Intelligent optimization methods of phase-modulation waveform

doi:10.23919/JSEE.2022.000089

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (4): 916-923.doi: 10.23919/JSEE.2022.000089

• DEFENCE ELECTRONICS TECHNOLOGY • Previous Articles Next Articles

Intelligent optimization methods of phase-modulation waveform

Jianwei SUN^1,²(), Chao WANG^1,^2,*(), Qingzhan SHI^1,²(), Wenbo REN^1,²(), Zekun YAO^1,²(), Naichang YUAN^1,²()

¹ College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China
² State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha 410073, China

Received:2021-01-21 Accepted:2022-03-21 Online:2022-08-30 Published:2022-08-30
Contact: Chao WANG E-mail:1195085653@qq.com;sywangc@163. com;qingzhan1990@163.com;464735596@qq.com;13177654355@163.com;yncwww@qq.com
About author:|SUN Jianwei was born in 1997. He received his B.S. degree from the National University of Defense Technology, Changsha, China, in 2019, where he is currently pursuing his M.S degree. His research interests are radio frequency and microwave technology. E-mail: 1195085653@qq.com||WANG Chao was born in 1977. He received his Ph.D. degree from the National University of Defense Technology (NUDT), Changsha, in 2007. He is currently an associate professor with NUDT. His research interest is electronic system design. E-mail: sywangc@163. com||SHI Qingzhan was born in 1990. He received his M.S. and Ph.D. degrees from the National University of Defense Technology (NUDT), Changsha, in 2015 and 2019, respectively. He is currently a lecturer with the NUDT. His research interest is signal processing. E-mail: qingzhan1990@163.com||REN Wenbo was born in 1995. He received his B.S. degree from the Southwest University of Science and Technology, Sichuan, China, in 2018. He is currently pursuing his M.S. degree in National University of Defense Technology. His research interests are microwave and millimeter-wave technology. E-mail: 464735596@qq.com||YAO Zekun was born in 1998. He received his B.S. degree from the National University of Defense Technology, Changsha, China, in 2020, where he is currently pursuing his M.S. degree. His research interests are radio frequency and microwave technology. E-mail: 13177654355@163.com||YUAN Naichang was born in 1965. He received his M.S. and Ph.D. degrees in electronic science and technology from the University of Electronic Science and Technology of China in 1991 and 1994, respectively. He is currently a professor with National University of Defense Technology. His research interests include signal processing and electronic system design. E-mail: yncwww@qq.com

Abstract

Abstract:

With the continuous improvement of radar intelligence, it is difficult for traditional countermeasures to achieve ideal results. In order to deal with complex, changeable, and unknown threat signals in the complex electromagnetic environment, a waveform intelligent optimization model based on intelligent optimization algorithm is proposed. By virtue of the universality and fast running speed of the intelligent optimization algorithm, the model can optimize the parameters used to synthesize the countermeasure waveform according to different external signals, so as to improve the countermeasure performance. Genetic algorithm (GA) and particle swarm optimization (PSO) are used to simulate the intelligent optimization of interrupted-sampling and phase-modulation repeater waveform. The experimental results under different radar signal conditions show that the scheme is feasible. The performance comparison between the algorithms and some problems in the experimental results also provide a certain reference for the follow-up work.

Key words: waveform optimization, intelligent optimization, phase-modulation, genetic algorithm (GA), particle swarm optimization (PSO)

Jianwei SUN, Chao WANG, Qingzhan SHI, Wenbo REN, Zekun YAO, Naichang YUAN. Intelligent optimization methods of phase-modulation waveform[J]. Journal of Systems Engineering and Electronics, 2022, 33(4): 916-923.

Figures/Tables 10

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References 36

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Parameter	Lower limit	Upper limit	Precision
Code width	0.1	4	0.1
Sampling time	1	10	0.5
Forwarding time	1	7	1
Lead time	0	10	0.5
Other constraints	$ {T_c} \leqslant {\text{0}}{\text{.4}}\tau $

Parameter	Detailed parameter
Radar signal 1	LFM (1 MHz, 64 μs)
Radar signal 2	LFM (1 MHz, 128 μs)
Radar signal 3	LFM (8 MHz, 64 μs)
Radar signal 4	PCM (2 MHz, 127 × 0.5 μs)
Radar signal 5	NLFM (8 MHz, 64 μs)
False alarm probability	10^?3
Protection unit	4
Average unit	16
Pseudo-random sequence	M sequence (511-bit)

Signal	Initial optimal	Global optimal
Signal 1	5.83	8.54
Signal 2	5.12	7.04
Signal 3	2.94	7.00
Signal 4	?2.83	2.76
Signal 5	4.59	7.06

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