In this paper, we propose the noncircular estimation signal parameters via rotational invariance techniques(NC-ESPRIT) algorithm as a two-dimension direction of arrival(2D-DOA) estimation algorithm for uniform rectang...
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ISBN:
(纸本)9781510819085
In this paper, we propose the noncircular estimation signal parameters via rotational invariance techniques(NC-ESPRIT) algorithm as a two-dimension direction of arrival(2D-DOA) estimation algorithm for uniform rectangular array. Compared to conventional circular ESPRIT algorithm, the proposed algorithm exploits the property of noncircular signals through data expansion, so that the array aperture is doubled. Therefore, the angle estimation performance is superior to that of the circular ESPRIT algorithm. Moreover the proposed algorithm has no spectral peak searching and the two-dimension angle estimates can be paired automatically. Simulation results illustrate the effectiveness and improvement of the proposed algorithm.
In this paper, we investigate the downlink achievable ergodic spectral efficiency (SE) of a single-cell multi-user millimeter wave system, in which a uniform rectangular array is used at the base station (BS) to serve...
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In this paper, we investigate the downlink achievable ergodic spectral efficiency (SE) of a single-cell multi-user millimeter wave system, in which a uniform rectangular array is used at the base station (BS) to serve multiple single-antenna users. We adopt a three-dimensional channel model by considering both the azimuth and elevation dimensions under single-path propagation. We derive the achievable ergodic SE for this system in with maximum ratio transmission precoding. This analytical expression enables the accurate and quantitative evaluation of the effect of the number of BS antennas, signal-to-noise ratio (SNR), and the crosstalk (squared inner product between different steering vectors) which is a function of the angles of departure (AoD) of users and the inter-antenna spacing. Results show that the achievable ergodic SE logarithmically increases with the number of BS antennas and converges to a value in the high SNR regime. To improve the achievable ergodic SE, we also propose a user scheduling scheme based on feedback of users' AoD information and obtain the maximum achievable ergodic SE. Furthermore, we consider a dense user scenario where every user's AoD becomes nearly identical and then derive the system's minimum achievable SE.
A precise model of the array response is required to maintain the performance of direction-of-arrival (DOA) estimation. When modeling errors are present or the sensor environment is time-varying, autocalibration becom...
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A precise model of the array response is required to maintain the performance of direction-of-arrival (DOA) estimation. When modeling errors are present or the sensor environment is time-varying, autocalibration becomes necessary. In this paper, the problem of phase autocalibration for uniform rectangular array (URA) geometries is considered. For the case with a single source, a simple and robust least-squares algorithm for joint 2-D DOA estimation and phase calibration is presented. When performing phase autocalibration with a URA, the phase and DOA parameters cannot be identified together without ambiguity. This problem is discussed and a suitable remedy is suggested. An approximate Cramer-Rao bound and analytical expressions for the mean squared error performance of the proposed estimator are presented. The proposed algorithm for phase autocalibration is extended for the case with multiple sources. The results are evaluated using a representative body of simulations.
A novel two-dimensional (2-D) direct-of-arrival (DOA) and mutual coupling coefficients estimation algorithm for uniform rectangular arrays (URAs) is proposed. A general mutual coupling model is first built based on ba...
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A novel two-dimensional (2-D) direct-of-arrival (DOA) and mutual coupling coefficients estimation algorithm for uniform rectangular arrays (URAs) is proposed. A general mutual coupling model is first built based on banded symmetric Toeplitz matrices, and then it is proved that the steering vector of a URA in the presence of mutual coupling has a similar form to that of a uniform linear array (ULA). The 2-D DOA estimation problem can be solved using the rank-reduction method. With the obtained DOA information, we can further estimate the mutual coupling coefficients. A better performance is achieved by our proposed algorithm than those auxiliary sensor-based ones, as verified by simulation results. (C) 2015 Elsevier B.V. All rights reserved.
A computationally efficient two-dimensional (2-D) direction-of-arrival (DOA) estimation method for uniform rectangular arrays is presented. A preprocessing transformation matrix is first introduced, which transforms b...
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A computationally efficient two-dimensional (2-D) direction-of-arrival (DOA) estimation method for uniform rectangular arrays is presented. A preprocessing transformation matrix is first introduced, which transforms both the complex-valued covariance matrix and the complex-valued search vector into real-valued ones. Then the 2-D DOA estimation problem is decoupled into two successive real-valued one-dimensional (1-D) DOA estimation problems with real-valued computations only. All these measures lead to significantly reduced computational complexity for the proposed method.
To maintain the performance of direction-of-arrival (DOA) estimation, an accurate model of the array response is required. In a time-varying sensor environment, this is only possible with autocalibration. For a unifor...
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ISBN:
(纸本)9781457705397
To maintain the performance of direction-of-arrival (DOA) estimation, an accurate model of the array response is required. In a time-varying sensor environment, this is only possible with autocalibration. For a uniform linear array, there exist algorithms for autocalibration which exploit the Toeplitz structure of the unperturbed spatial covariance matrix. In this paper, we develop an autocalibration method for 2-D DOA estimation with a uniform rectangular array, in which we exploit a Toeplitz-block Toeplitz structure. We present a simple algorithm for gain and phase estimation, discuss ambiguity problems and evaluate the performance using simulations.
In this study, the authors propose a fast quadrilinear decomposition algorithm for estimation of the directions-of-arrival and polarisations of the incident sources via a uniform rectangular array of electromagnetic v...
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In this study, the authors propose a fast quadrilinear decomposition algorithm for estimation of the directions-of-arrival and polarisations of the incident sources via a uniform rectangular array of electromagnetic vector sensors (EMVSs). Conventional quadrilinear alternating least squares (QALS), involves computationally intensive Khatri-Rao products in each iteration, to update the parameter matrices (factors). Moreover, QALS is more likely to fall in a local minimum and tends to take more steps before an acceptable solution, which further slows down the convergence and often mis-converges, thereby yielding meaningless results. To preserve the quadrilinearity, they arrange the measurements as a four-dimensional (4D) data (fourth-order tensor), from which a third-order sub-tensor (3D slice) can be obtained by fixing one index along any dimension. These slices are used to create new cost functions that are alternately minimised while updating the factors until convergence. They show that the rows of parameter matrices form the diagonal elements of a tensor, which capture the internal quadrilinearity of data and significantly reduce the cost function in few iterations only. Simulation results verify that the authors' algorithm holds faster convergence, does not mis-converge, provides parameter estimation accuracy similarly to the QALS and superior of the Estimation of Signal Parameters via Rotational Invariance Technique and propagator method.
One important application in the field of adaptive antenna array processing used in recent wireless communications systems, such as cognitive radio applications, is the direction of arrival (DoA) estimation. The exist...
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ISBN:
(纸本)9781509064779
One important application in the field of adaptive antenna array processing used in recent wireless communications systems, such as cognitive radio applications, is the direction of arrival (DoA) estimation. The existing works suggest that the N-x x N-y, two dimensional (2 - D) antenna array is almost surely able to recover up to [N-x/2] [N-y/2] two dimensional (2 - D) DoA. In this paper, a new 2 - D (azimuth and elevation) DoA estimation method using a minimum sparse ruler based rectangulararray of antenna is evaluated. The minimal sparse ruler is used to determine which antennas that have to be deactivated and which antennas that should be remain active. Therefore, it is possible to deactivate some antennas in the uniform rectangular array (URA) leading to a sparse rectangulararray (SpRA). While minimizing the reduction in the quality of the resulting DoA estimation with SpRA, the selection and averaging procedure are adopted to tackle these elements. This approach is possible for uncorrelated sources as the covariance matrix of the impinging signals on the URA contains redundant elements. The selection and averaging procedures are adopted to tackle these elements. These steps are followed by the execution of the MUSIC algorithm to compute the 2-D DoA estimates. The simulation study shows that it is possible to employ only 25-antennas in SpRA in order to estimate the azimuth (phi) and the elevation (theta) angles of up to 19 sources. The combinations of (phi) and (theta) is drawn from the range of 0 degrees <= phi <= 180 degrees and 0(0) <= theta <= 90 degrees. The separation in azimuth and elevation angles between sources is at least 10 degrees.
In this paper, joint frequency and 2-D direction of arrival (DOA) estimation at sub-Nyquist sampling rates of a multi-band signal (MBS) comprising of P disjoint narrowband signals is considered. Beginning with a stand...
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ISBN:
(纸本)9780992862671
In this paper, joint frequency and 2-D direction of arrival (DOA) estimation at sub-Nyquist sampling rates of a multi-band signal (MBS) comprising of P disjoint narrowband signals is considered. Beginning with a standard uniform rectangular array (URA) consisting of M = M-x x M-y sensors, this paper proposes a simpler modification by adding a N - 1 delay channel network to only one of the sensor. A larger array is then formed by combining the sub-Nyquist sampled outputs of URA and the delay channel network, referred to as the difference space-time (DST) array. Towards estimating the joint frequency and 2-D DOA on this DST array, a new method utilizing the 3-D spatial smoothing for rank enhancement and a subspace algorithm based on ESPRIT is presented. Furthermore, it is shown that an ADC sampling frequency of f(s) >= B suffices, where B is the bandwidth of the narrow-band signal. With the proposed approach, it is shown that O(MN/4) frequencies and their 2-D DOAs can be estimated even when all frequencies alias to the same frequency due to sub-Nyquist sampling. Appropriate simulation results are also presented to corroborate these findings.
This paper presents the model of satellite planar array, and interference localization via direction of arrival(DOA) estimation. We derive a dimension reduction DOA estimaton algorithm therein. The proposed algorithm,...
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ISBN:
(纸本)9783038353140
This paper presents the model of satellite planar array, and interference localization via direction of arrival(DOA) estimation. We derive a dimension reduction DOA estimaton algorithm therein. The proposed algorithm, which only requires a one-dimensional local searching, can avoid the high computational cost within two-dimensional multiple signal classification (2D-MUSIC) algorithm. We illustrate that the proposed algorithm has better angle estimation performance than estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm, and has very close angle estimation performance to 2D-MUSIC algorithm. Furthermore, our algorithm requires no extra pairing. Simulation results present the usefulness of our algorithm.
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