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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      07 April 2023, Volume 38 Issue 2   
    Article

    A NEW ADAPTIVE FILTERING TECHNIQUE FOR GNSS MULTIPATH DATA PROCESSING AND MITIGATION
    Pedda Naraiah.R, P.Naveen Kumar
    Journal of Data Acquisition and Processing, 2023, 38 (2): 1431-1441 . 

    Abstract

    Global satellite based navigation systems such as GPS (US), GLONASS (Russia), Galileo (Europe) and Compass (China) are widely used for precise positioning for several applications. The attainable positional accuracy of these systems is affected by satellite based (satellite clock errors, ephemeris errors, satellite instrumental bias), SIS (Signal in Space) and receiver based errors, clock bias, instrumental bias, multipath and receiver noise. Among the receiver based errors multipath is considered as the major debilitating factor that can lead to the degradation of signal strength or complete blockage of the signal in extreme case. Precise estimation and mitigation of multipath error is therefore required to improve positional accuracy of Global Navigation Satellite System (GNSS) systems. The multipath can be estimated precisely using Code minus Carrier (CMC) technique using linear combination of code phase and carrier phase measurements of GNSS signals. There are various multipath mitigation techniques proposed in open literature at signal processing level using hardware (MEDLL, MUSIC etc.) as well as software (Filtering techniques such as RLS, LMS, etc.,) approaches. Filtering techniques for multipath mitigation are superior to hardware approaches in terms of flexibility, adaptability and ability to process signals both in real-time as well as at post processing stages. In this paper, a novel filtering technique ‘Block LMS’ is proposed for multipath mitigation and its performance is compared with conventional techniques such as LMS and RLS. . The mean multipath error after RLS filtering on L1 and L2 are 1.38 m and 2.09 m, the multipath error reduced by 75.82% for L1 and 73.07% for L2. The mean multipath error on L1 after filtering using HRLS, LMS and NLMS are 1.32 m, 1.67m and1.71m respectively. It is observed that the respective filters multipath error mitigation in terms of percentages are 72.52%, 91.75% and 93.95% respectively. For L2 the mean multipath error using HRLS, LMS and NLMS is 1.98 m, 2.58 m and 2.61 m respectively. BLMS filter performs with significant improvement in multipath mitigation with 95.05% on L1 and 92.30% on L2. It is observed that BLMS filter has reduces multipath error more effectively.

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