The proliferation of wireless sensor networks (WSNs) has fostered the demand of context aware applications, among which localization plays a significant role. Localization in WSN is facing the challenges of (1) error and noise; (2) dynamic environments; (3) data packet loss. However, most presented localization algorithms are verified just by simulation but practical systems. To validate the localization algorithms realistically, a prototype WSN system equipped with a group of sensor nodes is deployed in this paper. A trilateration based optimization approaches and the Extended Kalman Filter (EKF) with position-velocity (PV) model are proposed and tested in the system comparing with the traditional trilateration. The experiment result indicates that the two proposed localization algorithms have much better accuracy than the traditional trilateration and, in a certain aspect, EKF with PV model is the most suitable algorithm among the three algorithms for localization in the prototype system.
In this paper, a real-time location feedback control system based on multi-sensor network is proposed for the precise control of a moving robot. The target tracking network system is a real test-bed that consists of a group of ultrasonic sensor nodes, a mobile robot and two laptops. In order to pursue excellent tracking performance and modify the robot’s trajectory promptly, Extended Kalman Filtering algorithm as well as a kind of scheduling scheme based on location is applied in the system. The experiment result validates the correctness of the Extended Kalman Filter (EKF) and shows that the target tracking network system is effective for robot feedback control.
In many wireless sensor networks (WSNs), target tracking is an essential application. This paper studies the real-time target tracking algorithm and the implementation for a multi-target real-time tracking system. The system consists of a wireless sensor network which includes several distributed ultrasonic sensor nodes and a monitoring base station, and two robots as moving targets. To avoid the conflicts in the network, a sensor node task scheduling scheme, and an adaptive clustering and inter-cluster negotiation network protocol (ACICN) are proposed for the system. To cope with distributed and asynchronous measurements, data synchronization and Extended Kalman Filter (EKF) location algorithm are studied for the system. The experiments show that the system can effectively track multi targets simultaneously.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.