Abstract
The track information is an important feature for radar target recognition. In this paper, the authors propose to classify targets based on radar track using bi-directional long short-term memory (BiLSTM) and self-attention mechanism. More specifically, the forward and backward operation in BiLSTM is able to capture temporal dependence of the track. The resulting deep resprentations of the track is refined by a self-attention mechanism to enhance the most discriminative parts. A fully connected layer followed by softmax operator is used to determine the type of the track. Experimental results show that the proposed method outperforms conventional algorithms.
Original language | English |
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Title of host publication | IET Conference Proceedings |
Publisher | Institution of Engineering and Technology |
Pages | 369-373 |
Number of pages | 5 |
Volume | 2020 |
Edition | 9 |
ISBN (Electronic) | 9781839535406 |
DOIs | |
Publication status | Published - 2020 |
Event | 5th IET International Radar Conference, IET IRC 2020 - Virtual, Online Duration: 4 Nov 2020 → 6 Nov 2020 |
Conference
Conference | 5th IET International Radar Conference, IET IRC 2020 |
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City | Virtual, Online |
Period | 4/11/20 → 6/11/20 |
Keywords
- BILSTM
- RADAR TRACK
- SELF-ATTENTION MECHANISM