An Intelligent DOA Estimation Error Calibration Method Based on Transfer Learning
Affected by various error factors in the actual environment, the accuracy of the direction of arrival (DOA) estimation algorithm will greatly decrease during an application. To address this issue, in this paper, we propose an intelligent DOA estimation error calibration method based on transfer lear...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/15/7636 |
| _version_ | 1797414690714812416 |
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| author | Min Zhang Chenyang Wang Wenli Zhu Yi Shen |
| author_facet | Min Zhang Chenyang Wang Wenli Zhu Yi Shen |
| author_sort | Min Zhang |
| collection | DOAJ |
| description | Affected by various error factors in the actual environment, the accuracy of the direction of arrival (DOA) estimation algorithm will greatly decrease during an application. To address this issue, in this paper, we propose an intelligent DOA estimation error calibration method based on transfer learning, which learns error knowledge from a small number of actual signal samples and improves the DOA estimation accuracy in the real application. We constructed a deep convolutional neural network (CNN)-based intelligent DOA estimation model to learn the mapping between the input signals and their azimuths. We generated a large number of ideal simulation signal samples to train the CNN model and used it as the pretrained model. Then, we fine-tuned the CNN model with a small number of actual signal samples collected in the actual environment. We demonstrate the effectiveness of the proposed method through simulation experiments. The experimental results indicate that the proposed method can effectively improve the accuracy of DOA estimation in the actual environment. |
| first_indexed | 2024-03-09T05:37:13Z |
| format | Article |
| id | doaj.art-df20a5db280d430082492fb94477f488 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T05:37:13Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-df20a5db280d430082492fb94477f4882023-12-03T12:28:27ZengMDPI AGApplied Sciences2076-34172022-07-011215763610.3390/app12157636An Intelligent DOA Estimation Error Calibration Method Based on Transfer LearningMin Zhang0Chenyang Wang1Wenli Zhu2Yi Shen3College of Electronic Engineering, National University of Defense Technology, Hefei 230031, ChinaCollege of Electronic Engineering, National University of Defense Technology, Hefei 230031, ChinaXi’an Satellite Control Center, Xi’an 710043, ChinaCollege of Electronic Engineering, National University of Defense Technology, Hefei 230031, ChinaAffected by various error factors in the actual environment, the accuracy of the direction of arrival (DOA) estimation algorithm will greatly decrease during an application. To address this issue, in this paper, we propose an intelligent DOA estimation error calibration method based on transfer learning, which learns error knowledge from a small number of actual signal samples and improves the DOA estimation accuracy in the real application. We constructed a deep convolutional neural network (CNN)-based intelligent DOA estimation model to learn the mapping between the input signals and their azimuths. We generated a large number of ideal simulation signal samples to train the CNN model and used it as the pretrained model. Then, we fine-tuned the CNN model with a small number of actual signal samples collected in the actual environment. We demonstrate the effectiveness of the proposed method through simulation experiments. The experimental results indicate that the proposed method can effectively improve the accuracy of DOA estimation in the actual environment.https://www.mdpi.com/2076-3417/12/15/7636DOA estimationerror calibrationtransfer learningconvolutional neural network |
| spellingShingle | Min Zhang Chenyang Wang Wenli Zhu Yi Shen An Intelligent DOA Estimation Error Calibration Method Based on Transfer Learning Applied Sciences DOA estimation error calibration transfer learning convolutional neural network |
| title | An Intelligent DOA Estimation Error Calibration Method Based on Transfer Learning |
| title_full | An Intelligent DOA Estimation Error Calibration Method Based on Transfer Learning |
| title_fullStr | An Intelligent DOA Estimation Error Calibration Method Based on Transfer Learning |
| title_full_unstemmed | An Intelligent DOA Estimation Error Calibration Method Based on Transfer Learning |
| title_short | An Intelligent DOA Estimation Error Calibration Method Based on Transfer Learning |
| title_sort | intelligent doa estimation error calibration method based on transfer learning |
| topic | DOA estimation error calibration transfer learning convolutional neural network |
| url | https://www.mdpi.com/2076-3417/12/15/7636 |
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