USE OF SEISMIC SIGNALS' TIME PARAMETERS FOR MOVING OBJECTS RECOGNITION BY REMOTE SEISMIC DEVICES

Abstract

The aim of the work is to determine improved temporal methods for recognition of a moving person and vehicles and the effectiveness of their use by remote autonomous seismic devices. Currently, the most promising seismic devices for the detection and recognition of moving objects are considered to be devices that use spectral and spectral-temporal methods of seismic signal processing. This is mainly due to their high probability of the objects correct recognition. But the use of these methods leads to a significant increase in the information and energy consumption, which is extremely undesirable for the remote autonomous seismic devices and systems based on them. The article proposes to use the energy-efficient temporal methods of seismic signal processing and the improved recognition methods based on the use of temporal parameters of seismic signals to recognize moving objects in these cases. To implement this and to reduce false alarms of the seismic devices, when animals penetrate into their detection zone, in contrast to the known devices, a temporal selection criterion related to the motion characteristics of medium and large animals is additionally introduced into the recognition method of a moving person. The testing of the recognition methods has shown that the proposed methods allow autonomous seismic devices to have both the insignificant power consumption and a significant value of the probability of the moving objects correct recognition. Compared with spectral, time-frequency and statistical methods for moving object recognition, the proposed temporal methods are much simpler and allow to design the remote autonomous seismic devices with minimal energy consumption.