Sequential Naval Target Range Profile Classification Using Special Fusion Method

This study proposes a novel classification method for sequential range profile data using naval target range profile data. Classification marine targets using radar outputs has become an important research area in modern society. Several algorithms developed for sequential data classification. The Hidden Markov Model (HMM) is one of the most useful methods which uses such specific data. It is difficult to analyze sequential marine target range profile data because data itself contains many environmental effects. Data changes due to target orientation, weather condition, clutter effect and so on. These external effects change range profile data condition. We propose a classification method using fusion of sequential range profile data set to achieve better classification results.