@inproceedings{acbe14a141b84c76b6776f4f953e93d7,
title = "Performance of sample covariance based capon bearing only tracker",
abstract = "Bearing estimates input to a tracking algorithm require a concomitant measurement error to convey confidence. When Capon algorithm based bearing estimates are derived from low signal-to-noise ratio (SNR) data, the method of interval errors (MIE) provides a representation of measurement error improved over high SNR metrics like the Cram{\'e}r-Rao bound or Taylor series. A corresponding improvement in overall tracker performance is had. These results have been demonstrated [4] assuming MIE has perfect knowledge of the true data covariance. Herein this assumption is weakened to explore the potential performance of a practical implementation that must address the challenges of non-stationarity and finite sample effects. Comparisons with known non-linear smoothing techniques designed to reject outlier measurements is also explored.",
author = "Richmond, {Christ D.} and Geddes, {Robert L.} and Ramis Movassagh and Alan Edelman",
year = "2011",
month = dec,
day = "1",
doi = "10.1109/ACSSC.2011.6190384",
language = "English (US)",
isbn = "9781467303231",
series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",
pages = "2036--2039",
booktitle = "Conference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011",
note = "45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011 ; Conference date: 06-11-2011 Through 09-11-2011",
}