Low speed reconnaissance unmanned air vehicle uses low cost air data dead reckoning (ADDR) as the primary navigation system. In order to keep the ADDR position error (due to heading and air speed sensor calibration/installation error and computation error) to a minimum value, Global Position System (GPS) is used in supervisory mode to update the ADDR position at regular intervals. This thesis deals with a new approach based on Kalman filtering for navigation sensor data fusion obtained from ADDR navigation system and GPS. The modeling of ADDR and GPS dynamics has been developed, simulated for its error sources and position accuracies to determine the covariance matrix. A feed forward Kalman filter based navigation sensor data fusion algorithm has been developed to fuse the information from ADDR and GPS to obtain the best position estimate. This algorithm provides a relatively accurate low cost navigation system for UAV applications.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    ADDR-GPS data fusion using Kalman filter algorithm


    Contributors:

    Published in:

    Publication date :

    2005-01-01


    Size :

    278938 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    ADDR-GPS Data Fusion Using Kalman Filter Algorithm

    Rajaduraimanickam, K. / Shanmugam, J. / Anitha, G. et al. | British Library Conference Proceedings | 2005


    Data Fusion in UAV Sensors using Kalman Filter Algorithm and Fuzzy Algorithm

    Huang, Tianchen | Springer Verlag | 2024

    Free access

    A Federated Kalman Filter Design Using a Gain Fusion Algorithm

    Kim, J. W. / Jee, G. I. / Lee, J. G. et al. | British Library Conference Proceedings | 1999


    Implementation of Vision and Lidar Sensor Fusion Using Kalman Filter Algorithm

    Kunjumon, Reshma / Gopan G. S., Sangeetha | BASE | 2021

    Free access

    Unscented Schmidt-Kalman Filter Algorithm

    Jason Stauch | Online Contents | 2015