Ship Target Recognition Technology of Radar High Resolution Range Profile based on Machine Learning

doi:10.23940/ijpe.20.04.p5.537548

Abstract

Abstract: The traditional equal interval framing method for high resolution range profiles (HRRP) of ship targets has the problems of large computation and low recognition rate. Therefore, an adaptive framing method based on the power spectrum correlation coefficient is proposed, which can be used for non-equal framing according to the characteristics of the ship. Using this method can effectively reduce recognition and matching templates, greatly reduce the recognition time, and can achieve high efficiency in combat. On this basis, this paper further discusses the features in the time domain and frequency domain extracted from the one-dimensional range profiles of ten typical ships, and it verifies the effectiveness by support vector machine (SVM) and other typical classifiers. The conclusion shows that the recognition rate can be effectively improved by selecting appropriate features and classifiers for different targets.

Key words: high resolution range profile, non-equal framing, feature extraction, SVM

Bo Dan, Shan Gao, and Zhihong Ji. Ship Target Recognition Technology of Radar High Resolution Range Profile based on Machine Learning [J]. Int J Performability Eng, 2020, 16(4): 537-548.

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