Direction finding and mutual coupling estimation for uniform rectangular arrays

Wu, Han; Hou, Chunping; Chen, Hua; Liu, Wei; Wang, Qing

doi:10.1016/j.sigpro.2015.04.019

Cited by 42 publications

(26 citation statements)

References 23 publications

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“…To mitigate the mutual coupling effect, researchers have developed many 2D DOA estimation methods with unknown mutual coupling [3][4][5][6][7][8][9][10][11][12][13][14]. These methods can mainly be classified into three types: electromagnetic simulation [3,4,6], active calibration [7,8], and blind calibration [5,[9][10][11][12][13][14]. The electromagnetic simulation methods in [3,4] use the electromagnetic theory to calculate the mutual coupling and are high in accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…However, it sometimes converges slowly and may cause the increase in runtime and even wrong DOA estimations [9]. The second one is called RAnk REduction (RARE) technique [9,12,14], which exploits the special structure of coupled array manifold matrix to construct a cost function similar to that of MUSIC method and estimate the angles via minimizing the cost function. However, the angle estimation via RARE technique often needs 2 Mathematical Problems in Engineering multidimensional search, which is still high in computational complexity [14].…”

Section: Introductionmentioning

confidence: 99%

“…The second one is called RAnk REduction (RARE) technique [9,12,14], which exploits the special structure of coupled array manifold matrix to construct a cost function similar to that of MUSIC method and estimate the angles via minimizing the cost function. However, the angle estimation via RARE technique often needs 2 Mathematical Problems in Engineering multidimensional search, which is still high in computational complexity [14]. The third technique is named auxiliary sensor technique, which blindly compensates the mutual coupling at the cost of a few auxiliary sensors and generates new received array data [10,13].…”

Section: Introductionmentioning

confidence: 99%

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Computationally Efficient 2D DOA Estimation for L-Shaped Array with Unknown Mutual Coupling

Dong

Chang

2018

Mathematical Problems in Engineering

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Although L-shaped array can provide good angle estimation performance and is easy to implement, its two-dimensional (2D) direction-of-arrival (DOA) performance degrades greatly in the presence of mutual coupling. To deal with the mutual coupling effect, a novel 2D DOA estimation method for L-shaped array with low computational complexity is developed in this paper. First, we generalize the conventional mutual coupling model for L-shaped array and compensate the mutual coupling blindly via sacrificing a few sensors as auxiliary elements. Then we apply the propagator method twice to mitigate the effect of strong source signal correlation effect. Finally, the estimations of azimuth and elevation angles are achieved simultaneously without pair matching via the complex eigenvalue technique. Compared with the existing methods, the proposed method is computationally efficient without spectrum search or polynomial rooting and also has fine angle estimation performance for highly correlated source signals. Theoretical analysis and simulation results have demonstrated the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Computationally Efficient 2D DOA Estimation for L-Shaped Array with Unknown Mutual Coupling

Dong

Chang

2018

Mathematical Problems in Engineering

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“…Among different DOA estimation methods, 2-D DOA estimation of coherent source signals [6][7][8][9][10] has drawn increasing attentions. Conventional high-precision methods, such as MUSIC [11] and ESPRIT [12], have achieved exciting performance.…”

Section: Introductionmentioning

confidence: 99%

Efficient method of two-dimensional DOA estimation for coherent signals

Shi

Liu

et al. 2017

J Wireless Com Network

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An effective decoherence method called the fourth-order cumulants-based improved Toeplitz matrices reconstruction (FOC-ITMR) is addressed for two-dimensional (2-D) direction-of-arrival (DOA) estimation of coherent signals. To avoid the loss of the array's physical aperture, the FOC-ITMR method fully utilizes the information of received data from the whole two parallel uniform linear arrays (ULAs) and the changing reference element based on FOC. Compared with previous works, the proposed method can offer excellent decoherence performance in both white noise and color noise environments. In addition, the proposed algorithm can achieve automatic pair-matching without additional computation. The theoretical analysis and simulation results confirm the effectiveness of the proposed algorithm.

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“…In general, the EVSAs have the forms of uniform linear patterns [39], uniform rectangular patterns [40,41], L-shaped patterns [42] and uniform circular patterns [43], etc., all of which can be classified into concurrent EVSAs [31,33,34,36] and spatially separated EVSAs (SS-EVSAs) [44,45]. Various constraints such as the carrier profile, the electromagnetic and aerodynamic compatibility, however, should be taken into account comprehensively in practical systems.…”

Section: Introductionmentioning

confidence: 99%

DOA and Polarization Estimation Using an Electromagnetic Vector Sensor Uniform Circular Array Based on the ESPRIT Algorithm

et al. 2016

Sensors

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In array signal processing systems, the direction of arrival (DOA) and polarization of signals based on uniform linear or rectangular sensor arrays are generally obtained by rotational invariance techniques (ESPRIT). However, since the ESPRIT algorithm relies on the rotational invariant structure of the received data, it cannot be applied to electromagnetic vector sensor arrays (EVSAs) featuring uniform circular patterns. To overcome this limitation, a fourth-order cumulant-based ESPRIT algorithm is proposed in this paper, for joint estimation of DOA and polarization based on a uniform circular EVSA. The proposed algorithm utilizes the fourth-order cumulant to obtain a virtual extended array of a uniform circular EVSA, from which the pairs of rotation invariant sub-arrays are obtained. The ESPRIT algorithm and parameter pair matching are then utilized to estimate the DOA and polarization of the incident signals. The closed-form parameter estimation algorithm can effectively reduce the computational complexity of the joint estimation, which has been demonstrated by numerical simulations.

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Direction finding and mutual coupling estimation for uniform rectangular arrays

Cited by 42 publications

References 23 publications

Computationally Efficient 2D DOA Estimation for L-Shaped Array with Unknown Mutual Coupling

Computationally Efficient 2D DOA Estimation for L-Shaped Array with Unknown Mutual Coupling

Efficient method of two-dimensional DOA estimation for coherent signals

DOA and Polarization Estimation Using an Electromagnetic Vector Sensor Uniform Circular Array Based on the ESPRIT Algorithm

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