Radar Emitter Classification Using Self-Organising Neural Network Models

被引:4
|
作者
Anjaneyulu, L. [1 ]
Murthy, N. S. [1 ]
Sarma, N. V. S. N. [1 ]
机构
[1] Natl Inst Technol, Dept ECE, Warangal, Andhra Pradesh, India
关键词
Artificial Neural Networks; EID; Fuzzy ART; ARTMAP; Radar Emitter;
D O I
10.1109/AMTA.2008.4763033
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
This paper presents a Radar Emitter Identification and Classification technique based on Fuzzy ART and ARTMAP Neural Networks. The radar emitter's parameters of RF, PW, PRI, Direction of Arrival(DOA) etc., are taken as inputs for the networks. The network is trained with the available data of the emitter types. After training, the network is used to identify the emitter type by applying the parameters of the emitter as inputs to the neural network. A number of simulations are carried out and the simulated results show that the network quickly and accurately Identify and classify the emitter types.
引用
收藏
页码:431 / 433
页数:3
相关论文
共 50 条
  • [31] Self-organising neural networks for adaptive control
    Warwick, K
    Ball, N
    JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 1996, 15 (02) : 153 - 163
  • [32] Pattern classification using multiple hierarchical overlapped self-organising maps
    Suganthan, PN
    PATTERN RECOGNITION, 2001, 34 (11) : 2173 - 2179
  • [33] Classification of motor commands using a modified self-organising feature map
    Sebelius, F
    Eriksson, L
    Holmberg, H
    Levinsson, A
    Lundborg, G
    Danielsen, N
    Schouenborg, J
    Balkenius, C
    Laurell, T
    Montelius, L
    MEDICAL ENGINEERING & PHYSICS, 2005, 27 (05) : 403 - 413
  • [34] A Self-organising Network Based on Lightweight Agents
    Debenham, John
    Prodan, Ante
    NETWORK-BASED INFORMATION SYSTEMS, PROCEEDINGS, 2008, 5186 : 202 - 211
  • [35] A self-organising network that grows when required
    Marsland, S
    Shapiro, J
    Nehmzow, U
    NEURAL NETWORKS, 2002, 15 (8-9) : 1041 - 1058
  • [36] An improved approach of self-organising fuzzy neural network based on similarity measures
    Gang Leng
    Xiao-Jun Zeng
    John A. Keane
    Evolving Systems, 2012, 3 (1) : 19 - 30
  • [37] Gait quality assessment using self-organising artificial neural networks
    Barton, Gabor
    Lisboa, Paulo
    Lees, Adrian
    Attfield, Steve
    GAIT & POSTURE, 2007, 25 (03) : 374 - 379
  • [38] A self-organising mixture network for density modelling
    Yin, HJ
    Allinson, NM
    IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE, 1998, : 2277 - 2281
  • [39] An efficient approach for Kohonen self-organising network
    Pan, JS
    Kuo, TH
    Chu, SC
    Day, JD
    Liao, BY
    ICEMI '97 - CONFERENCE PROCEEDINGS: THIRD INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, 1997, : 622 - 625
  • [40] Neural Classification of Compost Maturity by Means of the Self-Organising Feature Map Artificial Neural Network and Learning Vector Quantization Algorithm
    Boniecki, Piotr
    Idzior-Haufa, Malgorzata
    Pilarska, Agnieszka A.
    Pilarski, Krzysztof
    Kolasa-Wiecek, Alicja
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2019, 16 (18)