CNN-based cognitive radar array selection
Küçük Resim Yok
Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In cognitive radar, it may be desired to select an optimal subarray from a full antenna array in each scan to reduce the cost and computational complexity. Previous works on antenna selection rely on mostly optimization or greedy search methods. In this paper, we introduce a deep learning approach for antenna selection in a cognitive radar scenario. We design a deep convolutional neural network (CNN) to select the best subarray for direction-of-arrival estimation for each scan. The CNN accepts the array covariance matrix as its input and, unlike previous works, does not require prior knowledge about the target location. The performance of the proposed CNN approach is evaluated through numerical simulations. In particular, we show that it provides more accurate results than conventional support vector machines. © 2019 IEEE.
Açıklama
2019 IEEE Radar Conference, RadarConf 2019 -- 22 April 2019 through 26 April 2019 -- 152051
Anahtar Kelimeler
Antenna selection; Cognitive radar; Convolutional neural networks; Deep learning; DoA estimation
Kaynak
2019 IEEE Radar Conference, RadarConf 2019
