Estimation of Attitudes from a Low Cost Miniaturized Inertial Platform using Kalman Filter based Sensor Fusion Algorithm

Shantha Kumar, N and Jann, T (2004) Estimation of Attitudes from a Low Cost Miniaturized Inertial Platform using Kalman Filter based Sensor Fusion Algorithm. Sadhana, 29 (2). pp. 217-235. ISSN 0256-2499

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Abstract

Due to costs, size and mass, commercially available nertial navigation system are not suitable for small, autonomous flying vehicles like ALEX and other UAVs. In contrast using modern MEMS (or of similar class) sensors, the hardware costs, size and mass can be reduced substantially. However, sensors of low cost category suffer from inaccuracy and are influenced greatly by the temperature variation. In this work such inaccuracies and dependency on temperature variations have been studied, modeled and compensated in order to reach an adequate quality of the measurements for the estimation of attitudes. This has been done applying a Kalman filter based sensor fusion algorithm that combines sensor models, error parameters and estimation scheme. The attitude estimation from low cost sensors is first realized in MATLAB/SIMULINK platform and then implemented on hardware by programming the micro controller and validated. The accuracy of the estimated roll and pitch attitudes are well within the stipulated accuracy level of 50 for the ALEX. However the estimation of heading which is mainly derived from the magnetometer readings seems to be influenced greatly by the variation in local magnetic field

Item Type: Article
Subjects: AERONAUTICS > Avionics & Aircraft Instrumentation
Depositing User: Mr. Shantha Kumar N
Date Deposited: 30 Jun 2010 06:04
Last Modified: 30 Jun 2010 06:04
URI: http://nal-ir.nal.res.in/id/eprint/8479

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