Utilization of a unitary transform for efficient computation in the matrix pencil method to find the direction of arrival

Yilmazer, Nuri; Koh, Jinhwan; Sarkar, Tapan K.

doi:10.1109/tap.2005.861567

Cited by 144 publications

(80 citation statements)

References 14 publications

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“…1 and 2, RMSE of both estimates is plotted (in dB) versus signal to noise ratio (SNR) which is defined as SNR= 10 log(1/σ 2 n ) where σ 2 n is the variance of ν(n). The Cramer-Rao Lower Bound (CRLB) of the estimators is also calculated as in [2] and shown in these figures. UMP method.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The most computationally expensive part of MP method is singular value decomposition (SVD) of a complex data matrix. In [2], a UMP method was developed which reduces the computational effort to about 1 4 by converting complex data matrix into a real matrix. If some priori information about the DOAs is available, as in radar applications, then reduced dimension processing of data is possible as in beamspace MU-SIC, ESPRIT and CB-DOA methods [3,4,5].…”

Section: Introductionmentioning

confidence: 99%

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Beamspace matrix pencil method for direction of arrival estimation

Khan

Tufail

2009

IEICE Electron. Express

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Abstract:In this paper, we propose DFT Beamspace Matrix pencil (BMP) method for direction of arrival estimation (DOA). The DFT beamspace approach has the advantage of reduced computational complexity due to converting complex computations (in Matrix Pencil method) into real ones along with the inherent ability to operate in a reduced beam-space in situations where some priori information is available about the DOAs. Furthermore, a novel Multiple Invariance BMP (MBMP) method is also developed and it is shown through simulations that its reduced beamspace version has comparable performance to the existing Unitary Matrix Pencil method (UMP) with lower computational cost.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Beamspace matrix pencil method for direction of arrival estimation

Khan

Tufail

2009

IEICE Electron. Express

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“…L is chosen between N/3 and N/2 for efficient noise filtering [12]- [13]. The variance of the estimated values of R i and Z i will be minimal if the values of L are chosen in this range [14]. From the matrix Y, we can define two sub-matrixes, say…”

Section: Matrix Pencil Based On Uniform Linear Arraymentioning

confidence: 99%

Matrix Pencil for Direction Of Arrival Using Smart Antenna

Ihedrane¹,

SeddikBri²

2016

IJET

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Abstract-The main purpose of the smart antenna system is the selection of smart algorithms for adaptive array to estimate the Direction Of Arrival (DOA). By using Matrix Pencil (MP) algorithms the weight of the antenna array can be adjusted to form certain amount of adaptive beam to track corresponding users automatically and to minimize interference arising from others by introducing nulls in their direction. The interference can be suppressed and the desire signal can be extracted. One of the adaptive Matrix Pencil algorithm Least Mean Square Algorithm (LMS) is presented on this article using Uniform Circular Array (UCA) structure. Smart antenna incorporates this algorithm in coded form which calculates complex weights according to the signal environment. The efficiency of (LMS) algorithm is compared on the basis of normalized array factor and Root Mean Square Error (RMSE) for mobile communication. The results demonstrate clearly that the Matrix Pencil investigate in this work is more accurate and stable compared to the published measure.Keyword-Smart Antenna, DOA, LMS, MP, RMSE, UCA I. INTRODUCTION Smart antenna has been widely used in many applications such as radar, sonar and wireless communication systems. Considerable research efforts have been made to estimate the direction of arrival (DOA) and various array signal process techniques for DOA estimation have been proposed. In particular, the DOA estimation for uniform circular arrays (UCAs) has been developed in these scenarios, which desired all-azimuth angle coverage. By the virtue of their geometry, UCAs are able to provide 360°of coverage in azimuth plane. Moreover, they are known to be is isotropic. That is, they can estimate the DOA of incident signal with uniform resolution in the azimuth plane. In addition, direction patterns synthesized with UCAs can be electronically rotated in the plane of the array without significant change of beam shape [1]- [4].There are various methods to estimate the angle of arrival (DOA) of radio signals on the antenna array. DOA estimation techniques can be broadly divided into three different categories namely; conventional methods subspace based methods and maximum likelihood methods. Convolution methods are based on the concepts of beam forming and null steering, but it requires a large number of elements to provide high resolution. Examples of this method are delay and sum and Capon's minimum variance method [2].One major limitation of this method is poor resolution that is its ability to separate closely spaced signals. Unlike conventional methods, subspace methods exploit the information of the received data resulting in high resolution. Two main subspace based algorithms are Multiple Signal Classification and Estimation of Signal Parameters via Rotational Invariance Techniques.The DOA algorithms are classified as quadratic (non subspace) type and subspace type. The Barltett and Capon (Minimum Variance Distortion less Response) [3] are quadratic type algorithms. Both methods are highly dependent on physical size ...

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“…[1][2][3][4][5][6][7][8][9] 초기 다양한 위치 추정기법들은 대부분 원거리(far 최근 선형 선배열에서 근거리 위치 추정에 관한 연구가 많이 진행되었다. [3][4][5][6][7][8] 그중 가장 일반적인 기 법으로는 1차원 탐색 기법을 2차원으로 확장한 ML, [3] 2차원 MUSIC [4] 기법이 있으나 연산량이 많이 필요한 단점이 있다.…”

Section: 서 론unclassified

Near-field Source Localization Method using Matrix Pencil

Jung¹,

Lee²,

Yoon³

et al. 2013

The Journal of the Acoustical Society of Korea

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ABSTRACT:In this paper, near-field source localization algorithm is presented using Matrix Pencil in Uniform Linear Array(ULA). Based on the centrosymmetry of the ULA, the proposed algorithm decouples the steering vectors which allow for the bearing estimation using Matrix pencil. With estimated bearing, the range estimation of each source is consequently obtained by defining 1D MUSIC spectrum. Simulation results are presented to validate the performance of the proposed algorithm. 예측 기법(linear prediction), [5] higher-order ESPRIT, [6] cumulant 기반 [7] 등의 기법이 제안되었지만 추가적으로 II. 신호 모델

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Utilization of a unitary transform for efficient computation in the matrix pencil method to find the direction of arrival

Cited by 144 publications

References 14 publications

Beamspace matrix pencil method for direction of arrival estimation

Beamspace matrix pencil method for direction of arrival estimation

Matrix Pencil for Direction Of Arrival Using Smart Antenna

Near-field Source Localization Method using Matrix Pencil

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