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Estimation of Scalar Field Distribution in the Fourier Domain

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arxiv 2303.15700 v2 pith:6Y24RMZ3 submitted 2023-03-28 eess.SP

classification eess.SP
keywords fieldmodesalgorithmapproachdistributionestimationfouriermeasurements
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In this paper we consider the problem of estimation of scalar field distribution (e.g. pollutant, moisture, temperature) from noisy measurements collected by unmanned autonomous vehicles such as UAVs. The field is modelled as a sum of Fourier components/modes, where the number of modes retained and estimated determines in a natural way the approximation quality. An algorithm for estimating the modes using an online optimization approach is presented, under the assumption that the noisy measurements are quantized. The algorithm can also estimate time-varying fields through the introduction of a forgetting factor. Simulation studies demonstrate the effectiveness of the proposed approach.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. PINCH: Pipeline-Informed Noise Characterization in LIGO's Third Observing Run

    gr-qc 2025-05 conditional novelty 6.0 of 10

    PINCH uses support vector machines trained on clean GstLAL triggers to identify glitch-induced triggers, revealing class-specific patterns in how transient noise contaminates LIGO's third observing run.

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