Fast Parameter Estimation and Recognition Approach for Hybrid Spread Spectrum Signals

To improve the status of hybrid spread spectrum signal mainly based on direct sequence spread spectrum(DSSS) signal and frequency hopping(FH) spread spectrum signal,a fast approach is presented for DSSS and chirp spread spectrum.By establishing coefficient of frequency domain moment peak based neural network,two types of signals are identified.The recognition probability is above 95% when SNR(Signal-to-Noise Ratio) is close to-3 dB.By reverse-order conjugation convolution-fast dechirp,the code rate and initial frequency and slope of convolutional compound signal can be estimated.Code rate estimation accuracy is higher when SNR is close to-1 dB.