Application of Optimized Adaptive Chirp Mode Decomposition Method in Chirp Signal

The adaptive chirp mode decomposition method has a good effect on processing chirp signals. The parameter alpha controls the smoothness of the output signal. Too small an alpha will cause a smooth output signal. The parameter beta controls the instantaneous frequency (IF). If too small a beta value is used, the output IF will be very smooth. However, rapidly changing IFs require a relatively large beta. However, the choice of alpha,beta is artificially set, and there are errors in practical applications. Therefore, it employs the state transition algorithm to adaptively optimize alpha,beta to improve the signal-to-noise ratio (SNR) and resolution of the signal. First, as the species number of the state transition algorithm method is set artificially and has a long running time, this paper proposes a Rastrigin optimization test equation to test the optimization time of different species and determine the number of optimal species; second, the state transition algorithm determined by the number of species is employed to adaptively find the alpha,beta in the adaptive chirp mode decomposition algorithm; finally, the optimized adaptive chirp mode decomposition method is applied to the simulation signal and chirp signal from marine animals to verify the proposed method.