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在HRR雷达中,当目标尺寸大于雷达波长和雷达距离分辨单元时,在连续扫描过程中从目标不同散射中心返回的目标回波会产生不同的方向图,使传统杂波抑制方法无效。提出采用Hough变换来解决这个问题。Hough变换是一种在图像中识别曲线的著名变换。比较了两种基于Hough变换的雷达检测算法,一是将数据空间中的点映射到ρ-θ空间中的曲线的传统模式,另一种模式采用斜率-截距参数空间Hough变换。斜率-截距模式的效率通过仿真进行验证。与传统模式相比,Hough变换的斜率-截距模式的性能更好。针对非起伏目标及四种Swerling类目标,研究了在瑞利分布、Weibull分布、对数正态分布和K分布杂波下,Hough变换检测器的斜率-截距模式对HRR雷达信号的检测性能。还研究了目标速度和脉冲数的影响。通过Monte-Carlo仿真对Hough变换检测器的目标检测性能进行了分析。
In the HRR radar, when the target size is larger than the radar wavelength and the radar distance resolution unit, the target echoes returned from different scattering centers of the target during the continuous scanning will generate different patterns to invalidate the traditional clutter suppression method. Hough transform is proposed to solve this problem. Hough Transform is a well-known transformation that identifies curves in an image. Two kinds of radar detection algorithms based on Hough transform are compared. The first one is the traditional model which maps the points in data space to the curves in ρ-θ space. The other model uses the Hough transform of slope-intercept parameter space. The efficiency of the slope-intercept mode is verified by simulation. The Hough Transform’s slope-intercept mode performs better than the traditional mode. For non-undulation targets and four kinds of Swerling targets, the detection performance of the Hough Transform detector’s slope-intercept mode for HRR radar signals under Rayleigh, Weibull, Lognormal and K distribution clutter is studied. . The effects of target speed and number of pulses were also studied. The target detection performance of Hough transform detector is analyzed by Monte-Carlo simulation.