In:
The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 152, No. 4_Supplement ( 2022-10-01), p. A109-A109
Kurzfassung:
Acoustically tracked subsurface floats provide insights into ocean complexity and were first deployed over 60 years ago. A standard tracking method uses a Least-Squares algorithm to estimate float trajectories based on acoustic ranging from moored sound sources. However, infrequent or imperfect data challenge such estimates. Acoustic tracking is currently the only feasible strategy for recovering float positions in the sea ice region, a focus of this study. Acoustic records recovered from under-ice floats frequently lack continuous sound source coverage. This is because environmental factors such as surface sound channels and sea ice attenuate acoustic signals, while operational considerations make polar sound sources difficult to deploy. Here we present a Kalman Smoother approach that, by including some estimates of float behavior, extends tracking to situations with more challenging data sets. The Kalman Smoother constructs dynamically constrained, error-minimized float tracks using all possible position data. The Kalman Smoother is applied to previously-tracked floats from the southeast Pacific (DIMES experiment), and the results are compared with existing trajectories constructed using the Least-Squares algorithm. The Kalman Smoother is also used to reconstruct the trajectories of a set of previously untracked, acoustically-enabled Argo floats in the Weddell Sea.
Materialart:
Online-Ressource
ISSN:
0001-4966
,
1520-8524
Sprache:
Englisch
Verlag:
Acoustical Society of America (ASA)
Publikationsdatum:
2022
ZDB Id:
1461063-2
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