改进雷达原始数据矩阵检测的CFAR算法

J. Perdoch, S. Gazovová, M. Pacek, Z. Matousek, J. Ochodnicky
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引用次数: 1

摘要

本文提出了在原始雷达数据矩阵上改进恒虚警率检测的算法。在4个具体优化案例中,应用Cell-Averaging CFAR (CA-CFAR)评估了雷达信号处理的加速效果。为了提高CA-CFAR的实效性,还对CA-CFAR中的杂波影响进行了降低。仿真设置采用不同信噪比(SNR)值的合成雷达信号。进一步证明,将CA-CFAR应用于由计算统计值组成的向量上,可以降低雷达信号处理的计算复杂度。
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CFAR Algorithm for Improving Detections on Radar Raw Data Matrices
This paper presents algorithms for improving Constant False Alarm Rate (CFAR) detections on raw radar data matrices. Acceleration of radar signal processing was assessed by the application of Cell-Averaging CFAR (CA-CFAR) in four specific optimization cases. Reduction of clutter impact in CA-CFAR was also implemented in order to enhance CA-CFAR operation. For the simulation setup, synthetic radar signals with different Signal-to-Noise Ratio (SNR) values were used. It is further demonstrated that radar signal processing computational complexity can be reduced by applying CA-CFAR on the vector consisting of computed statistical values.
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