In order to assess threat of reentry-course ballistic missile comprehensively and rationally,a concept of defense object is put forward,which is integration of conservation-shot resource and theater critical area;then index system of threat assessment of reentry-course ballistic missile and frame of model is constructed;on this basis,quantized method of index system is gived and threat assessment model of multiple defense object and multiple ballistic missile is established;frame and algorithm flow of grey relationship analysis based on entropy is proposed. Practically applications indicate that the model is valid and the algorithm is feasible.

To improve the accuracy and reliability of modulation recognition at low signal to noise ratio (SNR) and few knowledge of signal parameter, the novel method based on the cyclic spectral feature and support vector machine(SVM) is presented. In the process of novel algorithms, the cyclic spectral analysis is used to realize the feature extract of the modulated signals, and the Eigenface method is used to reduce the amount of spectral coherence feature. Then, a new scheme of classification based on support vector machine is presented to classify the modulation signal. The experiment shows that the modulation classification accuracy of presented method is significantly improved at low SNR environment.