Abstract
A new array processing method is presented for bearing estimation based on the cross bispectrum of the array output data. The method is based on the asymptotic distribution of cross-bispectrum estimates and uses maximum likelihood theory. It is demonstrated that, when the noise additive sources are spatially correlated Gaussian with unknown cross-spectral matrix (CSM), the cross-bispectrum method provides better bearing estimates than the stochastic maximum likelihood method with known CSM. Analytical studies and simulations are given to document the performance of the new method.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Keywords
BispectrumBearing (navigation)Estimation theoryMathematicsGaussianMaximum likelihoodComputer scienceAlgorithmStatisticsApplied mathematicsPattern recognition (psychology)Speech recognitionArtificial intelligenceSpectral densityPhysics
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Publication Info
- Year
- 1991
- Type
- article
- Volume
- 39
- Issue
- 9
- Pages
- 1994-2006
- Citations
- 44
- Access
- Closed
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Cite This
Philippe Forster,
C.L. Nikias
(1991).
Bearing estimation in the bispectrum domain.
IEEE Transactions on Signal Processing
, 39
(9)
, 1994-2006.
https://doi.org/10.1109/78.134432
Identifiers
- DOI
- 10.1109/78.134432