Multiple transformation analysis for interference separation in TDCS

doi:10.23919/JSEE.2022.000104

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (5): 1064-1078.doi: 10.23919/JSEE.2022.000104

• ELECTRONICS TECHNOLOGY • Previous Articles Next Articles

Multiple transformation analysis for interference separation in TDCS

Guisheng WANG^1,^3,*(), Yequn WANG^1,²(), Shufu DONG¹(), Guoce HUANG¹()

¹ Information and Navigation College, Air Force Engineering University, Xi’an 710077, China
² The 30th Research Institute of China Electronics Technology Corporation, Chengdu 610054, China
³ National Key Laboratory of Airspace Technology Beijing 100192, China

Received:2020-09-04 Accepted:2021-11-24 Online:2022-10-27 Published:2022-10-27
Contact: Guisheng WANG E-mail:wgsfuyun@163.com;kgdwyq@126.com;kgddsf@126.com;kgdhgc@126.com
About author:|WANG Guisheng was born in 1979. He received his M.S. degree in military communication from the Information and Navigation College, Air Force Engineering University, Xi’an, China, in 2018, where he is currently pursuing his Ph.D. degree in information and communication engineering. He is an engineer in the National Key Laboratory of Airspace Technology. His research interests include compressive sensing based anti-jamming and military aeronautical and cognitive communication. E-mail: wgsfuyun@163.com||WANG Yequn was born in 1985. He received his M.S. and Ph.D. degrees from Air Force Engineering University in 2009 and 2012, respectively, where he is a currently a lecturer with the Information and Navigation College. His main research interests include aeronautical communication, ad hoc networks, satellite, and high frequency communication. E-mail: kgdwyq@126.com||DONG Shufu was born in 1970. He received his M.S. degree from Air Force Engineering University, in 1997, and his Ph.D. degree from Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China, in 2005. He is currently a professor with the Information and Navigation College, Air Force Engineering University. His main research interests include aeronautical and communication networking. E-mail: kgddsf@126.com||HUANG Guoce was born in 1962. He received his M.S. degree from Air Force Telecommunication Engineering College, Xi’an, China, in 1990. He is currently a doctoral supervisor and a professor with the Information and Navigation College, Air Force Engineering University. His main research interests include high frequency communication, aeronautical communication, and satellite communication.E-mail: kgdhgc@126.com
Supported by:
This work was supported by the University Cooperation Project Foundation of the Key Laboratory for Aerospace Information Technology (KX162600022)

Abstract

Abstract:

Various types of interference signals limit the practical application of transform domain communication systems (TDCSs) in the severe electromagnetic field, an orthogonal basis learning method of transformation analysis (OBL-TA) is proposed to effectively address the problem of obtaining an optimal transform domain based on sparse representation. Then, the sparse availability is utilized to obtain the optimal transformation analysis by the iterative methods, which yields the sparse representation for transform domain (SRTD) in unrestricted form. In addition, the iterative version of SRTD (I-SRTD) in unrestricted form is obtained by decomposing the SRTD problem into three sub-problems and each sub-problem is iteratively solved by learning the best orthogonal basis. Furthermore, orthogonal basis learning via cost function minimization process is conducted by stochastic descent, which is assured to converge to a local minimum at least. Finally, the optimal transformation analysis is developed by the effectiveness of different transform domains according to the accuracy of the sparse representation and an optimal transformation analysis separately (OPTAS) is applied to the synthesized signal forms with conic alternatives, dualization, and smoothing. Simulation results demonstrate that the superiorities of the proposed methods achieve the optimal recovery and separation more rapidly and accurately than conventional methods.

Key words: transformation analysis, interference separation, sparse representation, transform domain communication system (TDCS)

Guisheng WANG, Yequn WANG, Shufu DONG, Guoce HUANG. Multiple transformation analysis for interference separation in TDCS[J]. Journal of Systems Engineering and Electronics, 2022, 33(5): 1064-1078.

Figures/Tables 14

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Interference type	Frequency	Bandwidth	Amplitude
Multi-tone	Constant	Constant	Random
Comb-spectrum	Regular	Constant	Regular
Chirp	Regular	Regular	Constant
Frequency modulation for noise	Regular	Regular	Constant

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Multiple transformation analysis for interference separation in TDCS

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