Target CFAR Detection Method And Software Implementation With Two-Dimension Data For HFSWR

HFSWR can detect target vessels below sea level and low altitude aircraft byusing diffraction characteristics of high frequency electromagnetic wave propagationin the sea. In view of targets detection performance of HFSWR, more and morecountries develop HFSWR to monitor sea surface target vessels. Among them, theTarget detection of HFSWR is one of the key steps in the radar signal processing,target detection algorithm gets more and more attention of researchers, which CFARis one of the famous algorithms of target detection. HF radar target detection is animportant step in radar target detection, the detection performance directly affects thedetection performance of target detection and tracking. According to the scalability oftargets at a distance-Doppler spectrum,2-D reference window better estimates thebackground noise. In this paper, several problems based on the two-dimensionalCFAR detector were discussed:In the study of two-dimensional CFAR target detection method: Firstly, introducethe principle of one-dimensional CFAR detection based on curve fitting process.According to motive feature of target, the algorithm of target detection expands froma one-dimensional CFAR to two-dimensional CFAR detector. Due to the sensitive tomoving targets of HFSWR, using two-dimensional reference window can moreaccurately estimate the target background noise, in order to improve target detectionperformance. According to the expansibility of targets in the Doppler and distancespectrum from the theoretical analysis, combined with the large number of measureddata statistics, the paper gives the principle of the protection unit and other selectedparameters of two-dimensional reference window. Comparative analysis of CFARdetection of one-dimensional and two-dimensional CFAR by the measured data ofHFSWR, the two-dimensional CFAR detection can improve target detectionperformance by detection results.In CFAR processing, sea clutter and ground clutter based on the Range-Dopplerspectrum, and the development of the CFAR processing method based on curve fittingCFAR segmentation approach based on the overall curve fitting. According totwo-dimensional target CFAR detection method based on curve fitting principle andimplementation steps, based on the comparison and analysis of the difference betweenthe overall piecewise curve fitting and curve fitting CFAR processing. Compare and analysis the effects of two CFAR processing algorithms by using the measured data,and evaluate the performance of target detection by the AIS data. The results showthat the CFAR process based on segmented curve fitting is better than CFAR processalgorithm based on the overall curve fitting, especially for weak signal of target nearthe sea clutter.Finally, develop a software system about target CFAR detection of HFSWRbased on Matlab platform. The software integrates the CFAR detection algorithmswhich are implemented. The software can modify the parameters of detectionalgorithms of HFSWR which is selected, and display some parameters of the radar.The result of target detection and Doppler spectrum can be displayed in the real-time.AIS data can be read and the format of which can be converted to Range-Dopplerspectrum of formats, and can be displayed as needed, in order to compare thedifference of AIS targets and the result of radar target detection.