Effect of Sparse Array Geometry on Estimation of Co-array Signal Subspace

Authors

  • Mehmet Can Huc¨ umeno ¨ glu University of California, San Diego
  • Piya Pal ˘ University of California, San Diego

Keywords:

Davis Kahan, Difference co-arrays, Sparse arrays, Subspace Estimation

Abstract

This paper considers the effect of sparse array geometry on the co-array signal subspace estimation error for Direction-of-Arrival (DOA) estimation. The second largest singular value of the signal covariance matrix plays an important role in controlling the distance between the true subspace and its estimate. For a special case of two closely-spaced sources impinging on the array, we explicitly compute the second largest singular value of the signal covariance matrix and show that it can be significantly larger for a nested array when compared against a uniform linear array with same number of sensors.

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References

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Published

2020-11-07

How to Cite

Mehmet Can Huc¨ umeno ¨ glu, & Piya Pal ˘. (2020). Effect of Sparse Array Geometry on Estimation of Co-array Signal Subspace. The Applied Computational Electromagnetics Society Journal (ACES), 35(11), 1435–1436. Retrieved from https://journals.riverpublishers.com/index.php/ACES/article/view/7637

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Articles