Linear canonical matched filter: theory, design, and applications

Shi, Jun, Liu, Xiaoping, Fang, Xiaojie, Sha, Xuejun, Xiang, Wei, and Zhang, Qinyu (2018) Linear canonical matched filter: theory, design, and applications. IEEE Transactions on Signal Processing, 66 (24). pp. 6404-6417.

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The linear canonical transform (LCT) is a multiparameter unitary transform that generalizes a large number of classical transforms with application to signal processing and optics. Many of its fundamental properties are already known; however, little attention has been paid to the design and implementation of matched filters in the LCT domain. The objective of this paper is to design this type of filters that maximize the output signal-to-noise ratio, dubbed the linear canonical matched filter (LCMF). We first derive some facts of the LCT spectral analysis for random signals. Then, by applying the derived results, the LCMF design theory associated with the LCT is developed. Moreover, the implementation and basic properties of the LCMF are presented. The introduction of the LCMF invites a new interpretation of the ambiguity function and the correlation function of the LCT. Finally, we provide several applications for the theoretical derivations.

Item ID: 56426
Item Type: Article (Research - C1)
ISSN: 1941-0476
Keywords: ambiguity function, matched filter, linear canonical transform (LCT), correlation function, pulse compression
Funders: National Natural Science Foundation of China (NNSFC), Natural Science Foundation of Heilongjiang Province (NSFHP), Fundamental Research Funds for the Central Universities (FRFCU)
Projects and Grants: NNSFC Grant 61501144, NNSFC Grant 61871153, NNSFC Grant 61671179, NSFHP QC2018078, FRFCU 01111305
Date Deposited: 28 Nov 2018 09:41
FoR Codes: 40 ENGINEERING > 4006 Communications engineering > 400607 Signal processing @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 100%
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