Abstract

The detection of targets in military and security applications involves the usage of sensor systems which consist of a variety of sensors such as seismic, acoustic, magnetic and image ones as well. In order to extract signal features, which characterize particular targets, using of appropriate signal processing algorithms is required. Seismic signals can be considered as nonstationary and nonlinear signals especially in near-field seismic zone. Most of the signal processing algorithms assumed that signals are linear and stationary. However, in many cases this assumption is not valid, especially in case of seismic signals generated by moving vehicles, walking persons or gunfire activity. There are several methods which can be used for seismic signal processing, like short-time Fourier transform (STFT), Wavelet transform (WT) and Wigner-Ville distribution (WVD). The paper presents the concept of the seismic sensor system based on Micro-Electro-Mechanical-System (MEMS) sensor SF1500S. A dedicated to vehicle detection. The main part of the paper deals with application of the Hilbert-Huang transform (HHT) to seismic signal processing in time and time-frequency domain. In conclusion, the outcomes of experiments provide comparison of HHT and STFT efficiency in terms of seismic features description of moving vehicle.

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