Node localization is a fundamental requirement for deploying real wireless sensor network applications such as hospital logistics, environmental monitoring, and target surveillance. However, recently proposed algorithms still could not attain enough accuracy and are too costly. To improve the previous work, we describe a low cost, high accuracy, scalable, distributed localization algorithm which based on distance vectors. We assume that only few sensor nodes have known-locations (named as beacons) and the remaining nodes have unknown-locations (named as normal nodes). Each node updates its location from currently estimated distance vectors and given pairwise distances which are derived from received signal strength (RSS) measurements or time of arrival (TOA), and then passes this new location to neighbors until achieving enough convergence. Analysis, simulation and experimental results show that the proposed algorithm outperforms the other range-based algorithms. Specially the proposed algorithm on real-world experiment measurements, which contain unpredictable noise and shadowing, achieves better accuracy than the previous work do. The proposed method can perform well even with only few reference devices or anchors.
|Number of pages||6|
|Publication status||Published - 15 Dec 2008|
|Event||4th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2008 - Crown Plaza Hotel, Darling Harbour, Sydney, Australia|
Duration: 15 Dec 2008 → 18 Dec 2008
Conference number: 4
|Conference||4th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2008|
|Period||15/12/08 → 18/12/08|