Sun Guangmin, Liu Guosui, Wang Yunhong. 1-D RANGE PROFILE IDENTIFICATION OF RADAR TARGETS BASED ON LINEAR INTERPOLATION NEURAL NETWORK[J]. Journal of Electronics & Information Technology, 1999, 21(1): 97-103.
Citation:
Sun Guangmin, Liu Guosui, Wang Yunhong. 1-D RANGE PROFILE IDENTIFICATION OF RADAR TARGETS BASED ON LINEAR INTERPOLATION NEURAL NETWORK[J]. Journal of Electronics & Information Technology, 1999, 21(1): 97-103.
Sun Guangmin, Liu Guosui, Wang Yunhong. 1-D RANGE PROFILE IDENTIFICATION OF RADAR TARGETS BASED ON LINEAR INTERPOLATION NEURAL NETWORK[J]. Journal of Electronics & Information Technology, 1999, 21(1): 97-103.
Citation:
Sun Guangmin, Liu Guosui, Wang Yunhong. 1-D RANGE PROFILE IDENTIFICATION OF RADAR TARGETS BASED ON LINEAR INTERPOLATION NEURAL NETWORK[J]. Journal of Electronics & Information Technology, 1999, 21(1): 97-103.
A novel neural network model---Linear Interpolation Neural Network(LINN) has been presented, which is used for radar target identification. And the 1-D range profiles of targets are used as identification feature. It is well known that the 1-D range profile reflects the precise geometric structure feature of a target, but it varies with the pose of the target. The LINN utilizes just the variation information of the 1-D range profile with the pose to improve the identification performance of targets in any posture.
Stewart C, Lu Yichuan, Larson V. Vector quantization and learning vector quantization for radar target classification. SPIE 1993, Vo1.1960, 115-124.[2]Lu Yichuan, Chang Kuochu. A Neural network approach for high resolution target classification. SPIE 1995. Vol.2484. 558-566.[3]Neiberg L, Casasent D P. Feature Space Trajectory (FST) classifier neural network. SPIE 1994, Vol.2353,276-292.[4]Kouba E T, Rogers S K, Ruck D W, Bauer Jr. K W. Recurrent neural networks for radar target identification. SPIE 1993. Vo1.1965. 256-265.[5][5J Jouny I, Garber F D, Ahalt S C. Classfication of radar targets using synthetic neural networks.[6]IEEE Trans. on AES, 1993, 29(2): 336-343.
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