Nonlinear Feature Extraction of Acoustic Signals from Armored Vehicles Based on Chaos

摘要

Targets identification is a key technology in smart landmine. In order to effectively identify the armored vehicles, the features of acoustic signals radiated by these targets need to be extracted. 40 sample signals of 2 kinds of armored vehicles running under different conditions were collected by experiment. Since the acoustic signals radiated by vehicles had been proved to be chaotic, we extracted the features by chaotic dynamics on nonlinear theory. The reconstruction parameters of phase space from the time series (time-delay and embedding dimension) were obtained by improved C-C method, then the largest Lyapunov exponents were calculated with these parameters by Wolf method. The results show that the largest Lyapunov exponents can describe the nonlinear characters of the acoustic signals radiated by armored vehicles, as well as being characteristic parameters in targets identification for smart landmines.