Signal processing of sensor node data for vehicle detection

Abstract

We describe an algorithm and experimental work for vehicle detection using sensor node data. Both acoustic and magnetic signals are processed for vehicle detection. We propose a real-time vehicle detection algorithm called the adaptive threshold algorithm (ATA). The algorithm first computes the time-domain energy distribution curve and then slices the energy curve using a threshold updated adaptively by some decision states. Finally, the hard decision results from threshold slicing are passed to a finite-state machine, which makes the final vehicle detection decision. Real-time tests and offline simulations both demonstrate that the proposed algorithm is effective.