We consider the problem of robust localization of a set of underwater network nodes, based on pairwise distance measurements. Localization plays a key role in underwater network optimization, as accurate node positioning enables location-aware scheduling, data routing, and geo-referencing of the collected underwater sensor data. State-of-the-art graph localization approaches include variations of the classical multidimensional scaling (MDS) algorithm, modified to handle unlabelled, missing, and noisy distance measurements. In this paper, we present MAD-MDS, a robust method for graph localization from incomplete and outlier corrupted pair-wise distance measurements. The proposed method first conducts outlier excision by means of Median Absolute Deviation (MAD). Then, MAD-MDS performs rank-based completion of the distance matrix, to estimate missing measurements. As a last step, MAD-MDS applies MDS to the reconstructed distance matrix, to estimate the coordinates of the underwater network nodes. Numerical studies on both sparsely and fully connected network graphs as well as on data from past sea experiments corroborate that MAD-MDS attains high coordinate-estimation performance for sparsely connected network graphs and high corruption variance.
|Title of host publication||2021 5th Underwater Communications and Networking Conference, UComms 2021|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - 2021|
|Event||5th Underwater Communications and Networking Conference, UComms 2021 - Virtual, Online, Italy|
Duration: 31 Aug 2021 → 2 Sep 2021
|Name||2021 5th Underwater Communications and Networking Conference, UComms 2021|
|Conference||5th Underwater Communications and Networking Conference, UComms 2021|
|Period||31/08/21 → 2/09/21|
Bibliographical noteFunding Information:
This research was supported in part by the U.S. NSF under grants CNS-1753406 and OAC-1808582, by the U.S. AFOSR under YIP, by the MOST-BMBF German-Israeli Cooperation in Marine Sciences 2018-2020, and by the MOST action for Agriculture Environment and Water for year 2019.
© 2021 IEEE.
- Underwater acoustics
- corrupted distance measurements
- graph localization
- missing data
- robust MDS
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Signal Processing