{"title":"An Enhanced MUSIC DoA Scanning Scheme for Array Radar Sensing in Autonomous Movers","authors":"Kuan-Ying Chang, Kuan-Ting Chen, W. Ma, Y. Hwang","doi":"10.1109/AICAS.2019.8771584","DOIUrl":null,"url":null,"abstract":"In this paper, we present an enhanced MUltiple SIgnal Classification (MUSIC) scheme for Direction of Arrival (DoA) scanning using a linear antenna array system. The goal is to construct an obstruction map based on the DoA scanning results for an autonomous mover when navigating in a pedestrian rich environment. A low complexity DoA estimation scheme, which eliminates the requirement of a computationally expensive Eigen Decomposition (ED) in conventional MUSIC algorithm, is developed. An Orthogonal Projection Matrix (OPM) scheme is used. Furthermore, a QR decomposition method is employed to implement the pseudo inverse matrix calculation required in the OPM scheme. This leads to a very computing efficient approach and facilitates real time implementation in hardware accelerators. The simulation results show that the proposed scheme can perform comparably to the conventional scheme at a much lower computing complexity.","PeriodicalId":273095,"journal":{"name":"2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICAS.2019.8771584","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper, we present an enhanced MUltiple SIgnal Classification (MUSIC) scheme for Direction of Arrival (DoA) scanning using a linear antenna array system. The goal is to construct an obstruction map based on the DoA scanning results for an autonomous mover when navigating in a pedestrian rich environment. A low complexity DoA estimation scheme, which eliminates the requirement of a computationally expensive Eigen Decomposition (ED) in conventional MUSIC algorithm, is developed. An Orthogonal Projection Matrix (OPM) scheme is used. Furthermore, a QR decomposition method is employed to implement the pseudo inverse matrix calculation required in the OPM scheme. This leads to a very computing efficient approach and facilitates real time implementation in hardware accelerators. The simulation results show that the proposed scheme can perform comparably to the conventional scheme at a much lower computing complexity.