Title :
Convergence analysis for the extended-Kalman-filter based algorithm of target tracking and identification
Author :
Cheng, Dan S. ; Stubberud, Allen R.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA
Abstract :
The joint problem of target tracking and identification was discussed previously by the authors (1991), and a tracking/identification algorithm using an extended-Kalman-filter-based associative memory (EK-FAM) was demonstrated through several examples. The convergence properties of the algorithm are discussed. Under the appropriate conditions, a contraction operator can be developed, using Banach space concepts that guarantee convergence of the algorithm
Keywords :
Kalman filters; convergence of numerical methods; filtering and prediction theory; identification; tracking; Banach space; contraction operator; convergence properties; extended-Kalman-filter-based associative memory; target identification; target tracking; tracking/identification algorithm; Algorithm design and analysis; Associative memory; Convergence; Eigenvalues and eigenfunctions; Functional analysis; Jacobian matrices; Signal processing algorithms; Target tracking; Vectors; Virtual manufacturing;
Conference_Titel :
Signals, Systems and Computers, 1992. 1992 Conference Record of The Twenty-Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-3160-0
DOI :
10.1109/ACSSC.1992.269136
