Distributed source DOA estimation based on deep learning networks
Author:
Funder
Science and Technology Plan Project of Taizhou
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11760-024-03402-y.pdf
Reference42 articles.
1. Li, B., Zhang, X., Li, J., Ma, P.: DOA estimation of non-circular source for large uniform linear array with a single snapshot: extended DFT method. IEEE Commun. Lett. 25(12), 3843–3847 (2021)
2. Dai, X., Zhang, X., Wang, Y.: Extended DOA-matrix method for DOA estimation via two parallel linear arrays. IEEE Commun. Lett. 23(11), 1981–1984 (2019)
3. Lin, J., Ma, X., Yan, S., Hao, C.: Time-frequency multi-invariance ESPRIT for DOA estimation. IEEE Antennas Wirel. Propag. Lett. 15, 770–773 (2016)
4. Xu, L., Wen, F., Zhang, X.: A novel unitary PARAFAC algorithm for joint DOA and frequency estimation. IEEE Commun. Lett. 23(4), 660–663 (2019)
5. Hu, D., Zhang, Y., He, L., Wu, J.: Low-complexity deep-learning-based DOA estimation for hybrid massive MIMO systems with uniform circular arrays. IEEE Wirel. Commun. Lett. 9(1), 83–86 (2020)
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