Deinterleaving of Pulse Streams With Denoising Autoencoders

Analyzing radar signals is an important task in operating electronic support measure systems. The received signals in the real electromagnetic environment often originate from multiple emitters and must be separated for further processing. Pulses from important target emitters with known parameters...

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Vydáno v:IEEE transactions on aerospace and electronic systems Ročník 56; číslo 6; s. 4767 - 4778
Hlavní autoři: Li, Xueqiong, Liu, Zhangmeng, Huang, Zhitao
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.12.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Deinterleaving
denoising autoencoders
Electromagnetics
Emitters
Histograms
Modulation
Noise reduction
Performance degradation
Pulse measurements
Pulse repetition interval
pulse repetition interval (PRI)
pulse streams
Radar
Task analysis
time of arrival(TOA)
ISSN:0018-9251, 1557-9603
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Shrnutí:Analyzing radar signals is an important task in operating electronic support measure systems. The received signals in the real electromagnetic environment often originate from multiple emitters and must be separated for further processing. Pulses from important target emitters with known parameters should be picked out first. To solve the problem, time-of-arrival (TOA) deinterleaving may be performed to extract signals from a certain emitter by learning the pulse repetition interval (PRI) modulation that makes up the signal. However, conventional deinterleaving methods only work with simple PRI modulations; their performance degrades in noisy environments. A novel approach based on denoising autoencoders for TOA deinterleaving was developed in this article. The inner patterns of pulse-of-interest sequences were learned by the proposed denoising autoencoders to generate output sequences from well-trained autoencoders. Simulation results show that the proposed method outperforms conventional methods, especially in environments with high lost and spurious pulse ratios.
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ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2020.3004208