Multi-targets miss distance measurement based on a sequence of image processing techniques

Multi-targets miss distance measurement is studied in this paper based on a sequence of image processing techniques. Firstly, echoes from multi-targets are represented as a gray image with spectral intensity as its gray values by time-frequency transform. Then an adaptive threshold based on constant false alarm rate (CFAR) detection is devised to convert the gray image into a binary image. Further, a set of morphological operations is used to remove background noise from the binary image. Finally, miss distance parameters of multi-targets are obtained based on randomized Hough transform (RHT). The experimental results show the efficiency of proposed method