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Detection Performance Analysis of Small Target Under Clutter Based on LFMCW Radar

机译:基于LFMCW雷达的小目标杂波探测性能分析

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Linear frequency modulation continuous wave (LFMCW) radar is a common sensor for detecting near-range targets. In this paper, the detection performance of low-small-slow unmanned aerial vehicle (LSS-UAV) is studied using the two-dimensional Fourier transform (2D-FFT) technology in the presence of dense architectural clutter via a LFMCW radar. Firstly, the beat frequency signal in time domain and frequency domain is analyzed, and the relevant factors which affect the speed detection and range detection performance are also covered. Secondly, the influence mechanism of clutter on range and velocity measurements of UAV is analyzed when extended to the ground clutter scenario. Finally, we use Monte-Carlo simulations to analyze the detection performance related to different parameters, including the radar parameters (frequency modulation ratio, bandwidth, moving target indication or not), target parameters (RCS, velocity), and clutter parameters (amplitude, spectral width) etc. The result shows that the detection in velocity dimension is crucial for discriminating LSS-UAV from strong clutter. And it is better to use large bandwidth signal and long-time accumulation technology to improve the target detection performance on strong clutter background.
机译:线性调频连续波(LFMCW)雷达是用于检测近距离目标的常用传感器。本文采用二维傅里叶变换(2D-FFT)技术,通过LFMCW雷达,在密集的建筑杂波情况下,研究了低小慢慢无人机(LSS-UAV)的检测性能。首先,分析了时域和频域的拍频信号,并涵盖了影响速度检测和测距性能的相关因素。其次,分析了杂波扩展到地面杂波场景时对无人机航程和速度测量的影响机理。最后,我们使用Monte-Carlo仿真来分析与不同参数相关的检测性能,包括雷达参数(调频比,带宽,是否有移动目标指示),目标参数(RCS,速度)和杂波参数(幅度,结果表明,速度维的检测对于区分LSS-UAV和强杂波至关重要。最好使用大带宽信号和长时间累积技术来改善在强杂波背景下的目标检测性能。

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