Localization accuracy and threshold network density for tracking sensor networks

Localization of target is one of the core issues in target tracking. This paper analyzes mathematical techniques of localization from the view point of error in position estimation. It is observed that error in position estimation reduces as the number of sensors making measurement to the target increase. Moreover, it is dependent on the positions of sensors making measurements to target node and on the error in measurement. The error in position estimation is least when the sensors making measurement to the node are well distributed in all the directions around the target node. It has been analyzed that after a particular number of well distributed nodes making measurements to the target node there is no significant reduction in position estimation error. Due to the random nature of deployment of sensors, saturation in accuracy is reached after around eight neighbors making measurement to the target. The paper makes a significant contribution by analyzing and establishing an optimum threshold bound for network density such that the accuracy in position estimation is maximum.