Multi‐feature radar signal modulation recognition based on improved PSO algorithm

Intelligent Modulation Pattern Recognition Based on Wavelet Approximate Coefficient Entropy in Cognitive Radio Networks

“…Wavelet analysis is a local transform of time and frequency, which can effectively extract information from the signal and is conducive to the perception of the surrounding electromagnetic environment. For some time, many CR technologies are devoted to modulation recognition of communication signals by using spectrum and cyclic spectrum [2], characteristic parameters and their statistics [3], time-frequency transform [4], [5], and high-order cumulants [6]- [8]. However, these methods are difficult to achieve multiresolution analysis of the modulated signals, which increases the difficulty of ob-taining effective information, and the real-time performance of signal analysis and processing is not good.…”

“…In the simulation, 500 repeated experiments were performed to analyze the recognition rate of three kinds of wavelet entropy, and the classification and recognition were carried out according to the range of the characteristic parameters corresponding to different modulation signals. Take a= [8,16,32,16,8,4] and the recognition rate is shown in Fig. 10.…”