Abstract
Standard extended Kalman filtering algorithm usually needs a little precise initial value, but Strap down inertial navigation system(SINS) coarse alignment precision for marching vehicle can't meet the requirement. So UKF (unscented kalman filter) was proposed to achieve SINS initial alignment for marching vehicle with odometer aiding. The state equation for large misalignment error model was expounded, and observation equation was derived when the measurement variable was chosen as difference of velocity offered by SINS and velocity reckoned by odometer. UKF filtering algorithm based on additive noise model was derived. Simulation based on vehicular tests data showed that UKF filtering algorithm could achieve SINS initial alignment for marching vehicle, and UKF filtering algorithm could achieve better robustness from filtering initial value, higher alignment precision and faster convergence velocity than Standard extended Kalman filtering algorithm.
Published Version
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