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Sensor Management and Nonlinear Filtering Research.

Author: Avner Friedman; Minnesota univ minneapolis school of mathematics.
Publisher: [United States] : Minnesota univ minneapolis school of mathematics, 1998.
Series: AD-a360 450.
Edition/Format:   Book : National government publication : EnglishView all editions and formats
Database:WorldCat
Summary:
This grant is supporting development of mathematical foundations for sensor management and nonlinear filtering. The accomplishments so far are in two areas: (1) The use of Interactive Multiple Model Kalman Filters (IMMKF) with a metric called discrimination gain (DG); and (2) the use of nonlinear filtering, (NLF) in the tracking of target elevation for objects flying close to a reflecting surface. In the case of  Read more...
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Details

Material Type: Government publication, National government publication
Document Type: Book
All Authors / Contributors: Avner Friedman; Minnesota univ minneapolis school of mathematics.
OCLC Number: 45508347
Notes: Final rept. 1 Feb-31 Oct 98
MCIM progress rept. Prepared in collaboration with Lockheed Martin Tactical Defense Systems, St. Paul, MN.
Description: 13 p.
Series Title: AD-a360 450.

Abstract:

This grant is supporting development of mathematical foundations for sensor management and nonlinear filtering. The accomplishments so far are in two areas: (1) The use of Interactive Multiple Model Kalman Filters (IMMKF) with a metric called discrimination gain (DG); and (2) the use of nonlinear filtering, (NLF) in the tracking of target elevation for objects flying close to a reflecting surface. In the case of IMMKF, we demonstrate, using simulated data, that IMMKF can be used to compute the information gain when multiple sensors observe a collection of maneuvering airborne targets. In the case of NLF, we demonstrate the feasibility of using NLF methods for altitude tracking in multipath.

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