Abstract
Global Positioning System (GPS) is the modern Global Navigation Satellite System (GNSS) all over the world. The GPS system accuracy can be corrupted by several error sources like ionosphere, troposphere, satellite clock errors, ephemeris errors, multipath and instrumental bias. GPS signals undergo reflections by objects along the path and may arrive at the receiver antenna via different paths. This leads to wrong position estimate as the signals travel feet to miles more to reach the receiver antenna than a direct line of sight signal. This problem is called as multipath. The GPS receiver tracks both the direct and reflected signal components. Multipath provokes error in both pseudorange and carrier phase measurements. In our work, the estimated multipath error using code range minus carrier phase range (CRMCPR) technique is applied as the input to the standard and Markov Chain Monte Carlo (MCMC) particle filters. For the analysis, data corresponding to the receiver placed at Department of ECE, Andhra University, is considered.
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Swathi, N., Srilatha Indira Dutt, V.B.S., Sasibhushana Rao, G. (2020). MCMC Particle Filter Approach for Efficient Multipath Error Mitigation in Static GNSS Positioning Applications. In: Saini, H.S., Singh, R.K., Tariq Beg, M., Sahambi, J.S. (eds) Innovations in Electronics and Communication Engineering. Lecture Notes in Networks and Systems, vol 107. Springer, Singapore. https://doi.org/10.1007/978-981-15-3172-9_12
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DOI: https://doi.org/10.1007/978-981-15-3172-9_12
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