Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3608
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dc.contributor.authorRao, Tata V Srinivasa-
dc.contributor.authorRoy, Lakshi Prosad-
dc.contributor.authorMahapatra, Kamalakanta-
dc.date.accessioned2021-12-29T12:27:36Z-
dc.date.available2021-12-29T12:27:36Z-
dc.date.issued2021-12-
dc.identifier.citation15th IEEE International conference on Advanced Networks and Telecommunications systems(ATNS 2021)en_US
dc.identifier.urihttp://hdl.handle.net/2080/3608-
dc.descriptionCopyright of this paper is with proceedings publisheren_US
dc.description.abstractHardware implementation for faster real-time sig- nal processing in multiple-input multiple-output (MIMO) radar beamforming by estimating direction of arrival (DOA) using multiple signal classification (MUSIC) is attractive. The above subspace-based method works with a basic principle of eigenvalue decomposition and is found suitable for application-specific in- tegrated circuit (ASIC), field-programmable gate array (FPGA). In that regard, the cyclic Jacobi method is used for computing eigenvalues and eigenvectors, by orthonormal plane rotations in accomplishing eigenvalue decomposition. However, the fasterness and foremost, the accuracy of the DOA estimator realized in such above hardware depends on the involved number of antenna elements in an array, the number of snapshots, and the signal-to- noise ratio. Therefore, the comparative study on DOA estimation error on the above mentioned parameters in MUSIC and QR- based algorithms is presented in this paperen_US
dc.language.isoenen_US
dc.subjectMIMO,en_US
dc.subjectDOA,en_US
dc.subjectMUSICen_US
dc.titleComparative Study on Error in MIMO Radar DOA Estimationen_US
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