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Statistical Regularization as an Alternative to Model Order Selection

Martin del Campo Becerra, Gustavo Daniel and Serafín García, Sergio Alejandro and Reigber, Andreas and Ortega Cisneros, Susana (2021) Statistical Regularization as an Alternative to Model Order Selection. In: International Geoscience and Remote Sensing Symposium (IGARSS). IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2021-07-12 - 2021-07-16, Brussels, Belgium. doi: 10.1109/IGARSS47720.2021.9553314.

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The correct functioning of parametric focusing techniques [e.g., MUltiple SIgnal Classification (MUSIC)] require a proper selection of the model order. For such aim, a methodology based on the Kullback-Leibler information criterion is commonly employed. These methods perform well due to its propensity to choose relatively large model orders, which tend to retrieve good-fitted responses when the data generating mechanism is more complex than the models used to fit. However, some solutions can be misleading, since only the most proper model order (i.e., the actual number of targets) guaranties best performance. As an alternative, this work suggests employing statistical regularization instead of model order selection (MOS) approaches. First, a model with large order is chosen to perform focusing via parametric methods; subsequently, statistical regularization is applied, seeking to attain good-fitted solutions. To demonstrate the capabilities of the addressed novel strategy, Synthetic Aperture Radar (SAR) Tomography (TomoSAR) is considered as application.

Item URL in elib:https://elib.dlr.de/141467/
Document Type:Conference or Workshop Item (Speech)
Title:Statistical Regularization as an Alternative to Model Order Selection
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Martin del Campo Becerra, Gustavo DanielUNSPECIFIEDhttps://orcid.org/0000-0003-1642-6068UNSPECIFIED
Serafín García, Sergio AlejandroUNSPECIFIEDhttps://orcid.org/0000-0003-2986-3793UNSPECIFIED
Reigber, AndreasUNSPECIFIEDhttps://orcid.org/0000-0002-2118-5046UNSPECIFIED
Date:July 2021
Journal or Publication Title:International Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Keywords:Maximum-likelihood, Model Order Selection (MOS), MUltiple SIgnal Classification (MUSIC), Synthetic Aperture Radar (SAR), Tomography.
Event Title:IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Event Location:Brussels, Belgium
Event Type:international Conference
Event Start Date:12 July 2021
Event End Date:16 July 2021
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Aircraft SAR
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute
Deposited By: Martin del Campo Becerra, Gustavo
Deposited On:23 Mar 2021 12:31
Last Modified:24 Apr 2024 20:41

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