曾安敏, 杨元喜, 景一帆, 明锋. BDS/GPS融合定位中系统偏差补偿模型及其性能分析[J]. 武汉大学学报 ( 信息科学版), 2017, 42(10): 1423-1430. DOI: 10.13203/j.whugis20150808
引用本文: 曾安敏, 杨元喜, 景一帆, 明锋. BDS/GPS融合定位中系统偏差补偿模型及其性能分析[J]. 武汉大学学报 ( 信息科学版), 2017, 42(10): 1423-1430. DOI: 10.13203/j.whugis20150808
ZENG Anmin, YANG Yuanxi, JING Yifan, MING Feng. Systematic Bias Compensation Model of Inter-system Bias and Its Performance Analysis for BDS/GPS Fusion Positioning[J]. Geomatics and Information Science of Wuhan University, 2017, 42(10): 1423-1430. DOI: 10.13203/j.whugis20150808
Citation: ZENG Anmin, YANG Yuanxi, JING Yifan, MING Feng. Systematic Bias Compensation Model of Inter-system Bias and Its Performance Analysis for BDS/GPS Fusion Positioning[J]. Geomatics and Information Science of Wuhan University, 2017, 42(10): 1423-1430. DOI: 10.13203/j.whugis20150808

BDS/GPS融合定位中系统偏差补偿模型及其性能分析

Systematic Bias Compensation Model of Inter-system Bias and Its Performance Analysis for BDS/GPS Fusion Positioning

  • 摘要: 多系统的融合定位可有效提高用户导航定位的连续性、可靠性及定位精度。针对BDS、GPS观测量间存在系统间偏差的实际情况,建立了顾及系统误差的BDS/GPS融合定位模型,即在函数模型中增加附加参数来吸收系统间偏差,构造了新的顾及先验信息的融合定位模型,分析了这种新融合模型的特点及其对定位结果的影响。利用不同品牌接收机在中国不同地域对新的融合模型进行试验,试验结果表明:BDS、GPS观测量存在系统间偏差,且不同接收机的系统间偏差量值并不一样;增加系统参数的融合定位模型能较好地吸收BDS、GPS观测量的系统间偏差的影响,改善其融合导航定位性能;在观测卫星数不足、单系统不能定位的情况下,考虑先验信息的融合定位模型仍能获得较好的定位结果。

     

    Abstract: Navigation users will significantly benefit from BDS and GPS positioning fusion in terms of availability, accuracy and reliability. However, for single point positioning, systematic biases between multi-GNSS systems cannot be eliminated completely, thus the accuracy of positioning and navigation is not always improved with the un-difference measurements of multi-GNSS systems. In this paper, an integrated BDS/GPS positioning model with unknown systematic parameters that compensates for systematic bias is proposed. Furthermore, a Bayesian estimation of fusion positioning model is specifically investigated in which the priori information of the additional parameters is taken into account. Real data collected from different areas with different types of receivers are used to verify those new algorithms. The results show that (a) receiver-dependent inter-system biases are quite evident, while the size of the system bias varies with the receiver type; (b) the precision of fusion positioning is improved significantly by introducing additional parameters into the functional model; and (c) Bayesian estimation of fusion positioning model can still obtain ideal position solution when the number of visible satellites is not enough.

     

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