Hyperparameter free sparse estimation for wideband multiple-input-multiple-output radar direction finding without secondary data

The estimation of target directions of arrival (DOA) for wideband multiple-input-multiple-output (MIMO) radar is investigated in this article. First, the authors establish a signal model for wideband MIMO radar systems. Then, an algorithm is proposed to estimate the target angles without secondary data (i.e. the training data from slow-time is not required).The proposed algorithm unitises the spatial sparsity of target signals and it is derived under the Bayesian framework. It can estimate the spatial pseudo-spectra of the targets through cyclic optimisation. Additionally, it is hyperparameter-free and guarantees convergence. To analyse the performance of the proposed algorithm, the Cramér-Rao bound (CRB) is derived for DOA estimation with wideband MIMO radar. Numerical examples demonstrate that even without secondary data, the proposed algorithm can accurately estimate the DOA of the targets.