Identification and parameter estimation algorithm of radar signal subtle features

Abstract With the rapid development of electronic technology and its widespread application in modern warfare, the modulation methods of individual radar signal sources are more flexible, the parameters are diverse, and the modern battlefield electromagnetic signal environment is complex, so that radar signal recognition based on traditional conventional parameters Technology cannot meet real needs. Among the many radar signal modulation recognition algorithms that have appeared in recent years, neural network theory and intra-pulse analysis algorithms are widely used, but they each have their own shortcomings, and a single method cannot meet the needs of increasingly complex modulation signal recognition and parameter estimation needs. . Based on the above background, the research content of this paper is to identify the subtle characteristics of radar signals and their parameter estimation algorithms. In this paper, two types of typical modulation signals in intentional modulation of radar signals, namely phase-coded (PSK) signals and frequency-modulated (FM) signals, are proposed. A SVEFD algorithm based on classification from coarse to fine. According to the characteristics of the 3 dB bandwidth of the frequency spectrum of the PSK signal and the FM signal, the coarse classification between the classes is performed first. Finally, through experimental simulations, the results show that the correct recognition probability of the SVEFD algorithm at a lower signal-to-noise ratio is much higher than the m algorithm and also higher than the SVD algorithm. When the signal-to-noise ratio is greater than 1 dB, the average recognition rate reaches 94%, which proves that The effectiveness of the proposed SVEFD algorithm.When the signal-to-noise ratio is .1 dB, in addition to maintaining the correct recognition rate of more than 90% for the LFM and COSTAS signals, the other six types of signals have low correct recognition rates, so the SVEFD algorithm has advantages in comparison.