Gridless DOA estimation based on multivariate function genetic optimisation

• Main Authors: Meihong Pan, Gong Zhang
• Format: Article
• Language: English
• Published: Wiley 2019-07-01
• Series: The Journal of Engineering
• Subjects: image reconstruction; genetic algorithms; direction-of-arrival estimation; direction-of-arrival estimation method; multivariate function genetic optimisation; estimated signal; genetic algorithm; gridless pathway; on-grid sparse reconstruction algorithm; estimation accuracy; DOA estimation precision; grid-based sparse reconstruction algorithm; gridless DOA estimation; optimisation process
• Online Access: https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0378

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.