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dc.contributor.authorDuh, FBen_US
dc.contributor.authorJuang, CFen_US
dc.contributor.authorLin, CTen_US
dc.date.accessioned2014-12-08T15:26:15Z-
dc.date.available2014-12-08T15:26:15Z-
dc.date.issued2003en_US
dc.identifier.isbn0-7803-7810-5en_US
dc.identifier.urihttp://hdl.handle.net/11536/18636-
dc.description.abstractTo solve the existing dilemma between making good range resolution and maintaining the low average transmitted power, it is necessary for the pulse compression processing to give low range sidelobes in the modern high-resolution radar systems. The traditional pulse compression algorithms based on 13-element Barker code such as direct autocorrelation filter (ACF), least squares (LS) inverse filter, and linear programming (LP) filter have been developed, and the neural network algorithms were issued recently. However, the traditional algorithms cannot achieve the requirement of high signal-to-sidelobe ratio, and the normal neural network such as backpropagation (BP) network usually produces the extra problems of low convergence speed and sensitive to the Doppler frequency shift. To overcome these defects, a new approach using a neural fuzzy network with binary phase code to deal with pulse compression in a radar system is presented in this paper. The 13-element Barker code used as the binary phase signal code is carried out by six-layer self-constructing neural fuzzy network (SONFIN) with supervised learning algorithm. Simulation results show that this neural fuzzy network pulse compression (NFNPC) algorithm has the significant advantages in noise rejection performance, range resolution ability and Doppler tolerance, which are superior to the traditional and BP algorithms, and has faster convergence speed than BP algorithm.en_US
dc.language.isoen_USen_US
dc.titleApplication of neural fuzzy network to pulse compression with binary phase codeen_US
dc.typeProceedings Paperen_US
dc.identifier.journalPROCEEDINGS OF THE 12TH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1 AND 2en_US
dc.citation.spage1389en_US
dc.citation.epage1394en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000183448800240-
Appears in Collections:Conferences Paper