The Evaluation Of Features For Advanced Radar Emitter Signals

As the electronic warfare becoming more and more fierce, a number of theoretical problems brought by the signal processing of radar countermeasures need to be solved. Sub-selection identification based on the conventional five parameters (carrier frequency of the RF, pulse time of arrival TO A, the PA of the pulse amplitude, pulse width PW, pulse direction of arrival DOA) can not adapt to modern electronic warfare signal environments with a variety of complex system radars (such as pulse frequency modulation, phase encoding, frequency agility, PRI agility, etc.). Electronic experts have made a lot of research on radar emitter signals in time domain and frequency domain, and many signal features of radar emitter have been put forward. However, the evaluation system of the radar emitter signals’features was not perfect, therefore, some of the features can’t been well applied to practical environment. Based on this, this article constructs the evaluation model of radar emitter signals feature, and uses the evaluation model to make a comprehensive evaluation for the radar emitter signal features.1. Evaluate the status quo of radar emitter signal feature at home and abroad, and point out the problems need to be solved, and at last construct a emitter signal feature evaluation model.2. Analyse the extraction algorithm based on wavelet packet features, the instantaneous frequency derived features and time-frequency atoms potential modulation features respectively, in view of the high dimension of the wavelet packet features, some of the dimensional feature being interrupted serious by noise and the redundance of the features, the ReliefF algorithm was used to select the sorting ability to identify strong features in order to achieve the reduction of the features of dimensionality and the improvement of the correct recognition rate. The radar emitter signal(Conventional pulse signal, the chirp signal, non-linear FM pulse, two-phase encoded signals, four-phase encoded signals, the modulation parameters of the two frequency encoded signals) modulation parameters was changed in order to verify the stability of the features of the signal parameters. It was used as one of the evaluation index.3. The features evaluation index system of the emitter signal was established from the features of complexity, separability, and the recognition rate of the signal, given the theoretical model of each feature evaluation algorithm. It includes the time complexity index, index of spatial complexity (including class within the class of the distance between the overlapping domain size feature efficiency, minimum spanning tree variable boundary, outside of class and class nearest neighbor distance, based on the LP, nonlinear1NN-based non-linear), the stability index based on the mutual information of the reparability index, signal recognition rate of the confidence interval and the recognition rate, and the data of all indicators was simulated in the experiment.4. A radar emitter signal features of the multi-objective decision-making based on fuzzy hierarchy evaluation model is established. The indicators mentioned in the article are integrated in order to assess the performance of the signal features more comprehensively and accurately. This model can provide a theoretical basis for the adding of the other new features.This work is funded by "the National Natural Science Foundation of the complex system of radar emitter signal features evaluation mechanism "(No.60971103).