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Enhanced dual filter for floating wind lidar motion correction: The impact of wind and initial scan phase models

التفاصيل البيبلوغرافية
العنوان: Enhanced dual filter for floating wind lidar motion correction: The impact of wind and initial scan phase models
المؤلفون: Salcedo-Bosch, Andreu, Rocadenbosch, Francesc, Sospedra, Joaquim
المساهمون: Ministerio de Ciencia, Innovación y Universidades (España), European Commission, Agencia Estatal de Investigación (España), European Research Council, Generalitat de Catalunya, European Institute of Innovation and Technology, Ministerio de Economía y Competitividad (España)
بيانات النشر: Multidisciplinary Digital Publishing Institute
سنة النشر: 2022
المجموعة: Digital.CSIC (Consejo Superior de Investigaciones Científicas / Spanish National Research Council)
مصطلحات موضوعية: Floating doppler wind lidar, Apparent turbulence, Motion compensation, Kalman filter, Auto-regressive model, Random walk, Clustering, Power spectral density
الوصف: This article belongs to the Section Atmospheric Remote Sensing. ; An enhanced filter for floating Doppler wind lidar motion correction is presented. The filter relies on an unscented Kalman filter prototype for floating-lidar motion correction without access to the internal line-of-sight measurements of the lidar. In the present work, we implement a new architecture based on two cooperative estimation filters and study the impact of different wind and initial scan phase models on the filter performance in the coastal environment of Barcelona. Two model combinations are considered: (i) a basic random walk model for both the wind turbulence and the initial scan phase and (ii) an auto-regressive model for wind turbulence along with a uniform circular motion model for the scan phase. The filter motion-correction performance using each of the above models was evaluated with reference to a fixed lidar in different wind and motion scenarios (low- and high-frequency turbulence cases) recorded during a 25-day campaign at “Pont del Petroli”, Barcelona, by clustered statistical analysis. The auto-regressive wind model and the uniform circular motion phase model permitted the filter to overcome divergence in all wind and motion scenarios. The statistical indicators comparing both instruments showed overall improvement. The mean deviation increased from 1.62% (without motion correction) to −0.07% (with motion correction), while the root-mean-square error decreased from 1.87% to 0.58%, and the determination coefficient (R2 ) improved from 0.90 to 0.96. ; This research project was part of projects PGC2018-094132-B-I00 and MDM-2016-0600 (“CommSensLab” Excellence Unit) funded by Ministerio de Ciencia e Investigación (MCIN)/ Agencia Estatal de Investigación (AEI)/ 10.13039/501100011033/ FEDER “Una manera de hacer Europa”. The work of A. Salcedo-Bosch was supported by grant 2020 FISDU 00455 funded by Generalitat de Catalunya—AGAUR. The European Commission collaborated under projects H2020 ACTRIS-IMP (GA-871115) and H2020 ...
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: English
تدمد: 2072-4292
العلاقة: #PLACEHOLDER_PARENT_METADATA_VALUE#; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-094132-B-I00/ES/TELEDETECCION ATMOSFERICA MEDIANTE SENSORES COOPERATIVOS LIDAR, RADAR Y PASIVOS: APLICACIONES SOBRE TIERRA Y MAR PARA LA OBSERVACION ATMOSFERICA Y ENERGIA EOLICA OFF-SHORE/; info:eu-repo/grantAgreement/MINECO//MDM-2016-0600; info:eu-repo/grantAgreement/EC/H2020/871115; info:eu-repo/grantAgreement/EC/H2020/101008004; info:eu-repo/grantAgreement/EC/FP7/912054; Remote Sensing; Publisher's version; https://doi.org/10.3390/rs14194704Test; No; Remote Sensing 14(19): 4704 (2022); http://hdl.handle.net/10261/295346Test
DOI: 10.3390/rs14194704
الإتاحة: https://doi.org/10.3390/rs14194704Test
http://hdl.handle.net/10261/295346Test
حقوق: open
رقم الانضمام: edsbas.2B3751FE
قاعدة البيانات: BASE
الوصف
تدمد:20724292
DOI:10.3390/rs14194704