Range-Doppler Map Improvement in FMCW Radar for Small Moving Drone Detection Using the Stationary Point Concentration Technique
Range-Doppler Map Improvement in FMCW Radar for Small Moving Drone Detection Using the Stationary Point Concentration Technique
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DOI：
10.1109/tmtt.2019.2961911
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发表时间：
2020-01
影响因子：
4.3
通讯作者：
Junhyeong Park;Dae-Hwan Jung;Kyung-Bin Bae;Seong‐Ook Park
中科院分区：
文献类型：
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作者：
Junhyeong Park;Dae-Hwan Jung;Kyung-Bin Bae;Seong‐Ook Park
鉴于快速增长的无人机市场，无人机探测雷达的开发对于防止无人机损害生命和财产变得非常重要。调频连续波（FMCW）雷达经常用于无人机探测。在FMCW雷达的架构中，通常选择外差架构，其涉及不同的本机振荡器并在IF级产生差拍信号。然而，FMCW雷达有一个长期存在的问题，称为泄漏。在早期的研究中，我们提出了固定点集中（SPC）技术，通过减少泄漏引起的噪声本底增加来提高小型无人机的信噪比（SNR）。我们证明了所提出的技术增加了小型悬停无人机在1-D功率谱中的SNR。本文对外差FMCW雷达系统的实际问题进行了新的分析。一个是由于泄漏导致的距离-多普勒（r-D）图中的2-D噪声基底增加，另一个是不需要的多普勒频移。在此基础上，提出了一种基于改进的r-D图的SPC技术在小型运动无人机检测中的改进理论和实现方法。我们证明，该方法不仅减少了2-D噪声地板减轻泄漏，但也消除了不必要的多普勒频移的相位校准。因此，我们表明，所提出的方法增加了信噪比的小型移动无人机，并纠正其速度信息在同一时间在r-D地图。
Given the rapidly growing drone market, the development of drone detection radars has become highly important to prevent drones from damaging lives and property. Frequency-modulated continuous-wave (FMCW) radars have been frequently used for drone detection. Among the architectures of FMCW radar, a heterodyne architecture that involves different local oscillators and produces beat signals at the IF stage has often been chosen. The FMCW radar, however, has a chronic problem called leakage. In an earlier study, we proposed the stationary point concentration (SPC) technique to improve the signal-to-noise ratio (SNR) of small drones by reducing the increase in noise floor caused by leakage. We demonstrated that the proposed technique increases the SNR of small hovering drones in the 1-D power spectrum. In this article, we newly analyze the practical problems in the heterodyne FMCW radar system. One is the 2-D noise floor increase in the range-Doppler (r-D) map due to the leakage, and the other is unwanted Doppler shifts. Then, we propose an upgraded theory and realization method of the SPC technique for the detection of the small moving drone by improving the r-D map. We prove that the proposed method not only reduces the 2-D noise floor by mitigating the leakage but also removes the unwanted Doppler shifts by the phase calibration. Consequently, we show that the proposed method increases the SNR of the small moving drone and corrects its velocity information at the same time in the r-D map.