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Compared to globality based supervised dimensionality reduction methods such as Fisher Discriminant Analysis (FDA), locality based ones including Local Fisher Discriminant Analysis (LFDA) have attracted increasing interests since they aim to preserve the intrinsic data structures and are able to handle multimodally distributed data. However, both FDA and LFDA are usually solved via a ratio trace form...
Radar emitter recognition is an important and challenging subject in radar signal analysis and processing. In this work, an ambiguity function (AF) representative-slice based feature extraction and optimization algorithm is presented for unintentional modulation recognition of moving radar emitters. It considers near-zero slices of AF as representative feature set of radar emitters, which not only...
Radar emitter identification has attracted increasing interests in the last decade. The class-dependent method in 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...
The problem of concern here is the parameter estimation of chirp signals in the presence of additive noise. An improved cyclostationarity based algorithm is proposed to estimate the phase parameters. The novelty of the proposed algorithm lies in the iterative estimation of the second-order parameters. The main characteristics of the method include reduction in error propagation effect, increase in...
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