{"title":"一种增强的模拟卡尔曼滤波算法及其在自适应波束形成中的应用","authors":"K. Lazarus, N. H. Noordin, Z. Ibrahim","doi":"10.1109/RFM.2018.8846519","DOIUrl":null,"url":null,"abstract":"The Simulated Kalman Filter (SKF) algorithm is a newly introduced optimization algorithm inspired by the estimation capabilities of Kalman filter. In this paper, a population based metaheuristic algorithm named Simulated Kalman Filter with Modified Measurement (SKFMM) is proposed for adaptive beamforming application. SKFMM is compared with the existing SKF and OBSKF algorithms for adaptive beamforming. The experimental results show that the SKFMM algorithm can produce better mean Signal to Interference Plus Noise Ratio (SINR) values compared to the current SKF and OBSKF algorithms for adaptive beamforming application, producing statistically significant results.","PeriodicalId":111726,"journal":{"name":"2018 IEEE International RF and Microwave Conference (RFM)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Enhanced Simulated Kalman Filter Algorithm and its Application in Adaptive Beamforming\",\"authors\":\"K. Lazarus, N. H. Noordin, Z. Ibrahim\",\"doi\":\"10.1109/RFM.2018.8846519\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Simulated Kalman Filter (SKF) algorithm is a newly introduced optimization algorithm inspired by the estimation capabilities of Kalman filter. In this paper, a population based metaheuristic algorithm named Simulated Kalman Filter with Modified Measurement (SKFMM) is proposed for adaptive beamforming application. SKFMM is compared with the existing SKF and OBSKF algorithms for adaptive beamforming. The experimental results show that the SKFMM algorithm can produce better mean Signal to Interference Plus Noise Ratio (SINR) values compared to the current SKF and OBSKF algorithms for adaptive beamforming application, producing statistically significant results.\",\"PeriodicalId\":111726,\"journal\":{\"name\":\"2018 IEEE International RF and Microwave Conference (RFM)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International RF and Microwave Conference (RFM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RFM.2018.8846519\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International RF and Microwave Conference (RFM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RFM.2018.8846519","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Enhanced Simulated Kalman Filter Algorithm and its Application in Adaptive Beamforming
The Simulated Kalman Filter (SKF) algorithm is a newly introduced optimization algorithm inspired by the estimation capabilities of Kalman filter. In this paper, a population based metaheuristic algorithm named Simulated Kalman Filter with Modified Measurement (SKFMM) is proposed for adaptive beamforming application. SKFMM is compared with the existing SKF and OBSKF algorithms for adaptive beamforming. The experimental results show that the SKFMM algorithm can produce better mean Signal to Interference Plus Noise Ratio (SINR) values compared to the current SKF and OBSKF algorithms for adaptive beamforming application, producing statistically significant results.