|Abstract:||In a typical vector tracking loop (VTL), information is shared among all the receiving channels, and errors of one channel can be spread to other normal channels. Therefore, it is necessary to identify the erroneous channel in time and eliminate the adverse effect from the loop to avoid degrading the performance of receiver. In urban environment, the loss of GNSS signals occurs frequently due to building obstacle. Checking the carrier to noise density ratio (C/N0) of signal is an effective method to judge whether the signal is lost or not. In this paper, the performance of several commonly used methods for calculating (C/N0) are compared and analyzed firstly, then, an improved method is proposed to smooth the noise and adjust the calculation time adaptively. Next, a specific method of removing the blocked channel in the VTL and meanwhile tracking the blocked signal is described in detail. At last, three experiments were carried out in this paper. The first two experiments use the data generated by the GNSS signal simulator to verify the performance of the proposed method in two aspects, namely, calculation accuracy and calculation time. Real satellites data are collected from the outdoor environment in the third experiment, and the ability of detecting and removing the blocked channel in the VTL is verified. The experimental results show that the proposed method can identify the blocked channel more quickly and accurately than the previous methods, and continuously maintain stable navigation solution without the interference of signal blockage.|
Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017)
September 25 - 29, 2017
Oregon Convention Center
|Pages:||3648 - 3660|
|Cite this article:||
Zou, Xiaojun, Lian, Baowang, Wu, Peng, Xu, Haowei, Zhang, Lin, "Detect and Remove the Blocked Channel in the Vector Tracking Loop based on Carrier to Noise Density Ratio," Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, pp. 3648-3660.
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