Off-grid DOA Estimation Algorithm Based on Taylor-expansion and Alternating Projection Maximum Likelihood

LIU Shuai; XU Yuanyuan; YAN Fenggang; JIN Ming

doi:10.11999/JEIT231376

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LIU Shuai, XU Yuanyuan, YAN Fenggang, JIN Ming. Off-grid DOA Estimation Algorithm Based on Taylor-expansion and Alternating Projection Maximum Likelihood[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231376

Citation:

LIU Shuai, XU Yuanyuan, YAN Fenggang, JIN Ming. Off-grid DOA Estimation Algorithm Based on Taylor-expansion and Alternating Projection Maximum Likelihood[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231376

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Off-grid DOA Estimation Algorithm Based on Taylor-expansion and Alternating Projection Maximum Likelihood

doi: 10.11999/JEIT231376

School of Information Science and Engineering, Harbin Institute of Technology (Weihai), Weihai 264209, China

Funds: The General Projects of National Natural Science Foundation of China (62071144, 62171150), Taishan Scholars Project Special Funds (tsqn202211087)

Received Date: 2023-12-13
Rev Recd Date: 2024-05-10

Available Online: 2024-06-17

Abstract

Abstract

According to the problem that the maximum likelihood DOA estimation algorithm requires multi-dimensional search, is computationally intensive, and there is a problem in grid estimation, an Off-grid alternating projection maximum likelihood algorithm based on Taylor expansion is proposed. Firstly, the alternating projection method is used to transform the multi-dimensional search into multiple one-dimensional searches to obtain the rough estimation results corresponding to the preset large grid. Then, the second-order Taylor expansion of the one-dimensional cost function at the rough estimation results is carried out by using the matrix derivation theory. Finally, by calculating the partial derivative of the second-order Taylor expansion and making the derivative equal to zero, the closed-form solution of the off-grid parameters is obtained. Compared with the alternating projection maximum likelihood algorithm, this method breaks through the limitation of the search grid size. While ensuring the accuracy of the algorithm, it effectively reduces the number of points in the grid calculation of the algorithm while ensuring the accuracy of the algorithm, and improves the operation efficiency. Simulation results show the effectiveness of the algorithm.
- Maximum likelihood algorithm,
- Alternating projection,
- Off-grid,
- Taylor expansion

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References(22)

References

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