Array Uncertainties and Auto-calibration

Willerton, Marc; Venieris, Evangelos; Manikas, A.

doi:10.1142/9781783262755_0007

Cited by 4 publications

(8 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…That is, since calibration can be performed up to a common complex factor among the transceivers, a convenient approach is to assume r 1 = t 1 = 1 where such transceiver is considered a reference 5 . The CRLB for the remaining elements are calculated accordingly.…”

Section: A Reference Element For Calibrationmentioning

confidence: 99%

“…A method for transceiver calibration based on signals exchanged among antenna elements of the own array was proposed in [5]. Array shape estimation is performed in a first stage, followed by estimation of the transceiver responses.…”

Section: Introduction M Assive Multiple-input Multiple Output (Mimmentioning

confidence: 99%

“…Array shape estimation is performed in a first stage, followed by estimation of the transceiver responses. However, the method proposed in [5] rely on the assumption of spherical wave propagation between antenna elements, which is not suitable for our case due to the strong mutual coupling between BS antennas.…”

Section: Introduction M Assive Multiple-input Multiple Output (Mimmentioning

confidence: 99%

See 2 more Smart Citations

A receive/transmit calibration technique based on mutual coupling for massive MIMO base stations

Vieira

Rusek

Tufvesson

2016

2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

View full text Add to dashboard Cite

Section: A Reference Element For Calibrationmentioning

confidence: 99%

Section: Introduction M Assive Multiple-input Multiple Output (Mimmentioning

confidence: 99%

Section: Introduction M Assive Multiple-input Multiple Output (Mimmentioning

confidence: 99%

See 1 more Smart Citation

A receive/transmit calibration technique based on mutual coupling for massive MIMO base stations

Vieira

Rusek

Tufvesson

2016

2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

View full text Add to dashboard Cite

“…According to (13), Φ x affects imaging in two ways. First, a displacement Δx n occurs in the along-track point spread function p x (·).…”

Section: B Effects Of δX N and φ X On Imagingmentioning

confidence: 99%

“…If we use the aforementioned calibration method, the position errors can be calibrated within an accuracy of 0.02 mm, where the reconstructed 3-D image exhibits good performance in the same manner as the error-free case. There are also many other array calibration methods, such as pilot calibration, self-calibration, and adaptive calibration [13], and their applications to virtual element position error correction in LASAR will be the main focus of our future research.…”

Section: F Calibration Considerationmentioning

confidence: 99%

Statistical Analysis of the Effects of Virtual Element Position Errors on Airborne Down-Looking LASAR 3-D Imaging

Han

Bao

Tan

et al. 2015

IEEE Geosci. Remote Sensing Lett.

View full text Add to dashboard Cite

In order to achieve 3-D imaging with an airborne down-looking linear-array synthetic aperture radar (LASAR), a uniform virtual antenna array may be obtained by aperture synthesis of the cross-track sparse multiple-input-multiple-output array. However, the actual 3-D imaging quality is unavoidably degraded by errors in the virtual element position. In this letter, we investigate the effects of these errors on the forms and the degrees of image quality degradation by decomposing the error-related stochastic processes via an orthogonal transform based on discrete Legendre polynomials. It should be noted that these analyses are helpful for designing a LASAR system and providing a reference for specifying the requisite precision of measurement devices and calibration methods. Finally, we briefly consider the use of calibration methods to eliminate the effects of errors.Index Terms-Linear-array synthetic aperture radar (LASAR), phase error, 3-D imaging, virtual element.

show abstract

Underdetermined DOA Estimation of Quasi-Stationary Signals Using a Partly-Calibrated Array

Wang

et al. 2017

Sensors

View full text Add to dashboard Cite

Quasi-stationary signals have been widely found in practical applications, which have time-varying second-order statistics while staying static within local time frames. In this paper, we develop a robust direction-of-arrival (DOA) estimation algorithm for quasi-stationary signals based on the Khatri–Rao (KR) subspace approach. A partly-calibrated array is considered, in which some of the sensors have an inaccurate knowledge of the gain and phase. In detail, we first develop a closed-form solution to estimate the unknown sensor gains and phases. The array is then calibrated using the estimated sensor gains and phases which enables the improved DOA estimation. To reduce the computational complexity, we also proposed a reduced-dimensional method for DOA estimation. The exploitation of the KR subspace approach enables the proposed method to achieve a larger number of degrees-of-freedom, i.e., more sources than sensors can be estimated. The unique identification condition for the proposed method is also derived. Simulation results demonstrate the effectiveness of the proposed underdetermined DOA estimation algorithm for quasi-stationary signals.

show abstract

Array Uncertainties and Auto-calibration

Cited by 4 publications

References 18 publications

A receive/transmit calibration technique based on mutual coupling for massive MIMO base stations

A receive/transmit calibration technique based on mutual coupling for massive MIMO base stations

Statistical Analysis of the Effects of Virtual Element Position Errors on Airborne Down-Looking LASAR 3-D Imaging

Underdetermined DOA Estimation of Quasi-Stationary Signals Using a Partly-Calibrated Array

Contact Info

Product

Resources

About