3. [77] PARK J and KIM E. Super-resolution processing for multiple aperture antenna to suppress multipath[J]. Mathematics, 2024, 12(20): 3186. doi: 10.3390/math12203186. [78] ZHANG Haowei, LIU Haowei, FEI Taiyong, et al. An efficient radar-target assignment and power allocation strategy for low-angle tracking in the MIMO-multisite radar system[J]. Signal Processing, 2022, 200: 108645. doi: 10.1016/j.sigpro.2022.108645. [79] ZHANG Haowei, LIU Weijian, and FEI Taiyong. Beam resource scheduling for a VHF-MIMO radar network in low-angle tracking[J]. Chinese Journal of Aeronautics, 2023, 36(4): 423–441. doi: 10.1016/j.cja.2022.12.007. [80] DAEIPOUR E, BLAIR W D, and BAR-SHALOM Y. Bias compensation and tracking with monopulse radars in the presence of multi path[J]. IEEE Transactions on Aerospace and Electronic Systems, 1997, 33(3): 863–882. doi: 10.1109/7.599258. [81] FAN Mingyang, LIU Chaojie, JIA Jinsong, et al. Mismatch-indicator identification-enabled generalized labeled multi-Bernoulli filter for tracking multi-UAVs in urban environments[J]. Aerospace Science and Technology, 2026, 175: 111958. doi: 10.1016/j.ast.2026.111958. [82] HERNANDEZ M and FARINA A. PCRB and IMM for target tracking in the presence of specular multipath[J]. IEEE Transactions on Aerospace and Electronic Systems, 2020, 56(3): 2437–2449. doi: 10.1109/TAES.2019.2948671. [83] JIN Yuanwei, MOURA J M F, and O’DONOUGHUE N. Time reversal in multiple-input multiple-output radar[J]. IEEE Journal of Selected Topics in Signal Processing, 2010, 4(1): 210–225. doi: 10.1109/JSTSP.2009.2038983. [84] ZHANG Zhaoming, CHEN Baixiao, and YANG Minglei. Moving target detection based on time reversal in a multipath environment[J]. IEEE Transactions on Aerospace and Electronic Systems, 2021, 57(5): 3221–3236. doi: 10.1109/TAES.2021.3074131. [85] XU Lin, LI Yajun, WANG Pengfei, et al. High-frequency hybrid sky-surface wave radar target detection based on time reversal in sea clutter background[J]. IEEE Transactions on Aerospace and Electronic Systems, 2025, 61(4): 10130–10148. doi: 10.1109/TAES.2025.3560944. [86] ZHOU Hao, HU Guoping, SHI Junpeng, et al. Adaptive two-step Bayesian generalized likelihood ratio test algorithm for low-altitude detection[J]. IEICE Transactions on Communications, 2019, E102.B(3): 571–580. doi: 10.1587/transcom.2017ebp3418. [87] YILMAZ S H G and HAYVACI H T. Multipath exploitation radar with adaptive detection in partially homogeneous environments[J]. IET Radar, Sonar & Navigation, 2020, 14(10): 1475–1482. doi: 10.1049/iet-rsn.2020.0059. [88] LI Songlin, GUO Shisheng, CHEN Jiahui, et al. Multiple targets localization behind L-shaped corner via UWB radar[J]. IEEE Transactions on Vehicular Technology, 2021, 70(4): 3087–3100. doi: 10.1109/TVT.2021.3068266. [89] 黄乾超. 毫米波雷达非视域目标多径探测方法研究[D]. [硕士论文], 桂林电子科技大学, 2024. doi: 10.27049/d.cnki.ggldc.2024.001576.HUANG Qianchao. Research on multipath detection methods of non-line-of-sight targets with millimeter wave radar[D]. [Master dissertation], Guilin University of Electronic Technology, 2024. doi: 10.27049/d.cnki.ggldc.2024.001576. [90] PASSAFIUME M, ROJHANI N, COLLODI G, et al. Modeling small UAV micro-Doppler signature using millimeter-wave FMCW radar[J]. Electronics, 2021, 10(6): 747. doi: 10.3390/electronics10060747. [91] ZHANG Pengfei, LI Gang, HUO Chaoying, et al. Exploitation of multipath micro‐Doppler signatures for drone classification[J]. IET Radar, Sonar & Navigation, 2020, 14(4): 586–592. doi: 10.1049/iet-rsn.2019.0105. [92] XU Zhou, FAN Chongyi, and HUANG Xiaotao. MIMO radar waveform design for multipath exploitation[J]. IEEE Transactions on Signal Processing, 2021, 69: 5359–5371. doi: 10.1109/TSP.2021.3112042. [93] YILMAZ S H G, ZARRO C, HAYVACI H T, et al. Adaptive waveform design with multipath exploitation radar in heterogeneous environments[J]. Remote Sensing, 2021, 13(9): 1628. doi: 10.3390/rs13091628. [94] ZHENG Zixiang, ZHANG Yue, PENG Xiangyu, et al. MIMO radar waveform design for multipath exploitation using deep learning[J]. Remote Sensing, 2023, 15(11): 2747. doi: 10.3390/rs15112747. [95] QI Cheng, XIE Junwei, ZHANG Haowei, et al. Optimizing low-grazing angle detection for maneuvering targets in cognitive MIMO radar networks: A Shapley value approach[J]. IEEE Transactions on Vehicular Technology, 2025, 74(3): 4977–4992. doi: 10.1109/TVT.2024.3496778. [96] QI Cheng, ZHANG Haowei, XIE Junwei, et al. Cooperative game theoretic power allocation method to distributed MIMO radar sensor network for multitarget detection in low-altitude[J]. IEEE Sensors Journal, 2024, 24(6): 8731–8745. doi: 10.1109/JSEN.2024.3357891. [97] ZHANG Shoushuo, XIAO Zichao, LIU Rang, et al. Multipath exploitation for fluctuating target detection in RIS-assisted ISAC systems[J]. IEEE Wireless Communications Letters, 2024, 13(9): 2392–2396. doi: 10.1109/LWC.2024.3416453. [98] XU Xueting, ZHOU Yang, LI Huiying, et al. RIS-aided passive detection for LSS targets: A GNSS multipath-assisted scheme[J]. IEEE Journal on Selected Areas in Communications, 2024, 42(1): 34–51. doi: 10.1109/JSAC.2023.3322801. [99] LIANG Haobo, FENG Yuan, ZHANG Yushi, et al. A segmented sliding window reference signal reconstruction method based on fuzzy C-Means[J]. Remote Sensing, 2024, 16(10): 1813. doi: 10.3390/rs16101813. [100] AHMADI M, ALAEE-KERAHROODI M, BHAVANI SHANKAR M R, et al. Subspace-based detector for distributed mmwave MIMO radar sensors[C]. 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Rhodes Island, Greece, 2023: 1–5. doi: 10.1109/ICASSP49357.2023.10095315. [101] QI Cheng, XIE Junwei, ZHANG Haowei, et al. Research on detection performance of distributed PA-MIMO radar[C]. 2022 14th International Conference on Signal Processing Systems, Jiangsu, China, 2022: 156–161. doi: 10.1109/ICSPS58776.2022.00032. [102] DEIANA D, KOSSEN A S, and VAN ROSSUM W L. Multipath exploitation in an urban environment using a MIMO surveillance radar[C]. 11th International Radar Symposium, Vilnius, Lithuania, 2010: 1–4. [103] TIAN Xiang, CHEN Hui, HUANG Bang, et al. Fast parameter estimation algorithms for conformal FDA-MIMO radar[J]. IEEE Sensors Journal, 2023, 23(24): 30633–30641. doi: 10.1109/JSEN.2023.3325452. [104] ZHANG Juan, FAN Hongbao, WANG Chenhong, et al. Distance estimation and pairing for low angle group targets based on radar time reversal[J]. Digital Signal Processing, 2020, 106: 102808. doi: 10.1016/j.dsp.2020.102808. [105] XU Feng, MORENCY M W, and VOROBYOV S A. DOA estimation for transmit beamspace MIMO radar via tensor decomposition with Vandermonde factor matrix[J]. IEEE Transactions on Signal Processing, 2022, 70: 2901–2917. doi: 10.1109/TSP.2022.3176092. [106] GUO Yuehao, WANG Xianpeng, SHI Jinmei, et al. Fast real-valued tensor decomposition framework for parameter estimation in FDA-MIMO radar[J]. Digital Signal Processing, 2024, 145: 104309. doi: 10.1016/j.dsp.2023.104309. [107] ZHENG Guimei, SONG Yuwei, LIU Yibin, et al. Search-free range and angle estimation for bistatic VHF-FDA-MIMO radar in complex terrain[J]. Signal Processing, 2023, 212: 109163. doi: 10.1016/j.sigpro.2023.109163. [108] CHEN Jiahui, ZHANG Yang, GUO Shisheng, et al. Joint estimation of NLOS building layout and targets via sparsity-driven approach[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5114513. doi: 10.1109/TGRS.2022.3182429. [109] SUN Yanpeng, CHEN Li, and QU Lele. Through-the-wall radar imaging algorithm for moving target under wall parameter uncertainties[J]. IET Image Processing, 2019, 13(11): 1903–1908. doi: 10.1049/iet-ipr.2018.5670. [110] LEIGSNERING M, AHMAD F, AMIN M, et al. Multipath exploitation in through-the-wall radar imaging using sparse reconstruction[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2): 920–939. doi: 10.1109/TAES.2013.120528. [111] ZHANG Y, AHMED A, and HIMED B. Target altitude estimation in over-the-horizon radar[J]. IEEE Access, 2022, 10: 11260–11273. doi: 10.1109/ACCESS.2022.3145023. [112] CHEN Sheng, ZHAO Yongbo, HU Yili, et al. A beamspace maximum likelihood algorithm for target height estimation for a bistatic MIMO radar[J]. Digital Signal Processing, 2022, 122: 103330. doi: 10.1016/j.dsp.2021.103330. [113] 陈梦蝶, 王桁, 杨乃俊, 等. 动态环境下基于稀疏贝叶斯学习的多径利用自适应波束形成[J]. 通信技术, 2025, 58(10): 1048–1054. doi: 10.3969/j.issn.1002-0802.2025.10.003.CHEN Mengdie, WANG Heng, YANG Naijun, et al. Multipath utilization adaptive beamforming based on sparse Bayesian learning in dynamic environments[J]. Communications Technology, 2025, 58(10): 1048–1054. doi: 10.3969/j.issn.1002-0802.2025.10.003. [114] SEBT M A, GOODARZI M, and DARVISHI H. Geometric arithmetic mean method for low altitude target elevation angle tracking[J]. IEEE Transactions on Aerospace and Electronic Systems, 2023, 59(5): 5111–5119. doi: 10.1109/TAES.2023.3248562. [115] XIANG Yikun, XI Feng, and CHEN Shengyao. LiQuiD-MIMO radar: Distributed MIMO radar with low-bit quantization[C]. 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Rhodes Island, Greece, 2023: 1–5. doi: 10.1109/ICASSP49357.2023.10096939. [116] CHEN Ruilin, GUO Shisheng, and CUI Guolong. A fast multi-target detection and localization method for distributed MIMO radar[C]. 2022 5th International Conference on Telecommunications and Communication Engineering, New York, China, 2023: 89–94. doi: 10.1145/3577065.3577082. [117] LIU Qi, GUO Rui, WANG Jiajia, et al. Signal-level fusion-based height estimation of low-elevation target for distributed radar[J]. IEEE Transactions on Instrumentation and Measurement, 2025, 74: 6508114. doi: 10.1109/TIM.2025.3593573. [118] FENG Xiang, SUN Ping, ZHANG Lu, et al. Cognitive radar waveform selection for low-altitude maneuvering-target tracking: A robust information-aided fusion method[J]. Remote Sensing, 2024, 16(21): 3951. doi: 10.3390/rs16213951. -
图(2) / 表(2)
计量
- 文章访问数:
- HTML全文浏览量:
- PDF下载量:
- 被引次数: 0
