Stationary and Mobile Target Detection using Mobile Wireless Sensor Networks

TL;DR

This paper introduces a mobility model for mobile sensor networks that improves target detection and tracking efficiency, especially for stationary and mobile targets, by reducing overlap and increasing detection probability.

Contribution

The paper proposes a novel physical coverage-based mobility model that enhances detection performance and reduces the number of sensors needed in mobile wireless sensor networks.

Findings

Achieves desired detection probability with fewer sensors for stationary targets.

Provides higher detection probability for mobile targets compared to other models.

Improves coverage and detection efficiency in mobile sensor networks.

Abstract

In this work, we study the target detection and tracking problem in mobile sensor networks, where the performance metrics of interest are probability of detection and tracking coverage, when the target can be stationary or mobile and its duration is finite. We propose a physical coverage-based mobility model, where the mobile sensor nodes move such that the overlap between the covered areas by different mobile nodes is small. It is shown that for stationary target scenario the proposed mobility model can achieve a desired detection probability with a significantly lower number of mobile nodes especially when the detection requirements are highly stringent. Similarly, when the target is mobile the coverage-based mobility model produces a consistently higher detection probability compared to other models under investigation.