Blind Calibration and DOA Estimation With Uniform Circular Arrays in the Presence of Mutual Coupling

Lin, Min; Yang, Liu

doi:10.1109/lawp.2006.878898

Cited by 152 publications

(136 citation statements)

References 14 publications

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“…As can be seen from Eqs. (23) and (27), the first M 0 eigenvalues and the second M 0 eigenvalues are mutual conjugate, which respectively are λ 1i (i = 1, 2, . .…”

Section: Mls-mi-esprit Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

2-D Doa Estimation of LFM Signals for Uca Based on Time-Frequency Multiple Invariance Esprit

Cui¹,

Wu²,

Huang³

et al. 2017

PIER M

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Abstract-In order to improve the angle measurement precision with a low computational complexity, a 2-D direction of arrival (DOA) estimation algorithm UCA-TF-MI-ESPRIT is proposed in this paper. This algorithm is based on the mode space algorithm and the time-frequency (TF) multiple invariance rotational invariance technique (MI-ESPRIT). Firstly, a uniform circular array (UCA) is equivalent to a virtual uniform linear array (ULA) by utilizing mode-space algorithm. Then, the smoothed pseudo Wigner-Ville distribution (SPWVD) of the ULA output is calculated. The spatial time-frequency matrix can be obtained through the average of multiple time-frequency points in the time-frequency plane, and the signal subspace can also be obtained through using eigen decomposition. Then a simple and effective subarray dividing approach is proposed, and the multiple rotational invariant equation of the array is obtained by using the Bessel function. Finally, the closed-form solution is obtained using multi-leastsquares (MLS) criterion so that the 2-D DOA estimation of LFM signals in UCA is completed. The simulation results verify the effectiveness of the algorithm proposed by this paper.

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“…As can be seen from Eqs. (23) and (27), the first M 0 eigenvalues and the second M 0 eigenvalues are mutual conjugate, which respectively are λ 1i (i = 1, 2, . .…”

Section: Mls-mi-esprit Algorithmmentioning

confidence: 99%

“…So, it has been widely used, and the DOA estimation of UCA becomes an important issue nowadays [1][2][3][4][5][27][28][29]. In the field of direction finding, the methods based on egien-subspace have been getting lots of attention for the excellent estimation performance.…”

Section: Introductionmentioning

confidence: 99%

2-D Doa Estimation of LFM Signals for Uca Based on Time-Frequency Multiple Invariance Esprit

Cui¹,

Wu²,

Huang³

et al. 2017

PIER M

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show abstract

“…This issue can be divided into several topics: i) array geometry [3][4][5][6][7][8]; ii) estimation method [9][10][11][12]; iii) match of separately obtained estimations [13][14][15][16][17][18][19][20][21][22][23][24][25][26] (Note that parameter match operation is a key step in the 2-D DOAs estimation problem, and the failure in pairing will cause severe performance degradation); iv) the mutual coupling effect among multiple sensors can not be ignored since it may cause severe performance degradation [27][28][29][30][31][32][33][34][35][36][37], as shown in the linear array [32,35], the circular array [27][28][29], the rectangular array [30], and the hexagon array [31]; and v) the estimation failure problem, i.e., the elevation estimatorα l = asin( γ 2 l +φ 2 l λ/(2πd)) may fail since the estimation of {γ l , φ l } causes γ 2 l +φ 2 l λ/(2πd) > 1, especially when elevation angle is between 70 • and 90 • that is often encountered in mobile communication, as shown in ...…”

Section: Introductionmentioning

confidence: 99%

Two L-Shaped Array-Based 2-D Doas Estimation in the Presence of Mutual Coupling

Liang¹,

Liu²

2011

PIER

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Abstract-Recent research on the array geometrical configuration shows that the two L-shaped array (TLSA) has a lower CramerRao Low-Bound (CRLB) of two-dimensional (2-D) directions-of-arrival (DOAs) estimation than other array configurations. However, in this array configuration, there are some problems to note: i) three electric angles are independently obtained from three uniformly linear subarrays on three axes, so they must be matched before solving elevation and azimuth angles from them; ii) Similar to other array geometries, the effect of mutual coupling in the TLSA on the estimation performance cannot be ignored; and iii) the conventional elevation estimators may encounter estimation failure.In this paper, we develop a new TLSA-based 2-D DOAs estimation algorithm. The key points of this paper are: i) using some particularly selecting matrices, a trilinear model is constructed to compensate the effect of mutual coupling on three subarrays. In addition, the steering vector is restored using the trilinear alternating least square method; ii) 2-D DOAs are estimated from the properly chosen elements of the restored steering vector to avoid pairing parameters and the severe performance degradation resulted from the failure in pairing; and iii) a new elevation estimator is designed to avoid estimation failure. Simulation results are presented to validate the performance of the proposed method.

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“…The problem is that these adaptive DOA estimation algorithms are sensitive to array Mutual Coupling (MC) and such an effect needs to be removed in order to achieve a high performance in an actual system [5]. Many efforts have been made to reduce or compensate for this effect on Array [5,6,7,8,9,10].…”

Section: Introductionmentioning

confidence: 99%

Non- Sensitive Matrix Pencil method against mutual coupling

Azarbar

Dadashzadeh

Bakhshi

2011

IEICE Electron. Express

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Abstract:A new Matrix Pencil (MP) method including mutual coupling effects based on a Uniform Linear Array (ULA) is presented. By setting a group of elements as auxiliary on each side of the ULA, it can accurately estimate the Direction of Arrival (DOA) using a single snapshot of data and the effect of mutual coupling can be eliminated by the inherent mechanism of the proposed method. Theoretical analysis and simulation results demonstrate the effectiveness of the proposed algorithm. Keywords: matrix pencil, mutual coupling, DOA, ULA Classification: Microwave and millimeter wave devices, circuits, and systems References

show abstract

Blind Calibration and DOA Estimation With Uniform Circular Arrays in the Presence of Mutual Coupling

Cited by 152 publications

References 14 publications

2-D Doa Estimation of LFM Signals for Uca Based on Time-Frequency Multiple Invariance Esprit

2-D Doa Estimation of LFM Signals for Uca Based on Time-Frequency Multiple Invariance Esprit

Two L-Shaped Array-Based 2-D Doas Estimation in the Presence of Mutual Coupling

Non- Sensitive Matrix Pencil method against mutual coupling

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