用于HRR雷达在非高斯杂波中进行起伏目标检测的基于Hough变换的两种算法之比较

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。

Comparison of Two Algorithms for Detection of Fluctuating Targets in HRR Radars in Non-Gaussian Clutter Based on Hough Transform

In a HRR radar where the size of target is larger than wavelength of the radar and radar range resolution cells,and target returns from different scattering centres of the target produce different patterns in successive scans,make application of traditional methods of clutter suppression inefficient.Our solution for this problem is using the Hough transform.The Hough transform is a famous transform for finding curves in the images.In this thesis,we compare two algorithms based on Hough transform for radar detection,Conventional mode which maps points in the data space into curves in ρ-θ space.And the other mode which employs the slope-intercept parameter space Hough.The efficacy of the slope-intercept mode is verified by simulation.In comparison with the conventional case,the slope-intercept mode of Hough transform has a better performance.In this paper we investigate the performance of slope-intercept mode of Hough transform-based detector for HRR radar signals,in the presence of Rayleigh,Weibull,log normal and K distributed clutter for non-fluctuating and four types of Swerling targets.We also consider the effect of the velocity of target and number of pulses.The performance of target detection of Hough transform-based detector is analyzed through Monte-Carlo simulation runs.