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An Unambiguous Acquisition Algorithm for BOC (n, n) Signal Based on Sub-correlation Combination

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Abstract

To overcome the acquisition problems caused by the multiple peaks of the auto-correlation function of Binary Offset Carrier (BOC) modulated signal, a technology is proposed in this paper to eliminate secondary peaks based on sub-combination correlation. According to the characteristics of the sub-function of the BOC autocorrelation function, this new method recombining the sub-correlation function obtains the ability to eliminate the edge. In the process of local design, it is aimed to design two local signal waves which can achieve the homologous sub-correlation function of BOC auto-correlation function by respectively correlating both local and received signals. MonteCarlo simulations show that the proposed method can improve 3 dBHz sensitivity in detection probability compared with ASPeCT when the non-coherent number is 10 for BOCs (1, 1). In addition, it can be applied to BOCc (1, 1) and achieve the same the detection probability compared with the traditional BSPK-LIKE method by appropriately increasing the number of non-coherent.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (61561016, 11603041), Guangxi Information Science Experiment Center funded project, Department of Science and Technology of Guangxi Zhuang Autonomous Region (AC16380014, AA17202048, AA17202033), the basic ability promotion project of young and middle-aged teachers in Universities of Guangxi province (ky2016YB164).

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  1. Guangxi Key Laboratory of Precision Navigation Technology and Application, Guilin University of Electronic Technology, Guilin, 541004, China

    Xiyan Sun, Qing Zhou, Yuanfa Ji, Qiang Fu, Qinwen Miao & Sunyong Wu

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  1. Xiyan Sun
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  2. Qing Zhou
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  3. Yuanfa Ji
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  4. Qiang Fu
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Correspondence to Qing Zhou.

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Sun, X., Zhou, Q., Ji, Y. et al. An Unambiguous Acquisition Algorithm for BOC (n, n) Signal Based on Sub-correlation Combination. Wireless Pers Commun 106, 1609–1628 (2019). https://doi.org/10.1007/s11277-019-06232-1

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