Improved de-interleaving algorithm of radar pulses based on dual fuzzy vigilance ART

doi:10.23919/JSEE.2020.000008

Journal of Systems Engineering and Electronics ›› 2020, Vol. 31 ›› Issue (2): 303-311.doi: 10.23919/JSEE.2020.000008

• Defence Electronics Technology • Previous Articles Next Articles

Improved de-interleaving algorithm of radar pulses based on dual fuzzy vigilance ART

Wen JIANG(), Xiongjun FU*(), Jiayun CHANG()

School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China

Received:2019-07-03 Online:2020-04-30 Published:2020-04-30
Contact: Xiongjun FU E-mail:jwen912@126.com;fuxiongjun@bit.edu.cn;824400828@qq.com
About author:JIANG Wen was born in 1991. He received his M.S. degree from Zhengzhou University, China, in 2016. He is currently a doctoral student in School of Information and Electronics, Beijing Institute of Technology (BIT). His research interests include radar signal processing and radar pulses de-interleaving. E-mail: jwen912@126.com|FU Xiongjun was born in 1978. He received his B.Eng. degree and his Ph.D. degree from Beijing Institute of Technology (BIT), China, in 2000 and 2005 respectively. He is currently the vice dean of the School of Information and Electronics, BIT, and an associate professor and Ph.D. supervisor with BIT. His research interests include radar system, radar signal processing, waveform design, and automatic target recognition.E-mail: fuxiongjun@bit.edu.cn|CHANG Jiayun was born in 1989. She received her M.S. degree from Beijing Institute of Technology (BIT), China, in 2016. Currently, she is a doctoral student in School of Information and Electronics, BIT. Her research interests include automatic target recognition and radar signal processing. E-mail: 824400828@qq.com
Supported by:
the National Natural Science Foundation of China(61571043);the 111 Project of China(B14010);This work was supported by the National Natural Science Foundation of China (61571043) and the 111 Project of China (B14010)

Abstract

Abstract:

As a core part of the electronic warfare (EW) system, de-interleaving is used to separate interleaved radar signals. The de-interleaving algorithm based on the fuzzy adaptive resonance theory (fuzzy ART) is plagued by the problems of premature saturation and performance improving dilemma. This study proposes a dual fuzzy vigilance ART (DFV-ART) algorithm to address these problems and make the following improvements. Firstly, a correction method is introduced to prevent the network from prematurely saturating; then, the fuzzy vigilance models (FVM) are constructed to replace the conventional vigilance parameter, reducing the error probability in the overlapping region; finally, a dual vigilance mechanism is introduced to solve the performance improving dilemma. Simulation results show that the proposed algorithm could improve the clustering accuracy (quantization error dropped 60%) and the de-interleaving performance (clustering quality increased by 10%) while suppressing the excessive proliferation of categories.

Key words: fuzzy adaptive resonance theory (fuzzy ART), de-interleaving, dual vigilance mechanism.

Wen JIANG, Xiongjun FU, Jiayun CHANG. Improved de-interleaving algorithm of radar pulses based on dual fuzzy vigilance ART[J]. Journal of Systems Engineering and Electronics, 2020, 31(2): 303-311.

Figures/Tables 10

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Radar	AOA/($^\circ$)	PW/μs	PF/MHz	PRI/μs
1	55	2	1 000	Constant: 270
2	85	3.5	1 200	Constant: 1 500
3	115	5	1 400	Grops: 416/458/471/594
4	145	6.5	1 600	Jitter: 15%; Center: 750
5	175	8	1 800	Hopping: 10%; Center: 1 100
6	55	3.5	1 300	Constant: 270
7	115	3.5	1 300	Constant: 270
8	145	3.5	1 300	Constant: 270
9	175	3.5	1 300	Constant: 270
10	115	6.5	1 000	Constant: 500
11	115	6.5	1 200	Constant: 500
12	115	6.5	1 400	Constant: 500
13	115	6.5	1 600	Constant: 500

Algorithm	Computational complexity
Fuzzy ART	$N_1 \times C_M + C_I + C_V + C_U$
T1-FA	$N_2 \times C_M + C_I + 2C_V + C_U$
DFV-ART	$N_3 \times C_M + 2C_I + 4C_V + C_U$

Improved de-interleaving algorithm of radar pulses based on dual fuzzy vigilance ART

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