{"title":"Array Calibration Based on Improved Instrumental Sensors Method","authors":"Zeyang Dai, Xu Wang, Jian Liu","doi":"10.1109/CMC.2011.24","DOIUrl":null,"url":null,"abstract":"Instrumental Sensors Method (ISM) is an effective algorithm for joint estimation of signal Direction-of-Arrival(DOA) and direction-dependent array errors. However, this algorithm has some disadvantages, such as high computation complexity. In this paper, we propose an enhanced algorithm based on the basic ISM, in which there are two improvements to reduce the computation complexity. First, the improved algorithm combines least square method (LSM) with ISM to estimate signal DOA and direction-dependent array errors. Second, the improved algorithm simplifies matrix calculation when instrumental sensors are just one more than input signals. These two improvements can effectively estimate the signal'sDOA and direction-dependent array errors. The proposed algorithm has the same performance comparing with the basic ISM algorithm, but with the lower computation complexity. The simulation results show that the enhanced algorithm is effective, and it is convenient for the practice.","PeriodicalId":263741,"journal":{"name":"2011 Third International Conference on Communications and Mobile Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Third International Conference on Communications and Mobile Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CMC.2011.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Instrumental Sensors Method (ISM) is an effective algorithm for joint estimation of signal Direction-of-Arrival(DOA) and direction-dependent array errors. However, this algorithm has some disadvantages, such as high computation complexity. In this paper, we propose an enhanced algorithm based on the basic ISM, in which there are two improvements to reduce the computation complexity. First, the improved algorithm combines least square method (LSM) with ISM to estimate signal DOA and direction-dependent array errors. Second, the improved algorithm simplifies matrix calculation when instrumental sensors are just one more than input signals. These two improvements can effectively estimate the signal'sDOA and direction-dependent array errors. The proposed algorithm has the same performance comparing with the basic ISM algorithm, but with the lower computation complexity. The simulation results show that the enhanced algorithm is effective, and it is convenient for the practice.