Mixed targets localization using symmetric nested frequency diverse array radar - Hui Chen; Wen‐Qin Wang; Wei Wang (IET Signal Processing)
Abstract A mixed near‐field and far‐field targets localization method based on sparse signal reconstruction and subspace method is presented, which can obtain both direction‐of‐arrival (DOA) and range information of the targets by utilizing symmetric nested frequency diverse array (SNFDA). Due to the frequency diverse array (FDA) owing time‐angle‐range‐dependent beampattern, the authors first properly design frequency increments and choose the sensor outputs to construct a fourth‐order cumulant matrix of SNFDA which is only related to DOAs of targets, and the authors estimate the DOAs of all targets by solving the ℓ1‐norm minimization convex optimization problem. Then a mixed range‐dependent overcomplete dictionary with DOAs estimation is formulated in the compressive sensing framework to classify targets types by using periodic characteristics of the estimated range‐dependent beampattern. Finally, the range estimations of all targets are obtained via 1‐D range‐domain spectral searching. Compared with the existing mixed near‐field and far‐field targets localization methods, the proposed method jointly uses FDA angle‐range‐dependent beampattern and increased degrees‐of‐freedom of nested array, which can achieve both improved resolutions and accuracies in DOAs and ranges estimation for all targets. A set of numerical examples is reported and discussed to validate the superiority of the proposed algorithm.