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Multi-frequency carrier-phase linear combinations are greatly beneficial to improving the performance of ambiguity resolution (AR), cycle slip correction as well as precise positioning. However, as a limiting factor for further improvements in Global Navigation Satellite System (GNSS) high-precision positioning, the effect of multipath is also accentuated due to the measurement combination. In this paper, with real GPS and BDS triple-frequency observations, we analyse the influence of the carrier-phase multipath in three typical triple-frequency combinations: extra-wide-lane (EWL) combination, ionosphere estimation with ambiguity-corrected EWL/wide-lane (WL) combinations and the geometry-free and ionosphere-free (GIF) combination for narrow-lane (NL) AR. For more intuitive reflection of the influence caused by the carrier-phase multipath, zero-baseline tests with no multipath influence were carried out for comparison. The results from consecutive orbital repeat periods were also used to confirm this influence. Experiments show that for the BDS (1, 4, -5) and GPS (1, -6, 5) EWL combinations, the multipath errors could be combined with the biases of several metres in units of distance and over 0.5 cycles in units of cycles. Therefore in single-epoch EWL AR, besides the empirical precision, the bias caused by carrier-phase multipath should be also fully considered. The coefficients of the ionosphere estimation and GIF model are so large that the multipath errors are accentuated many times. Experiments results indicate that even smoothed or averaged with several hours, the errors of ionosphere estimators could be still over 10 cm; the biases of NL ambiguities with GIF model could be still over 0.5 cycles, especially for BDS GEO satellites. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved.

It is known that weak texture region have become the major barriers to the development of stereo matching. The lack of appropriate feature will make it difficult to find another corresponding pixel also have no feature. The fractional differential-based approach for image filtering have the capability of nonlinearly enhancing complex texture details obvious better than by traditional integral-based algorithms. In this article, the cost aggregation consists of two pieces: the weighted guided image filtering for color-scale; the image after fractional differential filtering as the guidance image used to guided image filtering (GIF) for grayscale. The aggregated values of two scales will represent the edge and weak texture area, respectively. Finally, a disparity refinement measure based on fast weighted median filtering is applied in this paper too. Performance evaluation on Middlebury data sets shows that the proposed algorithm can obtain high-quality, especially in weak texture region. It's an attractive stereo matching solution in practice for both speed and accuracy.