Window based Multiple Model Adaptive Estimation for Navigational Framework

Kottath, Rahul and Poddar, Shashi and Das, Amitava and Kumar, Vipan (2016) Window based Multiple Model Adaptive Estimation for Navigational Framework. Aerospace Science and Technology, 50. pp. 88-95. ISSN 1270-9638

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Kalman filter based algorithms aim at providing accurate estimate of the state parameters which is indirectly governed by the accuracy of the sensor measurement and noise parameters fed to the system model. Multiple Model Adaptive Estimation (MMAE) is one of the adaptive techniques which tries to reduce the dependency of Kalman filter on the noise parameters fed to the system. The main goal of this work is to improve state estimation by incorporating window size as one of the unknown parameters in MMAE framework, referred to as Window based MMAE (WMMAE). The proposed scheme intertwines the concepts of Innovation Adaptive Estimation (IAE) and MMAE in one structure and the state estimation for each model is implemented by IAE. Simulation results prove the efficacy of WMMAE scheme as compared to MMAE and its other variants.

Item Type: Article
Uncontrolled Keywords: Adaptive Kalman filter; Optimal state estimation; AHRS; Innovation Adaptive Estimation; Multiple Model Adaptive Estimation
Subjects: CSIO > Optics
Depositing User: Ms. Jyotsana
Date Deposited: 09 Aug 2018 11:55
Last Modified: 09 Aug 2018 11:55

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