Incoherent DOA estimation in uniform antenna arrays with inordinate spacing using a subband hopping approach

Alireza Shapoury, Erchin Serpedin

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1 Citation (Scopus)

Abstract

Given a certain transmission frequency, the Shannon spatial sampling limit defines an upper bound for the antenna element spacing. Beyond this bound, the exceeded ambiguity avoids correct estimation of the signal parameters (i.e., array manifold crossing). In this survey, the problem of simultaneous signal and direction-of-arrival (DOA) estimation of broadband sources is addressed when the element spacing of a uniform array antenna (uniform linear array (ULA)) is inordinate. It is illustrated that one can resolve the aliasing ambiguity by utilizing the inherent frequency diversity of the broadband sources. An algorithm based on maximum likelihood estimation (MLE) has been developed to estimate the transmitted data signal and the DOA of each source. Through confirmatory simulation, it is shown that the performance gain of the proposed setup is potentially significant, specifically under a low signal-to-noise ratio (SNR) and when the transmitters are closely spaced. This relaxes the stringent maximum element-spacing constraint of ULAs pertinent to the upper-bound frequency of transmission and suggests that the element spacing - which in practical applications results in detrimental element coupling - can be conveniently increased, in particular under wide transmission spectrum and low SNR (e.g., license-free communication). A method similar to the frequency hopping approach (i.e., subband hopping) is utilized for the problem of source associations and identification. In the sequel, a suboptimal subspace-based algorithm is proposed and its performance is investigated. An approximate expression for the estimation error has also been developed to gauge the behavior of the proposed setup.

Original languageEnglish
Pages (from-to)17-39
Number of pages23
JournalCircuits, Systems, and Signal Processing
Volume28
Issue number1
DOIs
Publication statusPublished - 2009
Externally publishedYes

Fingerprint

Direction of Arrival
Antenna Arrays
Direction of arrival
Antenna arrays
Spacing
Signal to noise ratio
Frequency hopping
Maximum likelihood estimation
Broadband
Error analysis
Gages
Transmitters
Upper bound
Frequency Hopping
Linear Array
Aliasing
Antennas
Sampling
Estimation Error
Maximum Likelihood Estimation

Keywords

  • Array signal processing
  • Direction-of-arrival estimation
  • Maximum likelihood estimation
  • Uniform linear arrays

ASJC Scopus subject areas

  • Signal Processing
  • Applied Mathematics

Cite this

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title = "Incoherent DOA estimation in uniform antenna arrays with inordinate spacing using a subband hopping approach",
abstract = "Given a certain transmission frequency, the Shannon spatial sampling limit defines an upper bound for the antenna element spacing. Beyond this bound, the exceeded ambiguity avoids correct estimation of the signal parameters (i.e., array manifold crossing). In this survey, the problem of simultaneous signal and direction-of-arrival (DOA) estimation of broadband sources is addressed when the element spacing of a uniform array antenna (uniform linear array (ULA)) is inordinate. It is illustrated that one can resolve the aliasing ambiguity by utilizing the inherent frequency diversity of the broadband sources. An algorithm based on maximum likelihood estimation (MLE) has been developed to estimate the transmitted data signal and the DOA of each source. Through confirmatory simulation, it is shown that the performance gain of the proposed setup is potentially significant, specifically under a low signal-to-noise ratio (SNR) and when the transmitters are closely spaced. This relaxes the stringent maximum element-spacing constraint of ULAs pertinent to the upper-bound frequency of transmission and suggests that the element spacing - which in practical applications results in detrimental element coupling - can be conveniently increased, in particular under wide transmission spectrum and low SNR (e.g., license-free communication). A method similar to the frequency hopping approach (i.e., subband hopping) is utilized for the problem of source associations and identification. In the sequel, a suboptimal subspace-based algorithm is proposed and its performance is investigated. An approximate expression for the estimation error has also been developed to gauge the behavior of the proposed setup.",
keywords = "Array signal processing, Direction-of-arrival estimation, Maximum likelihood estimation, Uniform linear arrays",
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AU - Serpedin, Erchin

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AB - Given a certain transmission frequency, the Shannon spatial sampling limit defines an upper bound for the antenna element spacing. Beyond this bound, the exceeded ambiguity avoids correct estimation of the signal parameters (i.e., array manifold crossing). In this survey, the problem of simultaneous signal and direction-of-arrival (DOA) estimation of broadband sources is addressed when the element spacing of a uniform array antenna (uniform linear array (ULA)) is inordinate. It is illustrated that one can resolve the aliasing ambiguity by utilizing the inherent frequency diversity of the broadband sources. An algorithm based on maximum likelihood estimation (MLE) has been developed to estimate the transmitted data signal and the DOA of each source. Through confirmatory simulation, it is shown that the performance gain of the proposed setup is potentially significant, specifically under a low signal-to-noise ratio (SNR) and when the transmitters are closely spaced. This relaxes the stringent maximum element-spacing constraint of ULAs pertinent to the upper-bound frequency of transmission and suggests that the element spacing - which in practical applications results in detrimental element coupling - can be conveniently increased, in particular under wide transmission spectrum and low SNR (e.g., license-free communication). A method similar to the frequency hopping approach (i.e., subband hopping) is utilized for the problem of source associations and identification. In the sequel, a suboptimal subspace-based algorithm is proposed and its performance is investigated. An approximate expression for the estimation error has also been developed to gauge the behavior of the proposed setup.

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