{"title":"基于模因粒子群算法的多路径DOA估计","authors":"J. Hung","doi":"10.1109/CCSSE.2016.7784348","DOIUrl":null,"url":null,"abstract":"This paper introduces a new combine of Memetic particle swarm optimum (MPSO) and beam-space oblique projection operator method suitable for dealing with direction of arrival (DOA) under a multipath environment. Generally, oblique projection operator is applied to project measurements onto a low-rank subspace along a direction that is oblique to the subspace and it enhance signals while nulling interferences. However, the method will be biased under a multipath environment. Therefore, we have proposed the beam-space oblique projection operator by MPSO scheme for DOA under a multipath environment. The MPSO that incorporates local search techniques applies in the particle swarm optimization (PSO) and the procedure as follow: first, we used the PSO to estimate the signal DOA by oblique projection operator method. Second, the personal best position of the swarm to set up beam-space oblique projection operator and using gradient-based techniques to enhance exact. The MPSO uses beam-space rebuilding oblique projection operator for local search techniques to address the issue of reduce multipath effect and increase find exact DOA estimation. Finally, numerical example with different a multipath environment is presented to illustrate the design procedure and to confirm the performance of the proposed method.","PeriodicalId":136809,"journal":{"name":"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Memetic particle swarm optimization algorithm for DOA estimation under multipath environment\",\"authors\":\"J. Hung\",\"doi\":\"10.1109/CCSSE.2016.7784348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a new combine of Memetic particle swarm optimum (MPSO) and beam-space oblique projection operator method suitable for dealing with direction of arrival (DOA) under a multipath environment. Generally, oblique projection operator is applied to project measurements onto a low-rank subspace along a direction that is oblique to the subspace and it enhance signals while nulling interferences. However, the method will be biased under a multipath environment. Therefore, we have proposed the beam-space oblique projection operator by MPSO scheme for DOA under a multipath environment. The MPSO that incorporates local search techniques applies in the particle swarm optimization (PSO) and the procedure as follow: first, we used the PSO to estimate the signal DOA by oblique projection operator method. Second, the personal best position of the swarm to set up beam-space oblique projection operator and using gradient-based techniques to enhance exact. The MPSO uses beam-space rebuilding oblique projection operator for local search techniques to address the issue of reduce multipath effect and increase find exact DOA estimation. Finally, numerical example with different a multipath environment is presented to illustrate the design procedure and to confirm the performance of the proposed method.\",\"PeriodicalId\":136809,\"journal\":{\"name\":\"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)\",\"volume\":\"183 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCSSE.2016.7784348\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCSSE.2016.7784348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Memetic particle swarm optimization algorithm for DOA estimation under multipath environment
This paper introduces a new combine of Memetic particle swarm optimum (MPSO) and beam-space oblique projection operator method suitable for dealing with direction of arrival (DOA) under a multipath environment. Generally, oblique projection operator is applied to project measurements onto a low-rank subspace along a direction that is oblique to the subspace and it enhance signals while nulling interferences. However, the method will be biased under a multipath environment. Therefore, we have proposed the beam-space oblique projection operator by MPSO scheme for DOA under a multipath environment. The MPSO that incorporates local search techniques applies in the particle swarm optimization (PSO) and the procedure as follow: first, we used the PSO to estimate the signal DOA by oblique projection operator method. Second, the personal best position of the swarm to set up beam-space oblique projection operator and using gradient-based techniques to enhance exact. The MPSO uses beam-space rebuilding oblique projection operator for local search techniques to address the issue of reduce multipath effect and increase find exact DOA estimation. Finally, numerical example with different a multipath environment is presented to illustrate the design procedure and to confirm the performance of the proposed method.