Dongxu An , Hua Wang , Jinfeng Hu , Xin Tai , Xinsheng Peng , Kai Zhong , Yongfeng Zuo , Huiyong Li , Fulvio Gini
{"title":"频谱密集环境下宽带MIMO雷达波束成形","authors":"Dongxu An , Hua Wang , Jinfeng Hu , Xin Tai , Xinsheng Peng , Kai Zhong , Yongfeng Zuo , Huiyong Li , Fulvio Gini","doi":"10.1016/j.sigpro.2025.110122","DOIUrl":null,"url":null,"abstract":"<div><div>Wideband MIMO radar beampattern shaping with Constant Modulus Constraints (CMCs) in spectrally dense environments is critical for future 6G networked sensing technology. Existing methods minimize the weighted function of wideband MIMO radar beampattern matching Mean Square Error (MSE) and the Energy Spectral Density (ESD) of Spatial Spectral Nulling (SSN) region; however, achieving precise ESD control remains a challenge. To address this, we minimize the beampattern matching MSE under CMCs and precise SSN Constraints (SSNCs). The non-convex nature of the CMCs and multiple SSNCs lead to a non-convex Quadratic-Constrained Quadratic Programming (QCQP) problem. To solve the problem, we propose a novel Manifold-Based Exact Penalty (MBEP) method. First, we construct the Complex Circular Manifold (CCM) to satisfy the CMCs and reformulate the SSNCs as an exact penalty function, thereby transforming the problem into an unconstrained optimization problem on the CCM. Subsequently, a Simplified Quasi-Newton (SQN) method is developed to optimize the problem on the CCM. Finally, the penalty factor is adaptively updated to improve the optimization process. Compared with existing methods: 1) the proposed method achieves precise control of the ESD level in the SSN region; and 2) the ESD in the SSN region is reduced by 8.8 dB, while the beampattern matching MSE is decreased by 0.02 dB.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110122"},"PeriodicalIF":3.4000,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wideband MIMO radar beampattern shaping in spectrally dense environments\",\"authors\":\"Dongxu An , Hua Wang , Jinfeng Hu , Xin Tai , Xinsheng Peng , Kai Zhong , Yongfeng Zuo , Huiyong Li , Fulvio Gini\",\"doi\":\"10.1016/j.sigpro.2025.110122\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Wideband MIMO radar beampattern shaping with Constant Modulus Constraints (CMCs) in spectrally dense environments is critical for future 6G networked sensing technology. Existing methods minimize the weighted function of wideband MIMO radar beampattern matching Mean Square Error (MSE) and the Energy Spectral Density (ESD) of Spatial Spectral Nulling (SSN) region; however, achieving precise ESD control remains a challenge. To address this, we minimize the beampattern matching MSE under CMCs and precise SSN Constraints (SSNCs). The non-convex nature of the CMCs and multiple SSNCs lead to a non-convex Quadratic-Constrained Quadratic Programming (QCQP) problem. To solve the problem, we propose a novel Manifold-Based Exact Penalty (MBEP) method. First, we construct the Complex Circular Manifold (CCM) to satisfy the CMCs and reformulate the SSNCs as an exact penalty function, thereby transforming the problem into an unconstrained optimization problem on the CCM. Subsequently, a Simplified Quasi-Newton (SQN) method is developed to optimize the problem on the CCM. Finally, the penalty factor is adaptively updated to improve the optimization process. Compared with existing methods: 1) the proposed method achieves precise control of the ESD level in the SSN region; and 2) the ESD in the SSN region is reduced by 8.8 dB, while the beampattern matching MSE is decreased by 0.02 dB.</div></div>\",\"PeriodicalId\":49523,\"journal\":{\"name\":\"Signal Processing\",\"volume\":\"238 \",\"pages\":\"Article 110122\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0165168425002361\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165168425002361","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Wideband MIMO radar beampattern shaping in spectrally dense environments
Wideband MIMO radar beampattern shaping with Constant Modulus Constraints (CMCs) in spectrally dense environments is critical for future 6G networked sensing technology. Existing methods minimize the weighted function of wideband MIMO radar beampattern matching Mean Square Error (MSE) and the Energy Spectral Density (ESD) of Spatial Spectral Nulling (SSN) region; however, achieving precise ESD control remains a challenge. To address this, we minimize the beampattern matching MSE under CMCs and precise SSN Constraints (SSNCs). The non-convex nature of the CMCs and multiple SSNCs lead to a non-convex Quadratic-Constrained Quadratic Programming (QCQP) problem. To solve the problem, we propose a novel Manifold-Based Exact Penalty (MBEP) method. First, we construct the Complex Circular Manifold (CCM) to satisfy the CMCs and reformulate the SSNCs as an exact penalty function, thereby transforming the problem into an unconstrained optimization problem on the CCM. Subsequently, a Simplified Quasi-Newton (SQN) method is developed to optimize the problem on the CCM. Finally, the penalty factor is adaptively updated to improve the optimization process. Compared with existing methods: 1) the proposed method achieves precise control of the ESD level in the SSN region; and 2) the ESD in the SSN region is reduced by 8.8 dB, while the beampattern matching MSE is decreased by 0.02 dB.
期刊介绍:
Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing.
Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.