Development of a wireless sensor network system for target tracking and surveillance

In most Wireless Sensor Network (WSN) target tracking systems in existence today, a significant number of low power sensor nodes are required to detect and to track the target. In many cases, a centralized architecture is employed in which the sensor nodes will send the information they have collect...

Full description

Saved in:
Bibliographic Details
Main Author: Toh, Yue Khing
Other Authors: Xie Lihua
Format: Theses and Dissertations
Language:English
Published: 2011
Subjects:
Online Access:https://hdl.handle.net/10356/43658
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
Description
Summary:In most Wireless Sensor Network (WSN) target tracking systems in existence today, a significant number of low power sensor nodes are required to detect and to track the target. In many cases, a centralized architecture is employed in which the sensor nodes will send the information they have collected to a more powerful fusion centre which wll in turn compute the estimated target trajectory. In the real world, centralized tracking in a large-scale WSN may not be feasible due to the possible failure of the fusion centre and the large communication delay in forwarding the measurement data to the fusion centre. Distributed target tracking techniques can be employed by tasking sensor nodes near to the target to perform sensing, target state estimation and selection of future tasking sensor nodes. In this thesis, the development of a prototype wireless sensor network test bed to demonstrate distributed target tracking using the Extended Kalman Filter (EKF) algorithm is discussed. In our approach, each sensor node is equipped with an active ultrasonic array for range finding and collaboration between the sensor nodes to accurately track a moving target. When a target is within the sensing range, a tasking sensor is elected to perform the task of tracking, target state estimation, sensor selection and data reporting of the target trajectory to the base station for visualization. Since all the computational tasks are performed by the sensor nodes, the need for a powerful fusion centre is effectively eliminated. Efficient ways of implementing the EKF and sensor selection scheme into these sensor nodes are also presented in this thesis. Problems arising from the limitations of a typical WSN such as limiting processing capability are investigated and ways to overcome these limitations are also discussed. As each sensor node has limited computation resources, the WSN is unable to accurately track the target due to the complexity of calculations in the EKF algorithm.