A Lower Bound of DOA-Estimates by an Array Randomly Subject to Sensor-Breakdown

This paper introduces a new metric, to approximately lower-bound the error-variance in the estimation of an incident source's direction-of-arrival (DOA), for a sensor-array subject to random breakdown in its individual sensors. This new metric equals a weighted sum of Cramér-Rao bounds, each c...

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Bibliographic Details
Published inIEEE sensors journal Vol. 12; no. 5; pp. 911 - 913
Main Authors Wong, K. T., Wu, Y. I., Yu-Sheng Hsu, Yang Song
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2012
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Approximation
Array signal processing
Arrays
Computer simulation
Cramer-Rao bounds
direction of arrival estimation
Lower bounds
Maximum likelihood detection
Maximum likelihood estimation
Measurement
Monte Carlo methods
phased arrays
Sensor arrays
Sensors
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Summary:This paper introduces a new metric, to approximately lower-bound the error-variance in the estimation of an incident source's direction-of-arrival (DOA), for a sensor-array subject to random breakdown in its individual sensors. This new metric equals a weighted sum of Cramér-Rao bounds, each conditioned on a distinct event of sensors-breakdown. Those distinct events together describe the overall random phenomenon of the fallibility of the sensors that constitute the sensor-array. This new metric's tightness as an approximate lower bound is illustrated by Monte Carlo simulations of the maximum-likelihood estimator.
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ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2011.2165704