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Study on GPS common-view observation data with multiscale Kalman filter algorithm

Recently, a filter bank design based on orthonormal wavelets and equipped with a multiscale Kalman filter was proposed for signal restoration of fractal signals corrupted by external noise. We use the ideal of the multiscale Kalman filter to process GPS common-view observation data. The methods are applied to GPS common-view observation data between the Communication Research Laboratory (CRL) and Shaanxi Astronomical Observatory (NTSC), China, which are located about 2000 km apart. Comparisons between Kalman filter and multiscale Kalman filter are given. The latter gives a more accurate estimation. Typical computer simulation results demonstrate its feasibility and effectiveness.