Journal of Northeastern University Natural Science ›› 2019, Vol. 40 ›› Issue (11): 1555-1560.DOI: 10.12068/j.issn.1005-3026.2019.11.007

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Low Signal to Noise Ratio Radar Signal Sorting Algorithm Based on FastICA

WANG Bin, GAO Bing, GU Pei-shang, XIN Feng-ming   

  1. School of Computer & Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China.
  • Received:2018-11-08 Revised:2018-11-08 Online:2019-11-15 Published:2019-11-05
  • Contact: WANG Bin
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Abstract: The traditional parameter-based signal sorting system cannot adapt to the problem of radar signal sorting in the current complex situation, and the blind source separation algorithm based on independent component analysis(ICA)is introduced into the radar signal sorting algorithm. FastICA algorithm combines fixed-point iteration and non-Gaussian maximization algorithm. It has the advantages of good stability, fast convergence and small calculation. However, this algorithm is very sensitive to noise and cannot be performed with low SNR. Aiming at this shortcoming, a synchronous cumulative average noise reduction algorithm is introduced, and signal equalization and smoothing to improve the original algorithm are combined, so that the new algorithm can sort the radar signals with low SNR. Simulation results show that the improved algorithm can achieve good sorting effect under low SNR and retain the advantages of the original algorithm.

Key words: independent component analysis(ICA), blind source separation, signal sorting, FastICA, synchronous accumulative average noise reduction

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