Improved power inversion algorithm based on derivative constraint

doi:10.23919/JSEE.2025.000105

Journal of Systems Engineering and Electronics ›› 2025, Vol. 36 ›› Issue (6): 1398-1406.doi: 10.23919/JSEE.2025.000105

• ELECTRONICS TECHNOLOGY • Previous Articles

Improved power inversion algorithm based on derivative constraint

Runnan WANG¹(), Hongchang LIU²(), Siyuan JIANG³(), Shuai LIU¹^,*()

¹ School of Information Science and Engineering, Harbin Institute of Technology, Weihai 264209, China
² Unit 63891 of Chinese People’s Liberation Army, Luoyang 471000, China
³ School of Information Science and Engineering, Harbin Institute of Technology, Harbin 150001, China

Received:2024-01-08 Accepted:2025-07-01 Online:2025-12-18 Published:2026-01-07
Contact: Shuai LIU E-mail:wennuan0212@163.com;328641792@qq.com;siyuanjiang1997@163.com;liu-shuai@hit.edu.cn
About author:
WANG Runnan was born in 1999. She received her B.E. degree in electronic information engineering from Wuhan University of Technology, Wuhan, China, in 2022, M.S. degree in information science and engineering from Harbin Institute of Technology (HIT), Weihai, China, in 2025. Her research interest is array signal processing. E-mail: wennuan0212@163.com

LIU Hongchang was born in 1984. He received his B.E. degree in launch engineering and M.S. degree in armament launch theory and technology from People’s Liberation Army Ordnance Engineering College, Shijiazhuang, China, in 2006 and 2009, respectively. He is an engineer in Unit 63891 of Chinese People’s Liberation Army, Luoyang, China. His research interest is radar and radar countermeasure. E-mail: 328641792@qq.com

JIANG Siyuan was born in 1997. He received his B.E. degree and M.S. degree respectively in electronic and information engineering from Tianjin University of Science and Technology, Tianjin, China, in 2019, and in electronic and communication engineering from Harbin Institute of Technology (HIT), Harbin, China, in 2021. Since 2021, he has begun working toward his Ph.D. degree with the Department of Electronics Information Engineering, HIT, Harbin, China. His current research interests include array signal processing and statistical performance analysis. E-mail: siyuanjiang1997@163.com

LIU Shuai was born in 1980. He received his B.E. and M.S. degrees from Northwestern Polytechnical University, China, in 2002 and 2005, respectively, and Ph.D. degree in information and communication engineering from Harbin Institute of Technology (HIT), Weihai, China, in 2013. He is a professor and a lecturer of the School of Information Science and Engineering, HIT, Weihai, China. His current research interests are robust adaptive beamforming, conformal array, polarization-DOA parameter estimation method, and radar electronic countermeasures. E-mail: liu-shuai@hit.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (62071144).

Abstract

Abstract:

The power inversion (PI) algorithm lacks specific constraints on desired signals. Thus, the beampattern has fluctuation in all directions other than the jamming sources. This phenomenon will damage the reception of desired signals. In high signal-to-noise ratio (SNR) application, the desired signal is inevitably suppressed by the PI algorithm, resulting in a deterioration to the out signal-to-interference-and-noise ratio (SINR). This paper proposes an improved PI algorithm based on derivative constraint. Firstly, the proposed method uses subspace projection to extract jamming-free data, the derivative constraint is imposed to the non-jamming data, and subsequently the Lagrange multiplier can be used to calculate the array weight vector. Simulation results demonstrate that, the proposed algorithm in this paper has a higher output SNR, flat gains in non-jamming directions, and applicability of high SINR than the PI algorithm, thus verifying the effectiveness of the algorithm.

Key words: power inversion (PI), subspace projection, derivative constraint, flat gain

Runnan WANG, Hongchang LIU, Siyuan JIANG, Shuai LIU. Improved power inversion algorithm based on derivative constraint[J]. Journal of Systems Engineering and Electronics, 2025, 36(6): 1398-1406.

Figures/Tables 5

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Improved power inversion algorithm based on derivative constraint

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