Optimization of the Vertical Wavenumber for PolInSAR Inversion Performance Based on Numerical CRLB Analysis
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Published:2023-11-10
Issue:22
Volume:15
Page:5321
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Affiliation:
1. College of Computer and Information Engineering, Nanjing Tech University, Nanjing 211816, China
Abstract
A number of advanced SAR missions have been planned to launch, which can operate in fully polarimetric SAR interferometry mode to acquire structural parameters of global forests. Before the PolInSAR mission, the system configuration of vertical wavenumber kz must be carefully designed because it has a significant impact on the inversion performance. To minimize the estimation error of forest height caused by the system error from the future PolInSAR campaigns, it is valuable for us to optimize the vertical wavenumber. To quantitatively investigate the impact of kz on PolInSAR inversion performance, this paper proposes the optimization of kz based on the Cramér–Rao Lower Bound (CRLB) analysis. Extensive numerical CRLB simulations have been conducted to analyze the impact of several parameters, including extinction level, incident angle, and system decorrelation, etc., on the optimum kz. Finally, by minimizing the simulated CRLB, the numerical optimum kz maps are provided for the system engineers to easily design the system parameters.
Funder
Natural Science Foundation of China Shanghai Academy of Space-flight Technology Research Key Laboratory of Radar Imaging and Microwave Photonics Postgraduate Research & Practice Innovation Program of Jiangsu Province
Subject
General Earth and Planetary Sciences
Reference37 articles.
1. Moreira, A., Hajnsek, I., Krieger, G., Papathanassiou, K., and Eineder, M. (2009, January 26–30). Tandem-L: Monitoring the Earth’s Dynamics with InSAR and Pol-InSAR. Proceedings of the 4th International Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry (PolInSAR 2009), Frascati, Italy. 2. Krieger, G., Hajnsek, I., Papathanassiou, K.P., Eineder, M., Younis, M., Zan, F.D., Lopezdekker, P., Huber, S., Werner, M., and Prats, P. (2010, January 4–8). Tandem-L: A Mission for Monitoring Earth System Dynamics with High Resolution SAR Interferometry. Proceedings of the European Conference on Synthetic Aperture Radar, Pasadena, CA, USA. 3. The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle;Quegan;Remote Sens. Environ.,2011 4. Quegan, S., Chave, J., Dall, J., Toan, T.L., and Williams, M. (2012, January 22–27). The science and measurement concepts underlying the BIOMASS mission. Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Munich, Germany. 5. Focusing the L-Band Spaceborne Bistatic SAR Mission Data Using a Modified RD Algorithm;Li;IEEE Trans. Geosci. Remote Sens.,2019
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