Substanitial enhancements to a multiple model adaptive estimator for target image tracking

1987 ◽  
Author(s):  
David Tobin ◽  
Peter Maybeck
Keyword(s):  
Multiple Model ◽  
Target Image ◽  
Adaptive Estimator ◽  
Image Tracking

scholarly journals A new generalized residual multiple model adaptive estimator of parameters and states

2006 ◽  
Vol 43 (9-10) ◽  
pp. 1092-1113 ◽  
Author(s):  
Charles D. Ormsby ◽  
John F. Raquet ◽  
Peter S. Maybeck
Keyword(s):  
Multiple Model ◽  
Adaptive Estimator

Using a multiple-model adaptive estimator in a random evasion missile/aircraft encounter

2001 ◽  
Vol 24 (6) ◽  
pp. 1176-1186 ◽  
Author(s):  
Y. Oshman ◽  
J. Shinar ◽  
S. A. Weizman
Keyword(s):  
Multiple Model ◽  
Adaptive Estimator

Multiple-model adaptive estimator for spacecraft attitude sensor calibration

2017 ◽  
Vol 89 (3) ◽  
pp. 457-467 ◽  
Author(s):  
Kai Xiong ◽  
Chunling Wei
Keyword(s):  
Kalman Filter ◽  
Convergence Rate ◽  
Attitude Determination ◽  
Spacecraft Attitude ◽  
Star Sensor ◽  
Multiple Model ◽  
Content Type ◽  
Adaptive Estimator ◽  
Calibration Algorithm ◽  
Novel Method

Purpose This paper aims to present a multiple-model adaptive estimator (MMAE) to calibrate the star sensor low frequency error (LFE). The star sensor LFE, which is caused primarily by the periodic thermal distortion, has a great impact on spacecraft attitude determination accuracy. Design/methodology/approach The unfavorable effect of the LFE can be partly eliminated by using the calibration algorithm based on the augmented Kalman filter (AKF). However, the AKF may be worse than the traditional Kalman filter (KF) in the absence of the LFE. To cope with this problem, the MMAE is applied first time for combining the AKF and the KF in the spacecraft attitude determination system, such that satisfactory performance can be achieved in different operating scenarios. Findings The convergence of the presented MMAE is demonstrated through a formal derivation. A novel method is proposed to tune the MMAE design parameter, such that the convergence rate of the estimator is increased. It is shown via numerical studies that the presented algorithm outperforms the AKF and the KF. Practical implications The calibration algorithm is applicable for spacecraft attitude determination. Originality/value An effective star sensor LFE calibration algorithm based on the MMAE is developed. In addition, a novel method is proposed to increase convergence rate of the estimator.

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