Abstract
Extracting effective features from ship-radiated noise is an important way to improve the detection and recognition performance of passive sonar. Complexity features of ship-radiated noise have attracted increasing amounts of attention. However, the traditional definition of complexity based on entropy (information stored in the system) is not accurate. To this end, a new statistical complexity measure is proposed in this paper based on spectrum entropy and disequilibrium. Since the spectrum features are unique to the class of the ship, our method can distinguish different ships according to their location in the two-dimensional plane composed of complexity and spectrum entropy (CSEP). To weaken the influence of ocean ambient noise, the intrinsic time-scale decomposition (ITD) is applied to preprocess the data in this study. The effectiveness of the proposed method is validated through a classification experiment of four types of marine vessels. The recognition rate of the ITD-CSEP methodology achieved 94%, which is much higher than that of traditional feature extraction methods. Moreover, the ITD-CSEP is fast and parameter free. Hence, the method can be applied in the real time processing practical applications.
Highlights
Feature extraction of ship-radiated noise has attracted considerable attention from sonar engineers because it is an important way to improve the detection and recognition performance of passive sonar [1,2,3,4,5,6].Due to the time-varying nature of the ocean medium and the interference of ocean ambient noise, it is challenging to extract effective characteristics from the received ship sound [7]
In order to weaken the influence of ocean noise, the de-noising procedure has been performed prior to the entropy estimation in recent studies, utilizing the famous variational mode decomposition (VMD), empirical mode decomposition (EMD), and its modifications [22,23,24,25]
Since the spectrum features are unique to the class of the ship, our method can distinguish different types of ships according to their location in the two-dimensional plane composed of complexity and spectrum entropy (CSEP)
Summary
Feature extraction of ship-radiated noise has attracted considerable attention from sonar engineers because it is an important way to improve the detection and recognition performance of passive sonar [1,2,3,4,5,6]. In order to comprehensively define the complexity, a statistical complexity measure called Lopez–Mancini–Calbert (LMC) complexity measure was proposed in Ricardo et al [29] by integrating the entropy H and disequilibrium Q (i.e., complexity C = HQ), where the disequilibrium denotes the distance between the given probability distribution and the equilibrium distribution of the accessible states of the system [29,30,31] (for a detailed description of the method, please check Section 2.2) By this definition, a given value of H can correspond to a range of possible.
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