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Sensors 2017, 17(10), 2218; https://doi.org/10.3390/s17102218

Clustered Multi-Task Learning for Automatic Radar Target Recognition

School of Aerospace Science and Technology, Xidian University, Xi’an 710126, China
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Received: 4 August 2017 / Revised: 22 September 2017 / Accepted: 23 September 2017 / Published: 27 September 2017
(This article belongs to the Section Remote Sensors)
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Abstract

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms. View Full-Text
Keywords: clustered multi-task learning; high-resolution range profile (HRRP); synthetic aperture radar (SAR); radar automatic target recognition (RATR) clustered multi-task learning; high-resolution range profile (HRRP); synthetic aperture radar (SAR); radar automatic target recognition (RATR)
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Li, C.; Bao, W.; Xu, L.; Zhang, H. Clustered Multi-Task Learning for Automatic Radar Target Recognition. Sensors 2017, 17, 2218.

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