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Super-resolution direction finding at subarray level for coherent sources based on weighting network

  • Hang Hu*
  • , Xiuwei Jing
  • *Corresponding author for this work
  • School of Electronics and Information Engineering, Harbin Institute of Technology

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

Abstract

2-D subarray level super-resolution direction finding methods have important applications in phased array radars. This paper studies ML (Maximum Likelihood) method at subarray level suitable for coherent sources and gives the corresponding signal model. Applying simplified array manifolds can make calibration cost of phased array reduced largely. We post-process the digital subarray outputs by bringing in weighting network which increases the flexibility of array processing greatly. The simplified array manifold based on Gaussian patterns we constructed can overcome the limitations of DSAM (Direct Simplified Array Manifold) method that available direction estimation area can't be changed and the uninterested sidelobe sources can't be suppressed completely, but the cost is that the precision of direction finding drops. Simulation results demonstrate the validity of the proposed method.

Original languageEnglish
Title of host publicationISAPE 2006 - 2006 7th International Symposium on Antennas, Propagation and EM Theory, Proceedings
Pages74-77
Number of pages4
StatePublished - 2006
Externally publishedYes
Event2006 7th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2006 - Guilin, China
Duration: 26 Oct 200629 Oct 2006

Publication series

NameISAPE 2006 - 2006 7th International Symposium on Antennas, Propagation and EM Theory, Proceedings

Conference

Conference2006 7th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2006
Country/TerritoryChina
CityGuilin
Period26/10/0629/10/06

Keywords

  • Gaussian subarray patterns
  • ML method
  • Phased array at subarray level
  • Simplified array manifold
  • Super-resolution direction finding

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