TY - GEN
T1 - A Learning-Based Approach to Underwater Direction of Arrival Estimation for Small Samples
AU - Zhang, Qinzheng
AU - Wang, Haiyan
AU - Yan, Yongsheng
AU - Shen, Xiaohong
AU - He, Ke
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - With the development of deep learning technology, the direction of arrival(DOA) estimation based on it is also booming. However, due to the difficulty in obtaining samples, underwater DOA estimation is hard to achieve the same effect as that on land. Meanwhile, underwater channel is more seriously affected by multipath which makes the neural networks have poor generalization ability. In this paper, we construct new input feature for the neural networks. Then we use transfer learning to utilize simulated data, and skillfully split the output task to make use of the multi-task learning mechanism. Experiments and simulations show that our method has good performance improvement.
AB - With the development of deep learning technology, the direction of arrival(DOA) estimation based on it is also booming. However, due to the difficulty in obtaining samples, underwater DOA estimation is hard to achieve the same effect as that on land. Meanwhile, underwater channel is more seriously affected by multipath which makes the neural networks have poor generalization ability. In this paper, we construct new input feature for the neural networks. Then we use transfer learning to utilize simulated data, and skillfully split the output task to make use of the multi-task learning mechanism. Experiments and simulations show that our method has good performance improvement.
KW - multi-task learning
KW - sensor arrays
KW - transfer learning
KW - underwater direction of arrival
UR - http://www.scopus.com/inward/record.url?scp=85146417355&partnerID=8YFLogxK
U2 - 10.1109/ICSPCC55723.2022.9984216
DO - 10.1109/ICSPCC55723.2022.9984216
M3 - 会议稿件
AN - SCOPUS:85146417355
T3 - 2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022
BT - 2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022
Y2 - 25 October 2022 through 27 October 2022
ER -