Adaptive Detection of an Unknown FH Signal Based on Image Features
Beijing(2009)
Abstract
We introduce an adaptive detection structure for unknown frequency hopping (FH) signal. After getting the short time Fourier transform (STFT) of received signal, we process the time-frequency spectrogram in terms of image operations, and extract multiple image features. Two kinds of method are employed for combinative detection. We firstly establish the FH signal verification and joint parameters estimation (FHSVJPE) model based on these image features, and estimate some FH parameters while resolving the model. The FH detection threshold used in the model can be adjusted adaptively according to complicated time varying environments. Then we propose a time frequency (TF) matching method to further detect the jammed hops and estimate other FH parameters. Simulation results demonstrate that this detection algorithm is feasible and efficient.
MoreTranslated text
Key words
time frequency matching,fourier transforms,adaptive detection structure,fh signal verification,image matching,detection algorithm,fh detection threshold,multiple image feature extraction,parameter estimation,short time fourier transform,image feature,feature extraction,complicated time,time-frequency spectrogram,jammed hop detection,image operation,fh parameter,adaptive unknown fh signal detection,unknown fh,joint parameters estimation,signal detection,frequency hop communication,unknown frequency hopping signal,combinative detection
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined