Chernoff bounds for Class-A noise
The goal is, using a very large passive array, to determine the performance limits of a detector. The signal of interest is narrowband with a Gaussian envelope, and the contaminating noise is multivariate Class-A. Two different multivariate models for the Class A family are presented. One of the models is appropriate for array processing applications. The data is spatially dependent and temporally independent. It is shown, in the spatially independent case, that the Chernoff approximation does closely approximate the performance of the optimal detector. It is shown the approximation improves as the number of samples increases. Unfortunately, it is also shown that the Chernoff approximation requires numerical evaluation of a M-dimensional integral. For the application here, M may be as large as 150, ruling out this approach. Two alternative approaches are examined. First, approximating the Class A model by a Gaussian model is shown to result in a poor approximation. Second, the exact likelihood ratio is approximated by a piece-wise function. While the approximation can be done with very good accuracy, the bound must be evaluated numerically. 10 refs., 11 figs.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE; USDOE, Washington, DC (United States)
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 6143346
- Report Number(s):
- UCRL-ID-108260; ON: DE92002939
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
58 GEOSCIENCES
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
SONAR
PERFORMANCE TESTING
ACOUSTIC MEASUREMENTS
DETECTION
OCEANOGRAPHY
SIGNAL-TO-NOISE RATIO
SIGNALS
STATISTICAL MODELS
UNDERWATER
LEVELS
MATHEMATICAL MODELS
MEASURING INSTRUMENTS
RANGE FINDERS
TESTING
440800* - Miscellaneous Instrumentation- (1990-)
580000 - Geosciences
990200 - Mathematics & Computers