The recognition method of radiation source based on information entropy and cloud model
Information entropy features are often used for radiation source signal recognition, but due to the information entropy is very sensitive to noise, so this method has greater recognition rate changes with the SNR. This paper putting forward a viable recognition based on Entropy and cloud model. using cloud model to extract secondary features of signals, build radiation source signal’s entropy and cloud feature vector. The method uses cloud model description and processing interval fuzzy and observation noise data, better solve the low SNR cases of radiation source signal feature extraction problem. At the same time, putting forward the similar cloud classification recognition algorithm based on cloud model. The simulation results show that Entropy and cloud model has better recognition effect under low SNR, which can improve the signals’ recognition rate under low SNR.
& Zhang, Z.
(2016). The recognition method of radiation source based on information entropy and cloud model. International Journal of Grid and Distributed Computing, 9 (2), 33-42.