The Chinese BeiDou system (BDS), having different types of satellites, is an important addition to the ever growing system of Global Navigation Satellite Systems (GNSS). It consists of Geostationary Earth Orbit (GEO) satellites, Inclined Geosynchronous Satellite Orbit (IGSO) satellites and Medium Earth Orbit (MEO) satellites. This paper investigates the receiver-dependent bias between these satellite types, for which we coined the name “inter-satellite-type bias” (ISTB), and its impact on mixed receiver attitude determination. Assuming different receiver types may have different delays/biases for different satellite types, we model the differential ISTBs among three BeiDou satellite types and investigate their existence and their impact on mixed receiver attitude determination. Our analyses using the real data sets from Curtin's GNSS array consisting of different types of BeiDou enabled receivers and series of zero-baseline experiments with BeiDou-enabled receivers reveal the existence of non-zero ISTBs between different BeiDou satellite types. We then analyse the impact of these biases on BeiDou-only attitude determination using the constrained (C-)LAMBDA method, which exploits the knowledge of baseline length. Results demonstrate that these biases could seriously affect the integer ambiguity resolution for attitude determination using mixed receiver types and that a priori correction of these biases will dramatically improve the success rate.
This paper presents the performance analysis of signals from the Galileo satellites in the E1 and E5a frequency bands and GPS L5 signals as measured by DLR's experimental ground-based augmentation system. The results show that the raw noise and multipath level of Galileo signals and of the GPS L5 signals are smaller than that of GPS L1. The new signals are also less sensitive to the choice of carrier-smoothing time constant. Furthermore, the inter-frequency biases that affect dual-frequency processing are investigated. These biases differ between satellites and depend on satellite and receiver hardware, but they can be determined a priori. With known receiver and antenna configurations, it is possible to correct for these biases. A residual uncertainty associated with the bias correction has to be taken into account. This can be modeled as part of the ground and airborne bounding standard deviations (σ pr_gnd and σ pr_air) used in GBAS processing.
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