Target Detection and Classification Using Seismic and PIR Sensors

(U) Robust Personnel Detection using PIR and Seismic Sensors

In this paper we analyze the signals from passive infrared (PIR) and seismic sensors to detect people. The PIR data analysis is done to determine the radiation source such as a human or an animal based on the signal strength, slopes of the signals, the number of Fresnel lens zones crossed by the target. The seismic data analysis is done to ascertain whether the footsteps belong to a human or an...

Detection of Target and Implemented By Using Seismic and Pir Sensors

To monitor human activities, such as pedestrian motion and detection of intruders in a secure region we are widely using the Unattended ground sensors (UGS). The efficiency of UGSsystems is often limited by high false alarm rates, possibly dueto inadequacies of the underlying algorithms and limitationsof onboard computation. In this regard, this paper presents awavelet-based method for target d...

Target Tracking by Using Seismic Sensors

Feature Selection and Occupancy Classification Using Seismic Sensors

In this paper†, we consider the problem of indoor surveillance and propose a feature selection scheme for occupancy classification in an indoor environment. The classifier aims to determine whether there is exactly one occupant or more than one occupant. Data are obtained from six seismic sensors (geophones) that are deployed in a typical building hallway. Four proposed features exploit amplitu...

Seismic Target Classification Using a Wavelet Packet Manifold in Unattended Ground Sensors Systems

One of the most challenging problems in target classification is the extraction of a robust feature, which can effectively represent a specific type of targets. The use of seismic signals in unattended ground sensor (UGS) systems makes this problem more complicated, because the seismic target signal is non-stationary, geology-dependent and with high-dimensional feature space. This paper propose...