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Nowadays, the traditional parameters recognition method cannot match the requirements of the increasing new modulation radar signals. In order to solve this problem, in this paper, it proposes the improved radar signal recognition algorithm based on fractal theory and Neural Network theory. Taking the advantage of the characteristics of relevant dimension which will be able to measure the relevant complex degree of the radial source signals, we extract the relevant point as the input of neutral network in order to recognize and classify the signals. Simulation results show that, this algorithm has a distinguish effect on classification under low SNR, which is suitable for the feature extraction and recognition of various styles of radar signals.

The Improved Radial Source Recognition Algorithm Based on Fractal Theory and Neural Network Theory