Title of Paper:Gridless DOA estimation based on multivariate function genetic optimisation

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Affiliation of Author(s):电子信息工程学院

Journal:J. Eng.

Abstract:Inspired by the optimisation process of multivariate function, a novel gridless direction-of-arrival (DOA) estimation method based on multivariate function genetic optimisation is proposed. The multivariate function is modelled as the difference between the estimated signal and the observed receiving data. The angles to be estimated are the variables of this function. The variables are calculated by minimising the multivariate function with the help of the genetic algorithm. The proposed algorithm can be seen as the gridless pathway to the traditional on-grid sparse reconstruction algorithm. This algorithm does not need to mesh the space into the discrete grid, so it can reduce the estimation accuracy caused by grid mismatch. Simulation results finally demonstrate the superiority of the proposed approach in terms of DOA estimation precision and computational efficiency over the grid-based sparse reconstruction algorithm. © 2019 Institution of Engineering and Technology. All rights reserved.

Translation or Not:no

Date of Publication:2019-10-01

Co-author:潘美虹

Correspondence Author:ZHANG Gong