Stochastic resolution analysis of co-prime arrays in radar

Stochastic resolution analysis of co-prime arrays in radar

Pribic, R (Thales)
Coutino, Mario (TU Delft Signal Processing Systems)
Leus, G.J.T. (TU Delft Signal Processing Systems)

2016-08-25

Resolution from co-prime arrays and from a full ULA of the size equal to the virtual size of co-prime arrays is investigated. We take into account not only the resulting beam width but also the fact that fewer measurements are acquired by co-prime arrays. This fact is relevant in compressive acquisition typical for compressive sensing. Our stochastic approach to resolution uses information distances computed from the geometrical structure of data models that is characterized by the Fisher information. The probability of resolution is assessed from a likelihood ratio test by using information distances. Based on this information-geometry approach, we compare stochastic resolution from active co-prime arrays and from the full-size ULA. This novel stochastic resolution analysis is applied in a one-dimensional angle processing. Results demonstrate the suitability in radar-resolution analysis.

radar
resolution
information geometry
co-prime arrays
compressive sensing

http://resolver.tudelft.nl/uuid:c907114c-db9b-478e-b92d-f30c4733b3a5

https://doi.org/10.1109/ssp.2016.7551757

IEEE, Piscataway, NJ

978-1-4673-7802-4

2016 IEEE Statistical Signal Processing Workshop (SSP)

2016 IEEE Statistical Signal Processing Workshop (SSP), 2016-06-26 → 2017-06-29, Palma de Mallorca, Spain

Institutional Repository

conference paper

© 2016 R Pribic, Mario Coutino, G.J.T. Leus