Accession Number:

ADA564903

Title:

Multi-Sensor Data Fusion: An Unscented Least Squares Approach

Descriptive Note:

Conference paper

Corporate Author:

ARMY RESEARCH LAB ADELPHI MD

Personal Author(s):

• George, Jemin
• Kaplan, Lance M.

Report Date:

2011-07-01

Pagination or Media Count:

9.0

Abstract:

This manuscript provides an approach to solving the nonlinear least squares problem that arises in decentralized fusion. In decentralized fusion, measurements are first processed at the sensor node before they are relayed to the central node. Even though almost all sensor noise can be modeled as additive noise, the additive nature of the measurement noise is lost when the signal is processed at the sensor node. The proposed unscented transformation-based approach helps to tackle the non-additive nature of the noise in the nonlinear least squares problem. Numerical simulations indicate that the proposed unscented transformation-based approach yields desired results.

Descriptors:

• *APPROXIMATION(MATHEMATICS)
• *DATA FUSION
• *LEAST SQUARES METHOD
• *MULTISENSORS
• *SENSOR FUSION
• *SIGNAL PROCESSING
• *TRANSFORMATIONS(MATHEMATICS)
• COMPUTERIZED SIMULATION
• ESTIMATES
• GAUSSIAN NOISE
• MEASUREMENT
• NODES
• SYMPOSIA
• TAYLORS SERIES

Subject Categories:

• Numerical Mathematics
• Statistics and Probability
• Cybernetics
• Miscellaneous Detection and Detectors

Distribution Statement:

APPROVED FOR PUBLIC RELEASE