Estimation With Multisensor/Multiscan Detection Fusion
Fadil Santosa · 1993
This first topic deals with a new procedure to carry out nonlinear transformations commonly encountered in practical surveillance systems, that eliminates the bias and provides a correct (rather than optimistic) covariance matrix. The topics covered in sections 2, 5 and 6 deal with discrete optimization (assignment) techniques applied to various multisensor-multitarget problems, including ballistic missile track initiation from a passive orbiting sensor. Section 3 presents some new efficient factorization algorithms that improve the numerical accuracy for several advanced state estimation filters used in practice. Section 4 deals with evaluation of performability measure of complex manufacturing systems.