Mobile Communications Handbook
Mobile Communications Handbook
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Recursive Position Estimation in Sensor Networks
ICNP '01 Proceedings of the Ninth International Conference on Network Protocols
Range-free localization schemes for large scale sensor networks
Proceedings of the 9th annual international conference on Mobile computing and networking
On the effect of localization errors on geographic face routing in sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Error analysis of localization systems for sensor networks
Proceedings of the 13th annual ACM international workshop on Geographic information systems
Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
An Efficient Directed Localization Recursion Protocol for Wireless Sensor Networks
IEEE Transactions on Computers
Source Localization and Tracking Using Distributed Asynchronous Sensors
IEEE Transactions on Signal Processing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Joint multiple target tracking and classification in collaborative sensor networks
IEEE Journal on Selected Areas in Communications
| Hi-index | 0.00 |
In wireless sensor networks (WSNs), target tracking algorithms are often based on geographical information provided by a localization algorithm. However, the errors introduced by such algorithms may affect the performance of tasks that depend on such information. In this paper, we evaluate how errors resulting from actual localization algorithms affect two classical target tracking algorithms: the Kalman filter and the Particle filter. As a proof-of-concept, we choose two relevant localization algorithms for WSNs. The first is the RPE (Recursive Position Estimation), a pioneer iterative solution, and the second is the DPE (Directed Position Estimation), another iterative solution that evolved from the RPE reducing errors and the cost of its predecessor. Our results clearly indicate that the tracking algorithms successfully filter the noise introduced by the target-node distance estimation. However, they fail to eliminate the errors introduced by localization algorithms.