Research on Spectrum Feature Identification of Indoor Multimodal Communication Signal | Zendy

Yunfei Chen | Zendy; Yang Liu | Zendy; Xintao Fan | Zendy

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Research on Spectrum Feature Identification of Indoor Multimodal Communication Signal

Author(s) -

Yunfei Chen,

Yang Liu,

Xintao Fan

Publication year - 2021

Publication title -

advances in mathematical physics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.283

H-Index - 23

eISSN - 1687-9139

pISSN - 1687-9120

DOI - 10.1155/2021/7913666

Subject(s) - signal (programming language) , computer science , pattern recognition (psychology) , wavelet , envelope (radar) , feature (linguistics) , artificial intelligence , feature extraction , identification (biology) , blind signal separation , speech recognition , channel (broadcasting) , telecommunications , radar , linguistics , philosophy , botany , biology , programming language

In order to solve the problem of large signal acquisition error caused by radio wave multipath effect in indoor environment, firstly, the signal source carried on the motion platform is collected for spectrum signal, and the signal processed by wavelet threshold denoising algorithms extracted and stored for spectrum feature extraction. Then, after data training and identification, the signal source is input into the system in random mode for identification. The experimental results show that the improved fuzzy clustering algorithm (FCA) is 12.7% higher than the spectrum envelope extraction method (SEEM) in the recognition rate of spectrum characteristics of different modes of signal source.

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