The Research On Target Detection Technology For Marine Radar In Image Processing

Navigation radar target detection is essential to ship, radar target detection and automatic tracking are of great value in terms of military and civilian. Navigation radar plays an important role during ship navigation and collision avoidance. Navigation radar is effected by the clutter, noise, and the same frequency interference in practical applications, the radar echo signal and radar images have been seriously affected, the target detection rate needs to be improved, the practical problems of multi-spectral detection of early warning topics, in the following several aspects of the theoretical study and experimental verification.Firstly, the history and current situation of the marine radar and radar target detection are analyzed and summarized.Then it gives a detailed study plan for the topic multi-spectral target detection,radar image pre-processing research and target detection.Part of the radar image pre-processing:first the characteristics of radar images are analyzed and the radar image pre-processing methods are summed up from the references.Then it focused on the median filtering and wavelet denoising methods.In median filtering it discussed different template shapes and window size of the effect for image preprocessing. It analyzed the adaptive median filter. In wavelet threshold denoising, wavelet basis, decomposition scale and the choice of threshold function are discussed, and then use the median filtering,adaptive median filtering, wavelet threshold denoising, wavelet combined with the median and wiener filtering methods to process real radar images. From the PSNR point of view, the wavelet image denoising PSNR has greatly improved than the median filter and cross window median filter does better than the rectangular and diamond-shaped window.Wavelet with median or wiener has no advantage in PSNR compared to wave denoising alone.From visual effects, wiener filtering with wavelet is better than the wavelet denoising, through a comprehensive measure the optimal is sym4wavelet.Part of the radar target detection:analyzed threshold segmentation and edge detection.In threshold segmentation method the Otsu and Ridler calculated threshold is too large, the threshold obtained by KSW is too small, this paper presents an improved threshold calculation method, and finally use morphological filtering for processing; Edge detection used four different detection operator for processing, and test results were analyzed and summarized. Simulation results show that the threshold segmentation method of calculation based on the improved threshold detection results is better than the canny target edge detection method.Finally, target discrimination.Because the strong echo of the clutter in the radar images may be false alarms as the goal, there may be a target echo is too weak to be missed, this article take the following discriminant method:use improved threshold segmentation method to do target detection for three continuous radar images, any two of the three test results do "and" operator, and then proceed to do "or" operator, and finally combined with a priori knowledge of discrimination. The experimental results show that the method can accurately determine the target.