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A modified KCCA for clutter separation in airborne MIMO SAR

  • School of Electronics and Information Engineering, Harbin Institute of Technology
  • Heilongjiang Province Administration of Surveying

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

Abstract

The signal or clutter separation in airborne MIMO SAR by the information of the direction-of-departure (DOD) or the direction-of-arrival (DOA) is able to be of benefit to the suppression of the 'unwanted' signals. As the signal separation performance after using the blocking matrix algorithm is greatly affected by the estimate deviation of the direction. Moreover, the direction of the 'unwanted' signal is unknown exactly in the practical application. To alleviate this situation, in this paper, a Modified Kernel Canonical Correlation Analysis (MKCCA) approach based on the blocking matrix approach is proposed. Firstly, the initial separation result is obtained by applying the blocking matrix approach. Then, we use KCCA as a further separation step. The azimuth searching result is adopted as the criteria of the separation performance. Simulation results demonstrate the excellent performance of the proposed approach, which could separate the signals or the clutter 'cleaner'.

Original languageEnglish
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6517-6520
Number of pages4
ISBN (Electronic)9781509033324
DOIs
StatePublished - 1 Nov 2016
Externally publishedYes
Event36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China
Duration: 10 Jul 201615 Jul 2016

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2016-November

Conference

Conference36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Country/TerritoryChina
CityBeijing
Period10/07/1615/07/16

Keywords

  • ICA
  • MIMO SAR
  • MKCCA
  • blocking matrix approach

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