Accession Number:

ADA564774

Title:

Joint PDF Construction for Sensor Fusion and Distributed Detection

Descriptive Note:

Conference paper

Corporate Author:

RHODE ISLAND UNIV KINGSTON DEPT OF ELECTRICAL AND COMPUTER ENGINEERING

Personal Author(s):

• Kay, Steven
• Ding, Quan
• Emge, Darren

Report Date:

2010-07-01

Pagination or Media Count:

7.0

Abstract:

A novel method of constructing a joint probability density function PDF under Hsub 1, when the joint PDF under Hsub 0 is known, is developed. It has direct application in distributed detection systems. The construction is based on the exponential family, and it is shown that asymptotically the constructed PDF is optimal. The generalized likelihood ratio test GLRT is derived based on this method for the partially observed linear model. Interestingly, the test statistic is equivalent to the clairvoyant GLRT, which uses the true PDF under Hsub 1, even if the noise is nonGaussian.

Descriptors:

• *DATA FUSION
• *DETECTION
• *MEASUREMENT
• *MULTISENSORS
• *OPTIMIZATION
• *PROBABILITY DENSITY FUNCTIONS
• *SENSOR FUSION
• ALGORITHMS
• ASYMPTOTIC NORMALITY
• COMPUTERIZED SIMULATION
• GAUSSIAN NOISE
• MAXIMUM LIKELIHOOD ESTIMATION
• PARAMETERS
• SYMPOSIA

Subject Categories:

• Statistics and Probability
• Cybernetics
• Miscellaneous Detection and Detectors

Distribution Statement:

APPROVED FOR PUBLIC RELEASE