基于单帧多通道配准的穿墙雷达运动目标实时检测方法设计与实现

doi:10.12305/j.issn.1001-506X.2026.08.06

摘要/Abstract

摘要：

穿墙雷达运动目标检测可实时获取封闭环境中的运动目标信息，在城市反恐维稳等方面发挥着重要的作用。当前研究大多集中在穿墙雷达运动目标检测算法方面，多数算法复杂度较高，难以满足实时检测的应用化需求。针对以上问题，提出一种单帧多通道配准的穿墙雷达运动目标实时检测方法及其高效实现。首先，提出一种基于单帧多通道数据频域相位补偿与对消的杂波抑制方法，有效减少传统基于多帧数据对消方法中的数据等待延迟。其次，设计一种基于图像处理单元（graphics processing unit，GPU）多数据流异步并行和线程层次结构的穿墙雷达运动目标实时检测实现方法。该方法包括基于GPU的杂波抑制多流异步并行技术、后向投影成像算法粗细粒度并行处理技术和二维恒虚警率检测算法块间并行块内规约并行处理技术。仿真与实测实验表明，所提方法能在1.078 ms内完成基于单帧、8通道和8192个距离向采样点回波数据的墙后运动目标实时检测，相较于常规基于中央处理器处理方法，处理效率提升92倍，表明了所提方法的有效性和鲁棒性。

关键词: 穿墙雷达, 移动目标, 实时检测, 图形处理器, 并行

Abstract:

Through-wall radar (TWR) motion target detection can provide real-time information on moving targets in enclosed environments, playing an important role in urban counter-terrorism and stability maintenance. Current research mainly focuses on TWR motion target detection algorithms, most of which suffer from high computational complexity, making it difficult to meet the requirements of real-time applications. To address this issue, a real-time TWR motion target detection method based on single-frame multi-channel registration and its efficient implementation is proposed. First, a clutter suppression method based on single-frame multi-channel data frequency-domain phase compensation and cancellation is introduced, which effectively reduces the data waiting latency inherent in traditional multi-frame data cancellation approaches. Secondly, a real-time detection method for moving targets of TWR based on multi stream asynchronous parallel and thread hierarchy of graphics processing unit (GPU) is designed. The proposed method includes a GPU-based clutter suppression multi-stream asynchronous parallel strategy, a coarse-and fine-grained parallelization of the back-projection （BP） imaging algorithm, and a block-level inter-parallel and intra-block reduction parallel strategy for two-dimensional constant false-alarm rate （CFAR） detection. Both simulation and experimental results demonstrate that the proposed method can complete real-time detection of moving targets behind walls within 1.078 ms for single-frame data with eight channels and 8192 range samples. Compared with conventional central processing unit-based implementations, the proposed method achieves a 92-fold improvement in processing efficiency, confirming its effectiveness and robustness.

Key words: through-wall radar, moving target, real-time detection, graphics processing unit （GPU）, parallel

中图分类号:

TN 911

曾小路, 刘国振, 钟世超, 刘飞杨, 杨小鹏. 基于单帧多通道配准的穿墙雷达运动目标实时检测方法设计与实现[J]. 系统工程与电子技术, 2026, 48(8): 2560-2580.

Xiaolu ZENG, Guozhen LIU, Shichao ZHONG, Feiyang LIU, Xiaopeng YANG. Design and implementation of real-time detection method for moving target using through-wall radar based on single-frame multi-channel registration[J]. Systems Engineering and Electronics, 2026, 48(8): 2560-2580.

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参数	参数值
信号源	线性调频连续波
脉冲宽度/s	$ 9.2\times {10}^{-8} $
带宽/GHz	0.7
中心频率/GHz	1.35
脉冲重复频率/Hz	100
发射天线间距（$ {{d}}_{{m}} $）/m	0.85
接收天线间距（$ {{d}}_{{n}} $）/m	0.21

环境信噪比/dB	对消方式	SFMCF-DPCA 后的图像熵	输出信噪比/dB
环境信噪比/dB	对消方式	SFMCF-DPCA 后的图像熵	SFMCF-DPCA	未杂波抑制
−10	任意两通道对消	7.852	9.6767	6.7061
	同发不同收通道对消	9.056	11.2126	8.4492
	相邻通道对消	7.480	14.3345	9.1661
20	任意两通道对消	7.344	17.335	9.7791
	同发不同收通道对消	6.572	22.7732	9.0724
	相邻通道对消	6.471	24.8618	10.2921
40	任意两通道对消	7.360	17.4056	9.6980
	同发不同收通道对消	6.560	22.7613	9.0519
	相邻通道对消	6.467	24.9302	10.2573

参数	参数值
信号源	线性调频连续波
脉冲宽度/s	$ 9.8\times {10}^{-8} $
带宽/GHz	0.7
中心频率/GHz	1.35
脉冲重复频率/Hz	2500
发射天线间距/m	0.85
接收天线间距/m	0.21

设备	型号	配置
CPU	Intel（R） Core（TM） i9-14900HX	5.8 GHz最大睿频，32 G内存
GPU	NVIDIA RTX 4070	5888 CUDA core，12 G显存

环节	平均耗时/ms		加速比	总加速比
环节	CPU	GPU（所提方法）	加速比	总加速比
杂波抑制	19.722	0.275	72	92
区域成像	41.785	0.305	137
目标检测	18.752	0.293	64