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一种用于MTI三角调频连续波多目标跟踪雷达的两相交错脉冲重复间隔和慢时间信号积分的信号处理算法。

A Signal Processing Algorithm of Two-Phase Staggered PRI and Slow Time Signal Integration for MTI Triangular FMCW Multi-Target Tracking Radars.

作者信息

Tang Taiwen, Wu Chen, Elangage Janaka

机构信息

Defence Research and Development Canada, Ottawa Research Centre, Ottawa, ON K1A 0Z4, Canada.

出版信息

Sensors (Basel). 2021 Mar 25;21(7):2296. doi: 10.3390/s21072296.

DOI:10.3390/s21072296
PMID:33805966
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8037985/
Abstract

In this paper, a novel signal processing algorithm for mitigating the radar blind speed problem of moving target indication (MTI) for frequency modulated continuous wave (FMCW) multi-target tracking radars is proposed. A two-phase staggered pulse repetition interval (PRI) solution is introduced to the FMCW radar system. It is implemented as a time-varying MTI filter using twice the hardware resources as compared to a uniform PRI MTI filter. The two-phase staggered PRI FMCW waveform is still periodic with a little more than twice the period of the uniform PRI radar. We also propose a slow time signal integration scheme for the radar detector using the post-fast Fourier transformation Doppler tracking loop. This scheme introduces 4.77 dB of extra signal processing gain to the signal before the radar detector compared with the original uniform PRI FMCW radar. The validation of the algorithm is done on the field programmable logic array in the loop test bed, which accurately models and emulates the target movement, line of sight propagation and radar signal processing. A simulation run of tracking 16 s of the target movement near or at the radar blind speed shows that the total degradation from the raw post-fast Fourier transformation received signal to noise ratio is about 2 dB. With a 20 dB post-processing signal to noise ratio of the proposed algorithm for the moving target at around a 20 km range and with about a -3.5 dB m radar cross section at a 1.5 GHz carrier frequency, the tracking errors of the two-dimensional angles with a 4×4 digital phased array are less than 0.2 degree. The range tracking error is about 28 m.

摘要

本文提出了一种用于缓解调频连续波(FMCW)多目标跟踪雷达的动目标显示(MTI)雷达盲速问题的新型信号处理算法。将一种两相交错脉冲重复间隔(PRI)解决方案引入到FMCW雷达系统中。它被实现为一个时变MTI滤波器,与均匀PRI MTI滤波器相比,使用的硬件资源是其两倍。两相交错PRI FMCW波形仍然是周期性的,其周期略大于均匀PRI雷达周期的两倍。我们还为雷达探测器提出了一种基于快速傅里叶变换后多普勒跟踪环的慢时间信号积分方案。与原始均匀PRI FMCW雷达相比,该方案在雷达探测器之前的信号上引入了4.77 dB的额外信号处理增益。该算法在环路测试平台上的现场可编程逻辑阵列上进行了验证,该平台准确地建模和模拟了目标运动、视线传播和雷达信号处理。对接近或处于雷达盲速的目标运动进行16 s跟踪的模拟运行表明,从原始快速傅里叶变换接收信号到噪声比的总降级约为2 dB。对于在20 km左右范围内运动的目标,在所提出算法的后处理信噪比为20 dB且在1.5 GHz载波频率下雷达截面积约为 -3.5 dB m的情况下,使用4×4数字相控阵时二维角度的跟踪误差小于0.2度。距离跟踪误差约为28 m。

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本文引用的文献

1
A Low-Complexity FMCW Surveillance Radar Algorithm Using Two Random Beat Signals.使用两个随机拍频信号的低复杂度 FMCW 监测雷达算法。
Sensors (Basel). 2019 Jan 31;19(3):608. doi: 10.3390/s19030608.
2
Long-Range Drone Detection of 24 G FMCW Radar with E-plane Sectoral Horn Array.基于 E 面扇形喇叭天线的 24GHz FMCW 雷达的远程无人机探测。
Sensors (Basel). 2018 Nov 28;18(12):4171. doi: 10.3390/s18124171.
3
Design of an FMCW radar baseband signal processing system for automotive application.用于汽车应用的调频连续波雷达基带信号处理系统设计。
Springerplus. 2016 Jan 18;5:42. doi: 10.1186/s40064-015-1583-5. eCollection 2016.