The comparative study of three nonparametric methods of SAR tomography for building reconstruction

Mehrnoosh Omati, Mahmod Reza Sahebi*, H. Aghababaei

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)
253 Downloads (Pure)

Abstract

Over the past years, synthetic aperture radar (SAR) tomography (TomoSAR) has indicated significant potentials for three-dimensional (3D) reconstruction of buildings in urban areas. A large number of SAR images are thus required to perform tomographic inversions in non-parametric spectral estimators. To this end, in the case of a limited choice of SAR acquisitions, the present study aims to evaluate the capabilities of five non-parametric spectral estimation (SE) techniques, including linear prediction (LP), maximum entropy (ME), and minimum norm (MN), Capon, and beamforming (BF) in the tomographic reconstruction of urban environments. The performance analysis is carried out by using both simulated and real SAR datasets. The study results demonstrate that the proposed efficient LP estimator, minimizing the average output signal power over the antenna array elements, can separate the layover scatterers along the height direction. This low-computational SE method is thus able to clean side lobes while using a small number of observations. The proposed algorithms, as applied on TerraSAR-X strip-map images of the city of Tehran, Iran, verify the effectiveness of the non-parametric LP reconstruction technique for urban buildings. The estimated height of the scatterers also indicates that the LP estimator is similar to the field-based measurements once compared with ME, MN, Capon, and BF reconstruction methods.

Original languageEnglish
Pages (from-to)1743-1751
Number of pages9
JournalAdvances in space research
Volume69
Issue number4
Early online date8 Aug 2021
DOIs
Publication statusPublished - 15 Feb 2022

Keywords

  • LINEAR prediction (LP)
  • Maximum entropy (ME)
  • Minimum norm (MN)
  • Nonparametric spectral estimation methods
  • Synthetic aperture radar tomography (TomoSAR)
  • Urban building reconstruction
  • ITC-ISI-JOURNAL-ARTICLE
  • 22/1 OA procedure

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