Scattering center estimation of HRRP via atomic norm minimization

Yu Wang, Yuan Jiang, Yanhua Wang, Yang Li, Jia Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

As the one-dimensional projection of the echoes from scattering centers on a target along the radar line-of-sight, high range resolution profile (HRRP) has drawn great attention to automatic target recognition (ATR). Normally, features are extracted based on the strong scattering centers of HRRP. In recent years, several scattering center estimation methods have been proposed, such as Prony and orthogonal matching pursuit (OMP). Prony needs the number of scattering centers a priori and is sensitive to noise. Due to discretization, OMP may lead to the off-grid effect. In this paper, we propose to estimate the scattering centers via atomic norm minimization (ANM). Similar to OMP, ANM is a sparsity based approach, but the signal is modelled in continuous space, thus alleviating the basis mismatch. Simulation and experimental results demonstrate that ANM achieves higher accuracy in terms of both position and amplitude compared with OMP.

Original languageEnglish
Title of host publication2017 IEEE Radar Conference, RadarConf 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages135-139
Number of pages5
ISBN (Electronic)9781467388238
DOIs
Publication statusPublished - 7 Jun 2017
Event2017 IEEE Radar Conference, RadarConf 2017 - Seattle, United States
Duration: 8 May 201712 May 2017

Publication series

Name2017 IEEE Radar Conference, RadarConf 2017

Conference

Conference2017 IEEE Radar Conference, RadarConf 2017
Country/TerritoryUnited States
CitySeattle
Period8/05/1712/05/17

Keywords

  • Atomic norm minimization
  • HRRP
  • Scattering center estimation
  • Sparse representation

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