References in periodicals archive ?
A template matching method based on close degree is adopted to verify the validity of fused characteristics for MFSK signal individual identification.
Assume that there are N categories of MFSK signals in the emitter recognition system.
When the received signal has the greatest close degree with one kind of MFSK signal in feature database, the type of received signal can be determined.
In the simulation environment with matlab R2011b, we give two experiments about the novel feature fusion algorithm of MFSK signal individual identification.
1 Experiment 1: Identification of different MFSK signals
9 that MFSK signals are completely identified when the SNR is above 0dB.
Based on above two experimental results and analyses, the proposed two-dimensional feature fusion algorithm not only realizes different MFSK signal individual identification, but also achieves different 4FSK signal individual identification.
Thus, compared to MFSK signal individual identification methods with single feature, the superiority of the proposed algorithm is overt, and the significance and contribution of this paper is proved.
On the basis of analyzing the characteristics of bi-spectrum analysis and wavelet transform, we propose a novel MFSK signal individual identification algorithm.
In further study, as an individual identification algorithm of MFSK signal is investigated in this paper, how to apply the algorithm to signals with other modulation types has great research significance.
This paper includes a concrete bi-spectrum analysis and a specific wavelet low-frequency analysis of MFSK signals.
3] Luo S E, Zhang X Y, and Luo L Y, "Subband processing based symbol-rate estimation method for MFSK signal," in Proc.
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