Accession Number:

ADA243507

Title:

Data Fusion for Least Squares

Descriptive Note:

Final rept. Jan 90-Aug 91,

Corporate Author:

ARMY BALLISTIC RESEARCH LAB ABERDEEN PROVING GROUND MD

Personal Author(s):

Report Date:

1991-12-01

Pagination or Media Count:

41.0

Abstract:

The wide array of uses for least-squares estimation testifies to its effectiveness. The key to structuring a problem for at least-squares solution is finding a Markov representation of the problem. This representation defines a recursive approach to estimation. When multiple estimates are available at each time step, the processing time can be decreased by using data fusion networks to reduce the information to a single estimate. Hierarchical networks, using both parallel and serial combination of data, can be devised. The cases presented herein can be used to preprocess the for any recursive least-squares method.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE