Name
Abstract | ||
|---|---|---|
Existing range-based localization schemes for underwater acoustic sensor networks (UASNs) rely on sufficient and accurate distance measurements. However, in practice, ranging packets are inevitably corrupted due to packet collisions and signal noises, resulting in missing and noisy distance measurements and further degrading localization performance significantly. In this paper, we propose a packet corruption tolerant localization algorithm to address this challenge. First, we design an energy-efficient mechanism to gather inter-node distance measurements and form partially observed Square Distance Matrix (SDM). Then, leveraging the intrinsic low-rank structure of SDM, the reconstruction of true SDM is formulated as a Frobenius-norm regularized matrix factorization problem and an improved Newton-Raphson method is designed to solve this problem. Finally, we apply Multi-Dimension Scaling technique to localize all the nodes based on the reconstructed SDM. Simulation results demonstrate that, our proposed algorithm outperforms the benchmark approaches in terms of localization accuracy, coverage and stability. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/WCNC45663.2020.9120644 | 2020 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC) |
Keywords | DocType | ISSN |
underwater acoustic sensor networks, packet corruption tolerant localization, low-rank matrix factorization, multi-dimension scaling | Conference | 1525-3511 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Keyong Hu | 1 | 4 | 4.18 |
| Xianglin Song | 2 | 0 | 0.34 |
| Zhongwei Sun | 3 | 4 | 2.76 |
| Hanjiang Luo | 4 | 136 | 13.25 |
| Zhongwen Guo | 5 | 4 | 3.85 |