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Improving robustness of passive source localization via convex optimization based mode filtering
conference contribution
posted on 2023-05-23, 18:55 authored by Huang, L, Fan, S, Xu, W, Yang, TCModel-based passive source localization is known to be quite sensitive to model mismatch. In this paper, we present a new implementation based on matched-mode processing. Specifically we formulate mode filtering as a convex optimization problem, and ℓ1-regularized least squares is applied, which is robust in terms of the numerical implementation. Simulations with respective full-depth and partially-spanned apertures show that with sound speed mismatch in water column, the proposed method has a better or equal tolerance over traditional matched-field processing; with sound speed mismatch in sediment layer, combining with mode selection, where higher order modes strongly interacting with the bottom are removed, our approach has a slightly decreased bias. Overall the new method demonstrates improved robustness of passive source localization for the examples we studied.
History
Publication title
Proceedings of OCEANS ’16 MTS/IEEE ShanghaiPagination
2053-2057ISBN
978-1-4673-9724-7Department/School
Australian Maritime CollegePublisher
IEEE-Inst Electrical Electronics Engineers IncPlace of publication
USAEvent title
OCEANS ’16 MTS/IEEE ShanghaiEvent Venue
Shanghai, ChinaDate of Event (Start Date)
2016-04-10Date of Event (End Date)
2016-04-13Repository Status
- Restricted