Real time localization algorithm for maneuvering targets in non-uniform sensor networks

Wireless ad-hoc sensor networks have recently emerged as a premier research topic. They have great long term economic potential, ability to transform our lives, and pose many new system-building challenges. Sensor networks also pose a number of new conceptual and optimization problems. Some, such as location, deployment, and tracking, are fundamental issues, in that many applications rely on them for needed information. In this paper an efficient real time localization algorithm for multi-target tracking in non-uniform network is proposed. The proposed localization algorithm combines both multi-dimension scaling and least mean square methods. The tracking algorithm overcomes the low connectivity by utilizing both historical and current target data. The incoming measures have a conference number that utilize the use of historical data to overcome low connectivity and prediction of next position. The study presents the relation among connectivity, number of active sensor around the targets, tracking error, and the duration of sensor nodes activation. Several simulations of maneuvering targets are given to verify the proposed localization algorithm.