基于冗余小波变换的高频地波雷达目标检测算法

为了从高频地波雷达(High Frequency Surface Wave Radar, HFSWR)信号生成的复杂距离多普勒(Range Doppler, RD)图像中准确提取运动点目标, 提出了一种基于冗余小波变换(Redundant Discrete Wavelet Transformation, RDWT)的RD图像点目标检测算法.该算法根据点目标与海杂波、电离层杂波等特征的差异, 首先在距离方向进行自适应RDWT以去除海杂波和地杂波, 并在多普勒方向进行自适应RDWT以去除电离层杂波; 然后利用图像形态学运算对背景噪声进行了抑制; 最后进行阈值自适应分割以得到点目标.实验结果表明:该算法能有效抑制RD图像中的海杂波、电离层杂波和背景噪声, 能从复杂的RD图像中实现点目标的有效检测, 其检测性能优于改进的恒虚警率(Constant False Alarm Rate, CFAR)算法.

A target detection algorithm of HFSWR basedonredundant discrete wavelet transform

In order to accurately detect the small moving targets in complex range Doppler (RD)images generated from the received signal of high frequency surface wave radar (HFSWR), a point target detection algorithm of RD images based on redundant discrete wavelet transform (RDWT) is presented. Firstly, according to the feature differences among point targets, sea clutter, ionospheric clutter, etc, the sea clutter and ground clutter regions in a RD image are firstly removed based on adaptive RDWT in range direction, and then the ionospheric clutter regions are removed based on adaptive RDWT in Doppler frequency direction. Secondly, the background noise components are suppressed by using gray image morphology operation. Finally, the point targets are extracted by an adaptive thresholding segmentation process. The experimental results show that the proposed algorithm can effectively suppress sea clutter, and ionospheric clutter, and background noise in a RD image, and can extract and detect the point targets in a complex RD images effectively, and its detection rate is superior to that of the improved constant false-alarm rate (CFAR) algorithm.