Two-dimensional DOA estimation algorithm based on unitary ESPRIT under parallel nested arrays

Parallel nested arrays, as a new type of array structure, significantly improve the spatial resolution and array degrees of freedom of the system by combining two sub arrays with different spacing. This article conducts in-depth research on the two-dimensional direction estimation (DOA) algorithm based on unitary ESPRIT under parallel nested array structures. Firstly, a detailed analysis was conducted on the structural characteristics of parallel nested arrays, emphasizing their importance in improving DOA estimation performance. Secondly, the two-dimensional DOA estimation algorithm based on unitary ESPRIT was explored from the aspects of sub array output signal processing, cross covariance matrix construction, virtual array and dimensionality reduction estimation. Finally, the DOA estimation process was analyzed, providing an effective method for two-dimensional DOA estimation under parallel nested array structures.