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The ambiguity function is an effective tool to solve the problem of radar emitter signals sorting in complex systems. To improve the real-time and accuracy of the ambiguity function main ridge (AFMR), this paper proposes an intelligent method to search AFMR based on adaptive differential evolution algorithm. The signal is pre-identified by the instantaneous frequency (IF) features to reduce the AFMR search range and the complexity of the problem. In this way, the differential evolution algorithm parameters can be adaptively adjusted according to the pre-recognition results to accelerate the convergence of the algorithm. Then the statistical hypothesis testing theory is used to analyze and test the search results. The experiment results show that the proposed method reduces the time of searching AFMR to about 4% compared with the exhaustive method with higher accuracy and stability.

The axially symmetric rotor plus quasiparticle model for an odd nucleus is generalized to the odd-odd nucleus and special attention is paid to the model basis accounting for {gamma} vibration perturbation around axial symmetry. The method presented in this paper is used for a number of realistic nuclei in the A=160 mass region. Two slightly different calculation schemes are put into practice. The first calculation gives results in qualitative agreement with experiments and the second calculation provides remarkable improvements to the first. A possible explanation of the mechanism for signature inversion of odd-odd nuclei is discussed. {copyright} {ital 1997} {ital The American Physical Society}

Feature extraction is the crucial technology to deinterleave and recognize the new system radar emitter signals. In this paper, a novel time-frequency atom feature extraction approach is presented. Based on the over-complete multiscale dictionary of Gaussian Chirplet atoms, adopting match pursuit (MP) to decompose signals and the improved quantum genetic algorithm (IQGA) to reduce the search time for MP, the optimal Chirplet atoms to represent the feature information of the radar emitter signals can be obtained. The validity and feasibility of the approach was proved by using fewer Chirplet atoms to acquire more accurate feature information compared with Gabor atoms approach.