Computationally efficient PUMA algorithm for two-dimensional frequency estimation of a single-tone via DFT beamspace transformation

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Detail(s)

Original languageEnglish
Title of host publication2016 CIE International Conference on Radar, RADAR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781509048281
Publication statusPublished - Oct 2016

Publication series

Name2016 CIE International Conference on Radar, RADAR 2016

Conference

Title2016 CIE International Conference on Radar, RADAR 2016
PlaceChina
CityGuangzhou
Period10 - 13 October 2016

Abstract

The problem of two-dimensional frequency estimation of a single-tone in white Gaussian noise is addressed in this paper, through a novel computationally efficient approach, referred to as beamspace principal-singular-vector utilization modal analysis (B-PUMA). Due to the centro-Hermitian structure inherent in the data model, the complex data matrix can be converted to real-valued via a DFT beamspace transformation. Thus, all calculations involved in the B-PUMA scheme are real-valued operations. Besides, to further boost the computational simplicity and estimation accuracy, an iteratively weighted least squares technique is employed to estimate the frequencies. Note that one iteration is sufficient for the B-PUMA to obtain comparable frequency estimates. Numerical results are included to demonstrate the effectiveness of our method.

Research Area(s)

  • Frequency estimation, Low-complexity, PUMA algorithm, Single-tone

Citation Format(s)

Computationally efficient PUMA algorithm for two-dimensional frequency estimation of a single-tone via DFT beamspace transformation. / Qian, Cheng; Xie, Junhao; Huang, Lei; So, H. C.

2016 CIE International Conference on Radar, RADAR 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 8059568 (2016 CIE International Conference on Radar, RADAR 2016).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review