A TUTORIAL DERIVATION OF RECRUSIVE WEIGHTED LEAST SQUARES STATE-VECTOR ESTIMATION THEORY (KALMAN THEORY)

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Abstract:

This is one of a series of tutorial reports deriving the discrete recursive Kalman estimation equations. The series proceeds from unweighted to weighted least squares parameter estimation in a vector space setting to the stage-wise updating, to time varying parameter or state variable estimation. The derivatives have been stage-wise tutorial in an attempt to make the theory accessible to the non-specialist in optimization theory.

Author(s):
Pappas, James S.
Author Organization(s):
ARMY TEST AND EVALUATION COMMAND WHITE SANDS MISSILE RANGE NM DEPUTY FOR NATIONAL RANGE OPERATIONS
Descriptive Note:
Special rept.
Pagination:
0059

Security Markings

DOCUMENT & CONTEXTUAL SUMMARY

Distribution:
Approved For Public Release

RECORD

Collection: TR
Identifying Numbers
Report Number(s):
RO-S-68-2
Monitor Series:
DA
 Subject Terms
Joint Capability Areas:
JCA_5_Command and Control; JCA_8.2.4_Leverage Capacities and Capabilities of Security Establishments; JCA_8.2_Shape; JCA_8_Building Partnerships; JCA_5.3_Planning; JCA_3.2_Engagement; JCA_3_Force Application; JCA_3.2.1_Kinetic Means; JCA_1.2.7_Experimentation; JCA_1.2_Force Preparation; JCA_1_Force Support; JCA_6.4.1_Secure Information Exchange; JCA_6_Net Centric
Communities of Interest:
Weapons Technologies
Descriptor(s):
*INFORMATION THEORY, OPTIMIZATION, MATRICES(MATHEMATICS), COMPUTER PROGRAMMING, MATHEMATICAL LOGIC, LEAST SQUARES METHOD, VECTOR SPACES, CORRELATION TECHNIQUES
Field(s)/Group(s):
Operations Research, Cybernetics
Keyword(s):
ESTIMATION THEORY, KALMAN FILTERS
Report Date:
1968 Aug 01