Abstract

Compared with uniform arrays, a generalized sparse array (GSA) can obtain larger array aperture because of its larger element spacing, which improves the accuracy of DOA estimation. At present, most DOA estimation algorithms are only suitable for the uniform arrays, while a few DOA estimate algorithms that can be applied to the GSA are unsatisfactory in terms of computational speed and accuracy. To compensate this deficiency, an improved DOA estimation algorithm which can be applied to the GSA is proposed in this paper. First, the received signal model of the GSA is established. Then, a fast DOA estimation method is derived by combining the weighted noise subspace algorithm (WNSF) with the concept of “transform domain” (TD). Theoretical analysis and simulation results show that compared with the traditional multiple signal classification (MUSIC) algorithm and the traditional WNSF algorithm, the proposed algorithm has higher accuracy and lower computational complexity.

Highlights

  • With the rapid development of information technology, wireless transmission systems, such as mobile communications, radar, and unmanned aerial vehicles (UAV), have become widely used

  • Compared with the uniform arrays, the generalized sparse array (GSA) can obtain larger array aperture. erefore, the estimation accuracy and resolution of the algorithm are effectively improved. e GSA is derived from a uniform array, and it can be obtained by redeploying the array elements of uniform array according to some optimization algorithms

  • The calculation range of the search function can be reduced by half, and the “rapidity” of the algorithm can be achieved. e theoretical analysis and computer simulation results show that the proposed algorithm has higher accuracy and lower computational complexity than the multiple signal classification (MUSIC) algorithm and traditional WNSF algorithm

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Summary

Introduction

With the rapid development of information technology, wireless transmission systems, such as mobile communications, radar, and unmanned aerial vehicles (UAV), have become widely used. When the number of array elements is limited, the aperture of the uniform array will be affected, which will lead to lower accuracy of DOA estimation [10, 11] To solve this problem, scholars have proposed the GSA—a nonequidistant array system—in which the distance between adjacent array elements is more than half of the wavelength of the incident signal [12,13,14,15]. E most significant feature of GSA is that the spacing between adjacent array elements is unequal In this case, most conventional DOA estimation algorithms which have strict requirements on array structure, such as ESPRIT algorithm [21,22,23], will lose their effect. Zhang et al [36] used spherical Fourier domain to construct the array signal model These methods are only applicable to uniform liner arrays, which means that the method is not universal. The calculation range of the search function can be reduced by half, and the “rapidity” of the algorithm can be achieved. e theoretical analysis and computer simulation results show that the proposed algorithm has higher accuracy and lower computational complexity than the MUSIC algorithm and traditional WNSF algorithm

Signal Model of GSA
DOA Estimation Algorithm Based on TDWNSF
Simulation 1
Simulation 2
Simulation 3
Conclusions
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