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Session A1: Algorithms for GNSS Processing and Sensor Integration

An Analysis on Joint Acquistision Performance of MBOC Signals
Xiamei Huang, Xue Wang, Xiaochun Lu, Yongnan Rao, Xiaofei Chen, Li Kang, Yao Guo, National Time Service Centre, Chinese Academy of Sciences, China
Location: Grand Ballroom G

With the development of GNSS (Global navigation Satellite System), there are more and more signals at the same center frequency. Some new modulation techniques are focused on spectrum separation. Multiplexed Binary Offset Carrier (MBOC) is an optimization method of spread spectrum modulation consisted of BOC (1,1) and BOC (6,1) and applied to BDS B1C, Galileo E1 B/C and GPS L1C. There are three MBOC signals: the Quadrature Multiplexed Binary Offset Carrier (QMBOC) adopted by BDS, the Composite Binary Offset Carrier (CBOC) proposed by Galileo, and the Time-multiplexed Binary Offset Carrier (TMBOC) for GPS.
As a newly designed signal, MBOC signal has many innovative features. One of the most outstanding feature is consisted of a pilot component and a data component. Only pilot component is used for conventional acquisition method, and one obvious disadvantage of this approach is the waste of signal power. Joint acquisition can make full use of both pilot and data components, which effectively eliminate signal power and improve acquisition sensitivity.
This paper focuses on analyzing the performance of conventional acquisition and joint acquisition with different MBOC signals. Firstly, this paper uses conventional acquisition and joint acquisition to process QMBOC, CBOC, and TMBOC signal respectively; Secondly, the acquisition sensitivity between joint acquisition and conventional acquisition is compared , and the calculation cost and detection probabilities are also analyzed. In general, the analysis of MBOC is based on simulator. With real signal, this papers carries out joint acquisition performance among different MBOC signals. The results prove that joint acquisition can effectively improve acquisition sensitivity and detection probabilities.




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