In this paper we consider detection in colored linear non-Gaussian noise of unknown covariance. Higher order cumulants of non-Gaussian processes are estimated in the presence of unknown deterministic and/or Gaussian signals. This allows either parametric or non-parametric estimation of the covariance of the non-Gaussian process via its cumulants. Our approach to detection is to augment methods based on second-order statistics using cumulants. We propose a solution for detection of deterministic signals based on matched filters which incorporate cumulants, where the resulting solutions are valid under either detection hypothesis. This allows for single record detection and obviates the need for prewhitening using noiseonly training records. We also consider detection of random Gaussian signals in non-Gaussian noise.
|Title of host publication
|IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1993
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 1993
|1993 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1993 - Minneapolis, United States
Duration: Apr 27 1993 → Apr 30 1993
|ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
|1993 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1993
|4/27/93 → 4/30/93
Bibliographical notePublisher Copyright:
© 1993 IEEE