Improved MUSIC Algorithm for Multiple Noncoherent Subarrays

Wen, Fei; Wan, Qun; Fan, Rong; Wei, He‐Wen

doi:10.1109/lsp.2014.2308271

Cited by 74 publications

(24 citation statements)

References 14 publications

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“…It provides unbiased estimation results in many practical applications, and is even found to perform well in a multiple signal environment. This algorithm achieves high resolution in DOA [14] only when the incoming signals are non-coherent. The results and simulations discussed in the above sections consider that that the incoming signals that are being incident are not related and hence are not generated from the same source.…”

Section: Detection Of Coherent Signalsmentioning

confidence: 99%

Resource Optimization for the Efficient Channel Access and Estimation in LTE System

Gupta¹,

Verma²

2015

IJIGSP

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Abstract-The signal processing applications are limited with high-resolution signal parameter estimation. Therefore the Direction of Arrival estimation algorithm needs to be effective and efficient in order to improve the performance of smart antennas. This paper presents the simulation for a subspace based DOA estimation algorithm with high resolution. MUSIC (Multiple signal classification) and the IMUSIC (Improved MUSIC) are presented and optimized by varying various parameters. The basic MUSIC algorithm is ineffective in estimating the incoming coherent signals. The new improved MUSIC algorithm overcomes this ineffectiveness and correctly estimates the related signals with improved accuracy. The improved version of MUSIC algorithm is brought about by taking into account the conjugate of the data matrix for MUSIC algorithm and then reconstructing it. The various factors like the number of array elements, number of snapshots, varying the distance between array elements, varying SNR and the difference in arrival angles can bring about better resolutions. The comparisons for MUSIC and Improved MUSIC algorithm are widely discussed.

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Section: Detection Of Coherent Signalsmentioning

confidence: 99%

Resource Optimization for the Efficient Channel Access and Estimation in LTE System

Gupta¹,

Verma²

2015

IJIGSP

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“…a aa (12) Using this weight vector, the spatial spectrum can be calculated using the below equation as-…”

Section: Capons Minimum Variance Distortionless Response (Mvdr) Beam-mentioning

confidence: 99%

“…Here both classical multichannel DOA algorithms and subspace based high resolution DOA algorithms are compared. Also performance evaluation of MUSIC algorithm [9][10][11][12] is provided in detail. This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

MATLAB Simulation of Subspace based High Resolution Direction of Arrival Estimation Algorithm

Agrawal¹,

Sudan²

2015

IJCA

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Over the past decades there has been technological breakthrough from analog to digital. Ever since the world war and also the invention of electromagnetic radio, there has always been an urge to know from which direction the signals were arriving to the listener"s direction finding receiver. The methodology of determining the direction of arrival (DOA) of incoming signals impinging on the uniform antenna array has drastically changed from conventional methods to subspace based methods. The main goal of this paper is to provide a comparative study of various classical multi-channel DOA algorithms and subspace based high resolution multi-channel DOA algorithms for multiple signals which are arriving at different DOA. Also detailed algorithm analysis and performance evaluation for subspace based multiple signal classification (MUSIC) algorithm is provided. It is shown that subspace based high resolution multi-channel MUSIC algorithm is statistically efficient and is a promising method for use against military communication in an electronic warfare direction finding system.

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“…Direction-of-arrival (DOA) estimation of incident signals is a momentous embranchment of array signal processing, and it also has received widespread concern in wireless communication [3]. Many classical DOA estimation techniques such as subspace-based methods [4][5][6], sparse reconstruction algorithms [7,8] and support vector classification-based algorithm [9] were proposed by scholars in succession. However, most of these algorithms are conditional on that mutual coupling (MC) between sensors is ignored or known.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, MC exists unavoidably, particularly between the elements with small spacing, and it can affect the structure of array manifold. So the methods [4][5][6][7][8][9] are difficult to achieve satisfactory estimation performance in practice Recently, in order to eliminate the effect of MC, many calibration algorithms [10][11][12][13][14][15][16][17][18] have been presented. Iterative method [10][11][12] is a commonly used technology to estimate MC coefficients (MCCs), but this method cannot estimate the DOA directly.…”

Section: Introductionmentioning

confidence: 99%

Doa Estimation With Sparse Array Under Unknown Mutual Coupling

Liu¹,

Zhao²,

Xiao³

2017

PIER Letters

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Abstract-In this paper, we propose a direction-of-arrival (DOA) estimation algorithm under unknown mutual coupling with a sparse linear array (SLA). We employ an SLA composed of two uniform linear arrays (ULA), and the element spacing of one of the subarrays is large enough to neglect the effect of the mutual coupling (MC). The fourth-order-cumulants (FOCs) of the received data from partial elements of the first subarray and all elements of the second subarray are exploited to construct a high-order FOC matrix. Then, the DOAs of incident signals are estimated by dealing with this high-order matrix. The array aperture is extended greatly due to the sparse structure. Hence, the proposed method shows much better performance than some classical blind DOA estimation methods in accuracy and resolution. We also propose some simulation results to prove the effectiveness of our method.

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Improved MUSIC Algorithm for Multiple Noncoherent Subarrays

Cited by 74 publications

References 14 publications

Resource Optimization for the Efficient Channel Access and Estimation in LTE System

Resource Optimization for the Efficient Channel Access and Estimation in LTE System

MATLAB Simulation of Subspace based High Resolution Direction of Arrival Estimation Algorithm

Doa Estimation With Sparse Array Under Unknown Mutual Coupling

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