Research of Decision Classification of Underwater Object Echo based on Fuzzy Integral
Underwater object recognition is one of three crucial technologies of underwater acoustic equipments development. Only partial information describing objects can be acquired in single sensor that is not enough for object classification. Method of decision fusion of underwater object echo signal, based on theory of fuzzy integral and fuzzy measure, was studied to integrate primary recognition result from multi-general-sensors to raise recognition rate. Five features were extracted from data collected on the sea to prove the performance of this method, including modul maxima power feature of continual dissymmetry Gauss wavelet, crossing-zero feature, wavelet coefficient amplitude feature, Wigner feature and Walsh feature. Recognition rate is increased by approximately 9 percent