A fast and automatically paired 2-D direction-of-arrival estimation with and without estimating the mutual coupling coefficients

Filik, Tansu; Tuncer, T. Engin

doi:10.1029/2009rs004260

Cited by 11 publications

(5 citation statements)

References 35 publications

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“…Scatter plots of the estimated azimuth and elevation are plotted in Figure 11, where the results have been averaged over 500 Monte Carlo runs. A challenge for further research is to incorporate the mutual coupling processing method to provide a more realistic scheme like the excellent algorithms [18,19,20] for applying sensor arrays.…”

Section: Simulation Resultsmentioning

confidence: 99%

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A Fast Algorithm for 2D DOA Estimation Using an Omnidirectional Sensor Array

Nie

Feng

et al. 2017

Sensors

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The traditional 2D MUSIC algorithm fixes the azimuth or the elevation, and searches for the other without considering the directions of sources. A spectrum peak diffusion effect phenomenon is observed and may be utilized to detect the approximate directions of sources. Accordingly, a fast 2D MUSIC algorithm, which performs azimuth and elevation simultaneous searches (henceforth referred to as AESS) based on only three rounds of search is proposed. Firstly, AESS searches along a circle to detect the approximate source directions. Then, a subsequent search is launched along several straight lines based on these approximate directions. Finally, the 2D Direction of Arrival (DOA) of each source is derived by searching on several small concentric circles. Unlike the 2D MUSIC algorithm, AESS does not fix any azimuth and elevation parameters. Instead, the adjacent point of each search possesses different azimuth and elevation, i.e., azimuth and elevation are simultaneously searched to ensure that the search path is minimized, and hence the total spectral search over the angular field of view is avoided. Simulation results demonstrate the performance characters of the proposed AESS over some existing algorithms.

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Section: Simulation Resultsmentioning

confidence: 99%

“…For each azimuth, they designed a new search-free rooting algorithm by expanding the array manifold into a double Fourier series. It is proved that even in the presence of severe mutual coupling [19,20], this hybrid approach can yield very robust 2D DOA estimation performances.…”

Section: Introductionmentioning

confidence: 99%

A Fast Algorithm for 2D DOA Estimation Using an Omnidirectional Sensor Array

Nie

Feng

et al. 2017

Sensors

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“…The array model in can be written for the m th antenna as

y_{m} (t) = α_{1} a_{m} ({normalΘ}_{1}) s (t) + \sum_{i = 2}^{N} α_{i} {\overset{a}{true}}_{m} ({normalΘ}_{i}, d_{i}) s (t) + n_{m} (t)

which can always be written as

y_{m} (t) = α_{1} a_{m} ({normalΘ}_{1}) s (t) (1 + β_{m 2} + β_{m 3} + \dots + β_{mN}) + n_{m} (t)

where β mi is a complex direction‐dependent coefficient. Then the array model for far‐field sources can be given as

boldy (t) = normalΓ (normalΘ) bolda (normalΘ) s (t) + boldn (t), t = 1, \dots, E

where Γ ( Θ ) is a direction‐dependent diagonal matrix and it represents the effect of near‐field multipaths on far‐field source as well as the mutual coupling [ Filik and Tuncer , ] between the antennas and gain/phase mismatch errors. Note that the model in has a single far‐field source and the artifacts from near‐field sources are represented by Γ ( Θ ).…”

Section: Direction Finding For a Far‐field Source With Multipath Compmentioning

confidence: 99%

“…where (Θ) is a direction-dependent diagonal matrix and it represents the effect of near-field multipaths on far-field source as well as the mutual coupling [Filik and Tuncer, 2010] between the antennas and gain/phase mismatch errors. Note that the model in (9) has a single far-field source and the artifacts from near-field sources are represented by (Θ).…”

Section: Direction Finding For a Far-field Source With Multipath Compmentioning

confidence: 99%

Far‐field DOA estimation and near‐field localization for multipath signals

Elbir

Tuncer

2014

Radio Science

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In direction finding and localization applications, multipath signals are important sources of error for parameter estimation. When the antenna array receives multipath reflections which are coherent with the far‐field line‐of‐sight signal, estimating the far‐ and near‐field components becomes an important problem. In this paper, a new method is proposed to estimate the direction‐of‐arrival (DOA) of the far‐field source and to localize its near‐field multipaths. Far‐field source DOA is estimated using calibration of the antenna array. A near‐to‐far transformation is proposed for the estimation of the near‐field source DOA angles. In order to estimate the near‐field range parameters, a compressive sensing approach is presented where a dictionary with near‐field sources with different ranges is employed. As a result, the proposed method estimates the far‐field and near‐field source DOAs as well as the range and the signal amplitudes of the near‐field sources. This method is evaluated using close‐to‐real world data generated by a numerical electromagnetic tool, where the array and transmitter are placed in an irregular terrain and array data are generated using full 3‐D propagation model. It is shown that unknown source parameters can be estimated effectively showing the potential of the proposed approach in applications involving high‐frequency direction finding and indoor localization.

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“…Still under the single‐mode assumption, from a signal‐processing point of view, ( Z + Z L ) can be regarded as a coupling matrix [ Gupta and Ksienski , 1983; Clerckx et al , 2007], whose effects are easily undone as soon as the array impedance matrix is known. Such coupling matrices can then be used to obtain direction‐of‐arrival estimates that account for the effects of mutual coupling [ Filik and Tuncer , 2010].…”

Section: Generalities About Mutual Coupling In Finite Arraysmentioning

confidence: 99%

A review on array mutual coupling analysis

2011

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An overview about mutual coupling analysis in antenna arrays is given. The relationships between array impedance matrix and embedded element patterns, including beam coupling factors, are reviewed while considering general‐type antennas; approximations resulting from single‐mode assumptions are pointed out. For regular arrays, a common Fourier‐based formalism is employed, with the array scanning method as a key tool, to explain various phenomena and analysis methods. Relationships between finite and infinite arrays are described at the physical level, as well as from the point of view of numerical analysis, considering mainly the method of moments. Noise coupling is also briefly reviewed.

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A fast and automatically paired 2-D direction-of-arrival estimation with and without estimating the mutual coupling coefficients

Cited by 11 publications

References 35 publications

A Fast Algorithm for 2D DOA Estimation Using an Omnidirectional Sensor Array

A Fast Algorithm for 2D DOA Estimation Using an Omnidirectional Sensor Array

Far‐field DOA estimation and near‐field localization for multipath signals

A review on array mutual coupling analysis

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