A beamspace approach for 2-D localization of incoherently distributed sources in massive MIMO systems

Lv, Tiejun; Tan, Fengxiao; Gao, Hui; Yang, Shaoshi

doi:10.1016/j.sigpro.2015.10.020

Cited by 53 publications

(15 citation statements)

References 40 publications

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“…] denotes the 3MN − K small eigenvalues corresponding to the signal subspace matrix and noise subspace matrix, respectively. As U s and B span the same column space, there exists a non-singular matrix T satisfiesB = U s T (28) Define three selection matrices as follow…”

Section: Signal Modelmentioning

confidence: 99%

“…And the problem of coexist circular and noncircular CD sources is also detailed analysis. In [27] and [28], three-parallel ULAs and multiple uniform circular arrays are designed to locate the 2D angular parameters estimation for ID sources. In [29], [30], 2D ID and CD sources DOA estimation in massive MIMO system with uniform rectangular array are considered by using ESPRIT-like and unitary ESPRIT algorithm, respectively.…”

Section: Introductionmentioning

confidence: 99%

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Joint DOD and DOA Estimation for Coherently Distributed Sources in Bistatic MIMO Radar Based on Joint Diagonalization

et al. 2019

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In this paper, an efficient method via unitary joint diagonalization is proposed to deal with the coherently distributed sources in bistatic multiple-input multiple-output (MIMO) radar systems. In order to determine the direction of departure (DOD) and direction of arrival (DOA) of the coherently distributed source, a special array configuration is designed both for transmitter and receiver in bistatic MIMO radar system. Then, a new signal model can be obtained by utilizing the designed array characteristic and the rotational invariance relationship is constructed both for DOD and DOA. For the special rotational invariance relationship, the joint diagonalization technique is adopted to locate the coherently distributed sources and the angular parameters are automatically paired without multidimensional search process. The proposed joint diagonalization method can also determine the targets when multiple imping sources have the common DODs or DOAs. Finally, the approximate determined Cramer-Rao bound of the proposed estimator for the coherently distributed sources is also derived. And, additional numerical results are conducted to verify the effectiveness and superiority of the proposed method. INDEX TERMS Bistatic MIMO radar, unitary joint diagonalization, coherently distributed sources, direction of departure estimation, direction of arrival estimation.

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Section: Signal Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Joint DOD and DOA Estimation for Coherently Distributed Sources in Bistatic MIMO Radar Based on Joint Diagonalization

et al. 2019

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“…If only ID or CD sources exist in the incident signals, the separation of ID and CD sources can be avoided. It is worth noting that the part of the proposed approach for 2D DOA estimation of ID sources can also be applied to other scenarios by exploiting the rotational invariance property of the array’s structure, such as uniform linear arrays (ULAs) and uniform cylindrical arrays (UCyA) [ 13 ]. The part of the proposed approach for 2D-DOA estimation of the CD source has a similar characteristic, i.e.…”

Section: The Proposed Algorithmmentioning

confidence: 99%

“…In real applications, the effect of angular spread cannot be ignored due to the scattering, reflection, diffraction and refraction of the transmitted signal. If the signal model is regarded as a point source, the DOA estimation performance of the VMIMO system [ 12 , 13 ] will degrade significantly. Generally, a spatially-distributed source consists of hundreds of point sources [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Wearable Sensor Localization Considering Mixed Distributed Sources in Health Monitoring Systems

Wan

Han

Wang

et al. 2016

Sensors

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In health monitoring systems, the base station (BS) and the wearable sensors communicate with each other to construct a virtual multiple input and multiple output (VMIMO) system. In real applications, the signal that the BS received is a distributed source because of the scattering, reflection, diffraction and refraction in the propagation path. In this paper, a 2D direction-of-arrival (DOA) estimation algorithm for incoherently-distributed (ID) and coherently-distributed (CD) sources is proposed based on multiple VMIMO systems. ID and CD sources are separated through the second-order blind identification (SOBI) algorithm. The traditional estimating signal parameters via the rotational invariance technique (ESPRIT)-based algorithm is valid only for one-dimensional (1D) DOA estimation for the ID source. By constructing the signal subspace, two rotational invariant relationships are constructed. Then, we extend the ESPRIT to estimate 2D DOAs for ID sources. For DOA estimation of CD sources, two rational invariance relationships are constructed based on the application of generalized steering vectors (GSVs). Then, the ESPRIT-based algorithm is used for estimating the eigenvalues of two rational invariance matrices, which contain the angular parameters. The expressions of azimuth and elevation for ID and CD sources have closed forms, which means that the spectrum peak searching is avoided. Therefore, compared to the traditional 2D DOA estimation algorithms, the proposed algorithm imposes significantly low computational complexity. The intersecting point of two rays, which come from two different directions measured by two uniform rectangle arrays (URA), can be regarded as the location of the biosensor (wearable sensor). Three BSs adopting the smart antenna (SA) technique cooperate with each other to locate the wearable sensors using the angulation positioning method. Simulation results demonstrate the effectiveness of the proposed algorithm.

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“…Antenna arrays have long been in use in the field of wireless communications in both civilian and military applications. A fundamental problem in array signal processing is the Direction of Arrival (DOA) estimation in two dimensions (i.e., elevation and azimuth) [1][2][3][4] for source localization of multiple sources impinging on this array of antennas. Several methods were proposed in the literature for DOA estimation.…”

Section: Introductionmentioning

confidence: 99%

Parallel Factor-Based Model for Two-Dimensional Direction Estimation

Tayem¹,

Majeed²,

Hussain³

2017

International Journal of Antennas and Propagation

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Two-dimensional (2D) Direction-of-Arrivals (DOA) estimation for elevation and azimuth angles assuming noncoherent, mixture of coherent and noncoherent, and coherent sources using extended three parallel uniform linear arrays (ULAs) is proposed. Most of the existing schemes have drawbacks in estimating 2D DOA for multiple narrowband incident sources as follows: use of large number of snapshots, estimation failure problem for elevation and azimuth angles in the range of typical mobile communication, and estimation of coherent sources. Moreover, the DOA estimation for multiple sources requires complex pair-matching methods. The algorithm proposed in this paper is based on first-order data matrix to overcome these problems. The main contributions of the proposed method are as follows: (1) it avoids estimation failure problem using a new antenna configuration and estimates elevation and azimuth angles for coherent sources; (2) it reduces the estimation complexity by constructing Toeplitz data matrices, which are based on a single or few snapshots; (3) it derives parallel factor (PARAFAC) model to avoid pair-matching problems between multiple sources. Simulation results demonstrate the effectiveness of the proposed algorithm.

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A beamspace approach for 2-D localization of incoherently distributed sources in massive MIMO systems

Cited by 53 publications

References 40 publications

Joint DOD and DOA Estimation for Coherently Distributed Sources in Bistatic MIMO Radar Based on Joint Diagonalization

Joint DOD and DOA Estimation for Coherently Distributed Sources in Bistatic MIMO Radar Based on Joint Diagonalization

Wearable Sensor Localization Considering Mixed Distributed Sources in Health Monitoring Systems

Parallel Factor-Based Model for Two-Dimensional Direction Estimation

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