Direction of Arrival Estimation for Off-Grid Signals Based on Sparse Bayesian Learning

@article{Wu2016DirectionOA,
  title={Direction of Arrival Estimation for Off-Grid Signals Based on Sparse Bayesian Learning},
  author={Xiaohuan Wu and Jun Yan},
  journal={IEEE Sensors Journal},
  year={2016},
  volume={16},
  pages={2004-2016}
}
The inherent limitation of the predefined spatial discrete grids greatly restricts the precision and feasibility of many sparse signal representation (SSR)-based direction-of-arrival (DOA) estimators. In this paper, we first propose a perturbed SSR-based model to alleviate this limitation by incorporating a bias parameter into the DOA estimation framework. Using this model, a perturbed sparse Bayesian learning-based algorithm, named PSBL, is developed to solve the DOA estimation problem… CONTINUE READING
Highly Cited
This paper has 54 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 26 extracted citations

55 Citations

02040201620172018
Citations per Year
Semantic Scholar estimates that this publication has 55 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 39 references

Similar Papers

Loading similar papers…