Title : ( Optimal Partitioned State Kalman Estimator for Maneuvering Target Tracking in Mixed Coordinates )
Authors: - - , Hamid Khaloozadeh , Naser Pariz , Ali Peiravi ,
Full TextAbstract
A new two stage algorithm is originally proposed to reduce the computational effort for maneuvering target tracking in mixed coordinates. The augmented state Kalman estimators, which are based on the jerk modelling, are computationally expensive. The conventional input estimation techniques assume constant acceleration level and there are not covered a generalized input modeling. In this research, an innovative scheme is developped to overcome these drawbacks by using a reduced state Kalman estimator with a new structure, which is optimal for general conditions. In addition, the proposed scheme is an unbiased filtering algorithm applied in mixed coordinates based on the pseudo linear measurements.
Keywords
, Psudo linear measurements, optimal reduced state Kalman estimator, input estimation, augmented state Kalman estimators, maneuvering target tracking
@article{paperid:1006471,
author = { -, - and Khaloozadeh, Hamid and Pariz, Naser and Peiravi, Ali},
title = {Optimal Partitioned State Kalman Estimator for Maneuvering Target Tracking in Mixed Coordinates},
journal = {Journal of Applied Sciences},
year = {2008},
volume = {8},
number = {20},
month = {October},
issn = {1812-5654},
pages = {3638--3645},
numpages = {7},
keywords = {Psudo linear measurements; optimal reduced state Kalman estimator; input estimation; augmented state Kalman estimators; maneuvering target tracking},
}
%0 Journal Article
%T Optimal Partitioned State Kalman Estimator for Maneuvering Target Tracking in Mixed Coordinates
%A -, -
%A Khaloozadeh, Hamid
%A Pariz, Naser
%A Peiravi, Ali
%J Journal of Applied Sciences
%@ 1812-5654
%D 2008
