4.7 Article

Non-Line-of-Sight Moving Target Detection Method Based on Noise Suppression

期刊

REMOTE SENSING
卷 14, 期 7, 页码 -

出版社

MDPI
DOI: 10.3390/rs14071614

关键词

non-line-of-sight (NLOS); millimeter wave; moving target detection; noise suppression

资金

  1. National Natural Science Foundation of China [62071022]

向作者/读者索取更多资源

This article discusses the detection of non-line-of-sight moving targets using reflection of low-power transmission signals, focusing on the echo signal model construction and detection method based on millimeter-wave radar. Innovative techniques such as polynomial fitting and range gating methods are applied to suppress noise, while FFT and MUSIC methods are used to estimate target location and velocity. Simulation and processing of both simulated and actual data verify the effectiveness of the denoising methods proposed in the paper.
At the present time, most of existing security systems only detect and track targets in line-of-sight (LOS). However, in practice, the locations of targets are often out of the line of sight. This article focuses on the non-line-of-sight (NLOS) moving target detection with low-power transmission signals by reflection. There are two key problems, the weak target echo signal and the multipath effect. In terms of the issues, this paper constructs the echo signal model of the NLOS target. On the basis of the echo model, the detection method of NLOS moving target based on millimeter-wave radar comes up, which is of great theoretical value and important practical significance for indoor security. This paper innovatively applies the polynomial fitting method to suppress static noise and range gating method to suppress noise from other range gates. Then, the location and velocity of the target are estimated by two-dimensional fast Fourier transform (FFT) and the multiple signal classification (MUSIC) method. Furthermore, in order to verify the accuracy of the NLOS target echo signal model proposed in this paper, we respectively simulated two important parts of the signal in the model, the target echo signal and the direct backscattered signal of the intermediate interface, both of which are multipath signals. We counted the echo path length distribution in these two parts, and applied the NLOS target detection method to process them respectively. In addition, we also simulated the NLOS target echo signal and obtained actual data in the actual scene, and processed both the simulated data and the actual data. Comparing the results of target detection with and without denoising methods, the effectiveness of the two denoising methods proposed in this paper is verified.

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