NDLI: Optimizing zero-slice feature of ambiguity function for radar emitter identification

Content Provider	IEEE Xplore Digital Library
Author	Lei Wang Hongbing Ji
Copyright Year	2009
Description	Author affiliation: School of Electronic Engineering, Xidian University, Xi'an 710071, China (Lei Wang; Hongbing Ji)
Abstract	Radar emitter identification has attracted increasing interests in the last decade. The class-dependent method in [5,6] to optimize Time-Frequency kernel of ambiguity function (AF) needs to rank kernel points in the whole AF plane and is sensitive to sampling data length. In this paper, an ambiguity function zero-slice based feature optimization algorithm is proposed for radar emitter recognition. It efficiently extracts the zero-slice feature of AF as intermediate feature set and avoids “out of memory” problem as in large whole-plane optimization. Further, a Direct Discriminant Ratio (DDR) criterion is employed to rank the kernel points along the obtained slice. The resulting scheme not only preserves the most discriminant features of individual emitters, but also improves the recognition accuracy greatly. The experiments on both simulation radar data from U.S. Naval Research Laboratory and real radar emitter data demonstrate the feasibility and effectiveness of the proposed method.
Starting Page	1
Ending Page	4
File Size	257846
Page Count	4
File Format	PDF
ISBN	9781424446568
DOI	10.1109/ICICS.2009.5397545
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-08
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radar Kernel Time frequency analysis Optimization methods Sampling methods Laboratories Signal processing Data mining Feature extraction Fourier transforms zero-slice radar emitter identification feature optimization intra-pulse fine features ambiguity function
Content Type	Text
Resource Type	Article

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