A Human Target Detection Method under Complex Conditions by Distributed Through-Wall Radar System
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摘要: 超宽带雷达由于具有距离分辨率高、穿透性强等特点，被广泛应用于废墟下的人体救援。然而，在复杂的环境条件下，依靠单台雷达对被困人员进行检测是一个巨大的挑战。该文基于分布式穿墙雷达系统，提出一种低信噪比条件下的人体目标自动检测方法。首先，两台超宽带脉冲雷达分时交替进行工作，从而避免探测时的互相干扰；然后对两台雷达的回波数据进行慢时间维度互相关处理，增强人体呼吸信号；其次，利用适配于分布式穿墙雷达的恒虚警率检测，实现人体呼吸信号的快速、自动检测；最后，通过三角定位方法实现被困人员的2维定位。一系列的实验结果表明，所提方法可以在低信噪比条件下实现人体的检测，其探测性能优于单台雷达。Abstract: Ultra-wideband radar is widely used for human rescue under ruins, due to its high range resolution and high penetration capability. However, it is difficult to rely on a single radar to detect trapped persons, under complex conditions. In this paper, a human respiration detection method under low Signal-to-Noise Ratio (SNR) conditions by distributed through-wall radar is proposed. First, two ultra-wideband impulse radars use time-division multiplexing to prevent mutual interference. Secondly, the slow-time dimension cross-correlation processing is performed on the echo data of the two radars to enhance the human respiration signal. Thirdly, the automatic detection algorithm is improved based on constant false alarm ratio to make it suitable for the distributed through-wall radar and realize automatic and fast detection. Finally, the trilateration algorithm is used to locate the trapped persons. A series of experimental results show that the method proposed can realize human detection under low SNR conditions, and its detection performance is better than that of a single radar.
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Key words:
- Through-wall radar /
- Distributed radar /
- Target detection
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