Effect of Sparse Array Geometry on Estimation of Co-array Signal Subspace
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Feb 05, 2021
- Source ID
- 10.47037/2020.aces.j.351186
Entities
People
- Mehmet Hucumenoglu
- Piya Pal
Organizations
- National Science Foundation
- Office of Naval Research
- University of California, San Diego