Angular information resolution limit of sensor arrays

Cheng, Y, Wang, X and Moran, B 2014, 'Angular information resolution limit of sensor arrays', in Proceedings of the 8th Sensor Array and Multichannel Signal Processing Workshop (SAM 2014), A Coruna, Spain, 22-25 June 2014, pp. 89-92.


Document type: Conference Paper
Collection: Conference Papers

Title Angular information resolution limit of sensor arrays
Author(s) Cheng, Y
Wang, X
Moran, B
Year 2014
Conference name SAM 2014
Conference location A Coruna, Spain
Conference dates 22-25 June 2014
Proceedings title Proceedings of the 8th Sensor Array and Multichannel Signal Processing Workshop (SAM 2014)
Publisher IEEE
Place of publication United States
Start page 89
End page 92
Total pages 4
Abstract A measure of the ability of a sensor array to resolve two closely spaced point sources in angle is proposed here based on the framework of information geometry. The consideration of the geometric structure of a measurement model leads to the concept of information resolution which serves as a new metric to measure intrinsic similarities and differences between signal distributions that generate the manifold geometry. The statistical divergence between two sources is characterized in terms of the geodesic distance induced by the Fisher information metric. An analytical expression of the angular information resolution limit (AIRL) is derived using the constraints on the probability of error for a binary hypothesis test associated with the resolution of two sources. The influence of the detection error as well as the signal-to-noise ratio (SNK) on resolvability are demonstrated. The proposed AIRL can be used as a performance measure for sensor arrays in localizing remote sources and is applicable to various applications (e.g. radar, sonar, or astronomy).
Subjects Signal Processing
Stochastic Analysis and Modelling
Keyword(s) Fisher information matrix
Optical variables measurement
Radar astronomy Analytical expressions
Binary hypothesis tests
Fisher information metric
Geometric structure
Information geometry
Performance measure
Probability of errors
Signal distribution
DOI - identifier 10.1109/SAM.2014.6882345
Copyright notice © 2014 IEEE
ISBN 9781479914807
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