Estimation of RVoG Scene Parameters by Means of PolInSAR With TanDEM-X Data: Effect of the Double-Bounce Contribution

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Title: Estimation of RVoG Scene Parameters by Means of PolInSAR With TanDEM-X Data: Effect of the Double-Bounce Contribution
Authors: Romero-Puig, Noelia | Lopez-Sanchez, Juan M. | Ballester-Berman, J. David
Research Group/s: Señales, Sistemas y Telecomunicación
Center, Department or Service: Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal | Universidad de Alicante. Instituto Universitario de Investigación Informática
Keywords: Agriculture | Bistatic radar | Double bounce (DB) | Forest | Polarimetric SAR interferometry (PolInSAR) | Rice | TanDEM-X | Vegetation
Knowledge Area: Teoría de la Señal y Comunicaciones
Issue Date: 30-Mar-2020
Publisher: IEEE
Citation: IEEE Transactions on Geoscience and Remote Sensing. 2020, 58(10): 7283-7304.
Abstract: This article evaluates the effect of the double-bounce (DB) decorrelation term that appears in single-pass bistatic acquisitions, as in the TanDEM-X system, on the inversion of scene parameters by means of polarimetric SAR interferometry (PolInSAR). The retrieval of all scene parameters involved in the Random Volume over Ground (RVoG) model (i.e., ground topography, vegetation height, extinction, and ground-to-volume ratios) is affected by this term when the radar response from the ground is dominated by the DB. The estimation error in all these parameters is analyzed by means of simulations over a wide range of system configurations and scene variables for both agricultural crops and forest scenarios. Simulations demonstrate that the inclusion of the DB term, which complicates the inversion algorithm, is necessary for the angles of incidence shallower than 30° to achieve an estimation error below 10% in vegetation height and to avoid a significant underestimation in the ground-to-volume ratios. At steep incidences, this decorrelation term does not affect the estimation of vegetation height and ground-to-volume ratios. Regarding the extinction, this parameter is intrinsically not well estimated, since most retrieved values are close to the initial guesses employed for the optimization algorithm, regardless of the use or not of the DB decorrelation term. Finally, these findings are compared with the experimental results from the TanDEM-X data acquired over the rice fields in Spain for the available system parameters (baseline and incidence angle) of the acquired data set.
Sponsor: This work was supported in part by the Spanish Ministry of Science, Innovation and Universities, the State Agency of Research (AEI), and in part by the European Funds for Regional Development (EFRD) under Project TEC2017-85244-C2-1-P. The work of Noelia Romero-Puig was supported in part by the Generalitat Valenciana and in part by the European Social Fund (ESF) under Grant ACIF/2018/204.
ISSN: 0196-2892 (Print) | 1558-0644 (Online)
DOI: 10.1109/TGRS.2020.2981756
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2020 IEEE
Peer Review: si
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