{"title":"基于组合搜索策略的改进粒子群优化算法用于干扰组网雷达系统的多干扰源资源分配","authors":"Wei-qi Zou, Chao-yang Niu, Wei Liu, Yan-yun Wang, Jia-qi Zhan","doi":"10.1049/sil2.12198","DOIUrl":null,"url":null,"abstract":"<p>This paper presents a new algorithm named combination search strategy (CSS)-based improved particle swarm optimisation (IPSO) to address the resource allocation problem of multiple jammers. First, the authors propose a CSS to effectively broaden the limited search range of the two-step solving framework. This method not only simplifies the solution framework but also considers the combined relationship between beam pointing and transmit power to determine the global solution to the original problem directly. Second, the authors propose the IPSO because the complexity of the decision variables is increased by CSS. This method can change the focus of searching the optimal solution at different stages, correct the direction of particle evolution over time and avoid the interference between the variables. Finally, this study simulates the problem of resource allocation of multiple jammers based on the CSS-IPSO. Based on the simulation results, the combined search strategy can obtain better resource allocation results in a short time, and the IPSO algorithm can further improve the accuracy and stability of the resource allocation results.</p>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sil2.12198","citationCount":"0","resultStr":"{\"title\":\"Combination search strategy-based improved particle swarm optimisation for resource allocation of multiple jammers for jamming netted radar system\",\"authors\":\"Wei-qi Zou, Chao-yang Niu, Wei Liu, Yan-yun Wang, Jia-qi Zhan\",\"doi\":\"10.1049/sil2.12198\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper presents a new algorithm named combination search strategy (CSS)-based improved particle swarm optimisation (IPSO) to address the resource allocation problem of multiple jammers. First, the authors propose a CSS to effectively broaden the limited search range of the two-step solving framework. This method not only simplifies the solution framework but also considers the combined relationship between beam pointing and transmit power to determine the global solution to the original problem directly. Second, the authors propose the IPSO because the complexity of the decision variables is increased by CSS. This method can change the focus of searching the optimal solution at different stages, correct the direction of particle evolution over time and avoid the interference between the variables. Finally, this study simulates the problem of resource allocation of multiple jammers based on the CSS-IPSO. Based on the simulation results, the combined search strategy can obtain better resource allocation results in a short time, and the IPSO algorithm can further improve the accuracy and stability of the resource allocation results.</p>\",\"PeriodicalId\":56301,\"journal\":{\"name\":\"IET Signal Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sil2.12198\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/sil2.12198\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/sil2.12198","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Combination search strategy-based improved particle swarm optimisation for resource allocation of multiple jammers for jamming netted radar system
This paper presents a new algorithm named combination search strategy (CSS)-based improved particle swarm optimisation (IPSO) to address the resource allocation problem of multiple jammers. First, the authors propose a CSS to effectively broaden the limited search range of the two-step solving framework. This method not only simplifies the solution framework but also considers the combined relationship between beam pointing and transmit power to determine the global solution to the original problem directly. Second, the authors propose the IPSO because the complexity of the decision variables is increased by CSS. This method can change the focus of searching the optimal solution at different stages, correct the direction of particle evolution over time and avoid the interference between the variables. Finally, this study simulates the problem of resource allocation of multiple jammers based on the CSS-IPSO. Based on the simulation results, the combined search strategy can obtain better resource allocation results in a short time, and the IPSO algorithm can further improve the accuracy and stability of the resource allocation results.
期刊介绍:
IET Signal Processing publishes research on a diverse range of signal processing and machine learning topics, covering a variety of applications, disciplines, modalities, and techniques in detection, estimation, inference, and classification problems. The research published includes advances in algorithm design for the analysis of single and high-multi-dimensional data, sparsity, linear and non-linear systems, recursive and non-recursive digital filters and multi-rate filter banks, as well a range of topics that span from sensor array processing, deep convolutional neural network based approaches to the application of chaos theory, and far more.
Topics covered by scope include, but are not limited to:
advances in single and multi-dimensional filter design and implementation
linear and nonlinear, fixed and adaptive digital filters and multirate filter banks
statistical signal processing techniques and analysis
classical, parametric and higher order spectral analysis
signal transformation and compression techniques, including time-frequency analysis
system modelling and adaptive identification techniques
machine learning based approaches to signal processing
Bayesian methods for signal processing, including Monte-Carlo Markov-chain and particle filtering techniques
theory and application of blind and semi-blind signal separation techniques
signal processing techniques for analysis, enhancement, coding, synthesis and recognition of speech signals
direction-finding and beamforming techniques for audio and electromagnetic signals
analysis techniques for biomedical signals
baseband signal processing techniques for transmission and reception of communication signals
signal processing techniques for data hiding and audio watermarking
sparse signal processing and compressive sensing
Special Issue Call for Papers:
Intelligent Deep Fuzzy Model for Signal Processing - https://digital-library.theiet.org/files/IET_SPR_CFP_IDFMSP.pdf