Name
Title | ||
|---|---|---|
RSSI Based Localization and Tracking in a Spatial Network System using Wireless Sensor Networks |
Abstract | ||
|---|---|---|
Localization has been a major research area in Wireless Sensor Networks (WSN) and has a rich literature of using many methods to estimate location accuracy. In WSN, localization systems use data from sensors which receive signals from beacons. The information received from a sensor node provides data about the location in the sequence. So it must be accurately estimated in a networked transportation system since the movement of data in the system involves both time and space coordinates. To estimate the location of the unknown nodes, wused the Received Signal Strength Indicator (RSSI), available on all wireless sensor nodes. The algorithm has been deloped to reduce the effect of non-deterministic delays using site-specific empirical models to achieve good location accuracy. As a measure of the propagation time of packets to reduce synchronization error, all nodes are synchronized using Round Trip Time and provide an accurate estimation of the node in time scale. Also, this paper describes the signal intensity based Extended Kalman filter for tracking a dynamically moving object from the optimized value of RSSI. Our method is compared with the existing methods and proved to be better under various circumstances of localization and tracking. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1007/s11277-021-09161-0 | WIRELESS PERSONAL COMMUNICATIONS |
Keywords | DocType | Volume |
Location sensing, RTT, Extended Kalman filter, Path loss model, RSSI, Packet reception rate | Journal | 123 |
Issue | ISSN | Citations |
1 | 0929-6212 | 1 |
PageRank | References | Authors |
0.36 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amutha Balakrishnan | 1 | 1 | 0.36 |
| Kadiyala Ramana | 2 | 1 | 2.39 |
| Karthick Nanmaran | 3 | 1 | 0.36 |
| R. Manikandan | 4 | 21 | 8.15 |
| Vidhyacharan Bhaskar | 5 | 1 | 1.38 |
| Suresh Kallam | 6 | 3 | 1.09 |