A Low Complexity Two-demensional DOA Joint Estimation Algorithm Based on Parallel Coprime Virtual Array

Lin LI; Yulong YU; Hui HAN

doi:10.11999/JEIT200296

Volume 43 Issue 6

Jun. 2021

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Lin LI, Yulong YU, Hui HAN. A Low Complexity Two-demensional DOA Joint Estimation Algorithm Based on Parallel Coprime Virtual Array[J]. Journal of Electronics & Information Technology, 2021, 43(6): 1653-1658. doi: 10.11999/JEIT200296

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Lin LI, Yulong YU, Hui HAN. A Low Complexity Two-demensional DOA Joint Estimation Algorithm Based on Parallel Coprime Virtual Array[J]. Journal of Electronics & Information Technology, 2021, 43(6): 1653-1658. doi: 10.11999/JEIT200296

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A Low Complexity Two-demensional DOA Joint Estimation Algorithm Based on Parallel Coprime Virtual Array

doi: 10.11999/JEIT200296 cstr: 32379.14.JEIT200296

Lin LI^{1, 2
,
,},
Yulong YU²,
Hui HAN¹

1.
State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE), Luoyang 471003, China
2.
School of Electronic Engineering, Xidian University, Xi’an 710071, China

Funds: The Open Project of State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (2020G0101)

Received Date: 2020-04-21
Rev Recd Date: 2020-08-11

Available Online: 2020-08-15

Publish Date: 2021-06-18

Abstract

Abstract

There are more and more problems for the two-Dimensional (2D) direction finding with traditional parallel arrays, such as low degree of freedom, low resolution and large estimation errors with small snapshots, etc. In view of these problems and based on the parallel coprime virtual array, a low-complexity 2D Direction Of Arrival (DOA) algorithm is proposed in this paper. In the proposed algorithm, a virtual array is generated by the the expansion of two mutually parallel linear arrays. Then an extended matrix with high degrees of freedom of the 2D angular is constructed by the autocovariance matrix and cross-covariance matrix. Finally, the automatically matched 2D-DOA estimation is obtained by the Singular Value Decomposition (SVD) and Estimating Signal Parameters via Rotational Invariance Techniques (ESPRIT). Compared with the traditional two-dimensional DOA estimation methods, the proposed algorithm utilizes more information from the received data of the array, can distinguish more incident signals with high resolution. Meanwhile, the proposed algorithm needs no 2D linear searching or angular parameter matching and is with good performance under low Signal-to-Noise Ratio (SNR) and small snapshot. Experimental simulation results demonstrate the correctness and validity of the algorithm.
- 2D-Direction Of Arrival(DOA) estimation,
- Parallel coprime array,
- Extended matrix

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References(17)

References

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