In this paper, the problem of one-bit quantized signal direction-of-arrival (DOA) estimation via sparse array is considered. The proposed method first gives an approximate reconstruction method to extend the aperture of sparse array, then a compressive sensing method is presented to obtain accurate...
We first reformulate DOA estimation as a maximum a posteriori (MAP) problem, unifying on-grid and off-grid scenarios under a Laplacian-type sparsity prior to effectively enforce sparsity for both uniform and sparse linear arrays. For off-grid signals, a first-order approximation grid model is ...
One-bit sparse array DOA estimation. In Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA, 5–9 March 2017; pp. 3126–3130. [Google Scholar] Ge, S.; Fan, C.; Wang, J.; Huang, X. Low-complexity one-bit ...
Existing one-bit direction of arrival (DOA) estimate methods based on sparse recovery or subspace have issues when used for massive uniform linear arrays (MULAs), such as high computing cost, estimation accuracy depending on grid size, or high snapshot-number requirements. This paper considers the...
Existing one-bit direction of arrival (DOA) estimate methods based on sparse recovery or subspace have issues when used for massive uniform linear arrays (MULAs), such as high computing cost, estimation accuracy depending on grid size, or high snapshot-number requirements. This paper considers the...
Existing one-bit direction of arrival (DOA) estimate methods based on sparse recovery or subspace have issues when used for massive uniform linear arrays (MULAs), such as high computing cost, estimation accuracy depending on grid size, or high snapshot-number requirements. This paper considers the...