An Indoor Moving Target Detection Method Based on Doppler Chirp Rate Profile and Range Gating Filter

IF 8.9 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Internet of Things Journal Pub Date : 2025-02-12 DOI:10.1109/JIOT.2025.3540887
Xiaodong Qu;Feiyang Liu;Hao Zhang;Xiaolong Sun;Xiaopeng Yang
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Abstract

The detection of indoor moving targets using autonomous-aerial-vehicle (AAV)-mounted through-the-wall radar (TWR) has been widely applied in both military and civilian fields. However, the imaging results of moving targets often suffer from defocusing and are prone to be submerged in strong stationary clutter, which reduces the detection rate of moving targets. To address this issue, this article proposes a detection method for indoor moving targets based on Doppler chirp rate profile and range gating filter using AAV-mounted TWR. In the proposed method, the characteristics of Doppler chirp rate for both clutter and moving targets are analyzed. The range migration of the target echo is corrected in the range-Doppler (RD) domain through sinc interpolation. Then, the fractional Fourier transform (FrFT) is applied to estimate the chirp rate at each range bin. Subsequently, the estimated chirp rate values are compared with the theoretical chirp rate values of stationary objects. Based on the differences of Doppler chirp rates, a gating filter in fast time domain is designed to suppress clutter originated from walls and stationary objects. Finally, an azimuth compression filter is constructed to achieve focused imaging of moving targets. Both simulation and field experiments demonstrate the feasibility and effectiveness of the proposed method. The proposed method shows strengths over other methods in terms of improvement factor, image entropy, and peak-sidelobe ratio.
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基于多普勒啁啾速率谱和距离门控滤波器的室内运动目标检测方法
利用机载自主飞行器(AAV)的穿壁雷达(TWR)对室内运动目标进行探测,在军事和民用领域都有广泛的应用。然而,运动目标的成像结果往往存在离焦问题,且容易被强静止杂波淹没,降低了运动目标的检测率。针对这一问题,本文提出了一种基于机载TWR的多普勒啁啾速率谱和距离门控滤波器的室内运动目标检测方法。在该方法中,分析了杂波和运动目标的多普勒啁啾率特性。通过正弦插值在距离-多普勒(RD)域对目标回波的距离偏移进行校正。然后,应用分数阶傅里叶变换(FrFT)估计每个距离库的啁啾率。然后,将估计的啁啾率值与静止目标的理论啁啾率值进行比较。基于多普勒啁啾速率的差异,设计了一种快速时域门控滤波器来抑制来自墙壁和静止物体的杂波。最后构造了一个方位压缩滤波器,实现了运动目标的聚焦成像。仿真和现场实验验证了该方法的可行性和有效性。该方法在改进系数、图像熵和峰值旁瓣比等方面均优于其他方法。
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来源期刊
IEEE Internet of Things Journal
IEEE Internet of Things Journal Computer Science-Information Systems
CiteScore
17.60
自引率
13.20%
发文量
1982
期刊介绍: The EEE Internet of Things (IoT) Journal publishes articles and review articles covering various aspects of IoT, including IoT system architecture, IoT enabling technologies, IoT communication and networking protocols such as network coding, and IoT services and applications. Topics encompass IoT's impacts on sensor technologies, big data management, and future internet design for applications like smart cities and smart homes. Fields of interest include IoT architecture such as things-centric, data-centric, service-oriented IoT architecture; IoT enabling technologies and systematic integration such as sensor technologies, big sensor data management, and future Internet design for IoT; IoT services, applications, and test-beds such as IoT service middleware, IoT application programming interface (API), IoT application design, and IoT trials/experiments; IoT standardization activities and technology development in different standard development organizations (SDO) such as IEEE, IETF, ITU, 3GPP, ETSI, etc.
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