
Research Article
Multipath and Distorted Detection Based on Multi-correlator (Workshop)
@INPROCEEDINGS{10.1007/978-3-030-41117-6_27, author={Rongtao Qin}, title={Multipath and Distorted Detection Based on Multi-correlator (Workshop)}, proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part II}, proceedings_a={CHINACOM PART 2}, year={2020}, month={2}, keywords={Multi-correlator Multipath signal Distorted signal}, doi={10.1007/978-3-030-41117-6_27} }
- Rongtao Qin
Year: 2020
Multipath and Distorted Detection Based on Multi-correlator (Workshop)
CHINACOM PART 2
Springer
DOI: 10.1007/978-3-030-41117-6_27
Abstract
With the advent of new Global Navigation Satellite Systems (GNSS) and signals, the signal quality monitoring techniques for navigation signals also need to be updated. In the traditional satellite signal integrity detection, the multi-correlator processing method is commonly used in signal quality monitoring to detect if a signal is distorted. This method often assumes that multipath signals have been eliminated, avoiding multipath signals from interfering with the detection results. However, if there is a multipath signal that has not been eliminated, since the correlation functions of the multipath signal and the distorted signal have a certain similarity, if the detection method without considering the multipath effect is used, here is a case where the multipath signal is erroneously detected as a distorted signal. Since the influence of the multipath signal and the distorted signal on the positioning result is very different, it is necessary to distinguish the two signals during the detection process. In this paper, the model of multipath signal and distorted signal is discussed for the new generation GNSS signal (BOC signal). Based on the characteristics of the correlation functions of these two models, a multi-correlator range setting method is proposed, and the appropriate detection values are selected, which can effectively distinguish multipath signals and distorted signals at the relevant peak levels.