Open AccessGridless DOA estimation based on multivariate function genetic optimisation
Author(s) -
Pan Meihong,
Zhang Gong
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0378
Subject(s) - multivariate statistics , computer science , genetic algorithm , grid , algorithm , function (biology) , estimation , mathematical optimization , mathematics , machine learning , engineering , geometry , evolutionary biology , biology , systems engineering
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.