Cognitive antenna selection for DOA estimation in automotive radar

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

17 Scopus citations


The performance of direction-of-Arrival (DOA) estimation is directly determined by the array aperture and the number of elements in the array. In many problems, a large array is available, but the number of receiving channels is limited, either by the system cost, or by the complexity. In this work, we address the problem of DOA estimation with a large number of antenna array elements and a small number of receivers, where the receivers are connected to the array elements via a reconfigurable switching matrix. A cognitive approach, named cognitive antenna selection (CASE), for sequentially switching the elements of the sensor array based on history observations and prior information is proposed. The antenna elements selection is via minimization of the conditional Bobrovski-Zakai bound on the mean-squared-error (MSE) of the DOA estimate. The performance of the proposed algorithm is evaluated in a problem of two sources via simulations and compared to two other non-Adaptive approaches. The proposed algorithm outperforms both of the considered algorithms in terms of MSE both asymptotically and in the threshold region.

Original languageEnglish
Title of host publication2016 IEEE Radar Conference, RadarConf 2016
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781509008636
StatePublished - 3 Jun 2016
Event2016 IEEE Radar Conference, RadarConf 2016 - Philadelphia, United States
Duration: 2 May 20166 May 2016

Publication series

Name2016 IEEE Radar Conference, RadarConf 2016


Conference2016 IEEE Radar Conference, RadarConf 2016
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications
  • Instrumentation


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