CFAR detection method based on gray correlation characteristics in multi-target environment

Abstract

The invention discloses a CFAR detection method based on gray correlation characteristics in the multi-target environment. According to the method, a background window is adaptively thresholded for clutter truncation, and heterogeneous pixels in the background window are eliminated, and the real clutter is retained to the maximum extent; the maximum likelihood method is utilized to perform two-parameter (the log-mean and the logarithmic standard deviation) estimation on the truncated clutter, and two-dimensional lognormal distribution is utilized to achieve accurate modeling of gray joint probability density between adjacent pixels of the clutter; according to the given false alarm rate, the joint CFAR detection results with different pitches and different directions are obtained, and lastly, the joint CFAR detection results with the different pitches and the different directions are merged to realize CFAR detection based on gray correlation characteristics. The method is advantaged inthat statistical characteristics of the signal-to-noise ratio, gray-scale correlation and the truncated clutter are comprehensively utilized, on the condition that the target detection rate in the multi-target environment is improved, the false alarm rate can be effectively reduced, and the application value is relatively high.

Description

technical field [0001] The invention relates to the technical field of SAR image target detection, in particular to a CFAR detection method based on gray-scale correlation characteristics in a multi-target environment. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution imaging radar with all-weather and all-weather observation capabilities. The research and technology development of target detection and surveillance using SAR images has been highly valued in the field of marine remote sensing, and it is a research hotspot in the marine application of SAR images at this stage. [0003] With the change of weather and ocean wind speed, the sea conditions are very different, so the clutter presented in the SAR image will also have a huge difference. For these complex situations, an adaptive constant false alarm (CFAR) is needed in the detection process. )Detection method. The CFAR detection algorithm sets three sliding windows of target window, p...

AI Technical Summary

Problems solved by technology

The traditional SAR image CFAR detection method only utilizes the intensity information of isolated pixel points of the target, and does not fully explore the spatial correlation information between pixels inside the target, resulting in a large number of false alarms in the detection results, especially under complex background clutter.

[0007] In short, traditional CFAR detection methods are difficult to balance high detection rate and low false alarm rate in a multi-target environment, and it is urgent to develop a new CFAR detection method that takes into account both high detection rate and low false alarm rate.

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