A method of dynamic positioning with the medium and long baseline for aerial measurement scenarios

doi:10.11947/j.AGCS.2019.20180513

Abstract

Abstract: Medium and long baseline kinematic relative positioning with a single base station will be affected by atmospheric residual errors and the ambiguities could not be fixed fast. Therefore, the performance of long-baseline relative positioning with low ambiguity-fixed rate is not as good as short-baseline situations. While considering baselines varying from short to long in airborne scenes, we propose a new method to improve the performance of kinematic relative positioning. First, high precision ionospheric delays can be easily obtained from the ambiguity-fixed resolutions in short-baseline scenes when the air just taking off. Second, the subsequent ionospheric delays are predicated epoch by epoch based on previous ionospheric delays. At last, filter with ionosphere predication constrained is implemented to fix the ambiguities quickly and obtain continuous high-precision positioning results. In this paper, the characteristics of double-differenced ionospheric residual errors for the dynamic measurement scenarios with long-baseline are analyzed. A sliding window will be applied for modeling and prediction of ionospheric delays. Next, we have discussed the implementation conditions, performance of positioning and the ambiguity resolution with this proposed method. The presented algorithm is evaluated by a set of airborne data and the results show that the new scheme can obtain the 100% fixing rate nearly and centimeter-level positioning accuracy in long baseline relative positioning with single base station as long as a few minutes short-baseline data. With this method, the costs of airborne measurement tasks will be significantly reduced.

Key words: kinematic relative positioning, medium and long baseline, ionosphere constraint

CLC Number:

P228

ZHANG Yuxi, ZHANG Xiaohong, LIU Quanhai, ZHU Feng. A method of dynamic positioning with the medium and long baseline for aerial measurement scenarios[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(7): 871-878.

References

[1] 张小红, 刘经南, FORSBERG R, 等. 基于精密单点定位技术的航空测量应用实践[J]. 武汉大学学报(信息科学版), 2006, 31(1):19-22, 46. ZHANG Xiaohong, LIU Jingnan, FORSBERG R, et al. Application of precise point positioning in airborne survey[J]. Geomatics and Information Science of Wuhan University, 2006, 31(1):19-22, 46.
[2] 孙中苗, 翟振和, 肖云. 渤海湾航空重力及其在海域大地水准面精化中的应用[J]. 测绘学报, 2014, 43(11):1101-1108. DOI:10.13485/j.cnki.11-2089.2014.0174. SUN Zhongmiao, ZHAI Zhenhe, XIAO Yun. Airborne gravimetry in bo hai Bay and its role on the refining of the regional marine geoid[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(11):1101-1108. DOI:10.13485/j.cnki.11-2089.2014.0174.
[3] 宁津生, 黄谟涛, 欧阳永忠, 等. 海空重力测量技术进展[J]. 海洋测绘, 2014, 34(3):67-72, 76. NING Jinsheng, HUANG Motao, OUYANG Yongzhong, et al. Development of marine and airborne gravity measurement technologies[J]. Hydrographic Surveying and Charting, 2014, 34(3):67-72, 76.
[4] LEICK A. GPS satellite surveying[M]. 3rd ed. Hoboken, NJ:John Wiley, 2004:181-182.
[5] ODIJK D. Weighting ionospheric corrections to improve fast GPS positioning over medium distances[C]//Proceedings of International Technical Meeting of Satellite Division of US Institute Navigation. Salt Lake City, USA:ION, 2000:1113-1123.
[6] WIELGOSZ P, KASHANI I, GREJNER-BRZEZINSKA D. Analysis of long-range network RTK during a severe ionospheric storm[J]. Journal of Geodesy, 2005, 79(9):524-531.
[7] WVBBENA G, BAGGE A, SEEBER G, et al. Reducing distance dependent errors for real-time precise DGPS applications by establishing reference station networks[C]//Proceedings of the 9th International Technical Meeting of the Satellite Division of the US Institute of Navigation. Kansas City, USA:ION, 1996:1845-1852.
[8] 高星伟, 陈锐志, 赵春梅. 网络RTK算法研究与实验[J]. 武汉大学学报(信息科学版), 2009, 34(11):1350-1353. GAO Xingwei, CHEN Ruizhi, ZHAO Chunmei. A network RTK algorithm and its test[J]. Geomatics and Information Science of Wuhan University, 2009, 34(11):1350-1353.
[9] LI Bofeng, SHEN Yunzhong, FENG Yanming, et al. GNSS ambiguity resolution with controllable failure rate for long baseline network RTK[J]. Journal of Geodesy, 2014, 88(2):99-112.
[10] RIZOS C. Network RTK research and implementation:a geodetic perspective[J]. Journal of Global Positioning Systems, 2002, 1(2):144-150.
[11] WANNINGER L. Virtual reference stations for centimeter-level kinematic positioning[C]//Proceedings of the International Technical Meeting of the Satellite Division of the Institute of Navigation. Portland, Oregon:ION, 2002.
[12] BLEWITT G. Carrier phase ambiguity resolution for the global positioning system applied to geodetic baselines up to 2000 km[J]. Journal of Geophysical Research:Solid Earth, 1989, 94(B8):10187-10203.
[13] DONG Danan, BOCK Y. Global positioning system network analysis with phase ambiguity resolution applied to crustal deformation studies in California[J]. Journal of Geophysical Research:Solid Earth, 1989, 94(B4):3949-3966.
[14] TEUNISSEN P J G. The geometry-free GPS ambiguity search space with a weighted ionosphere[J]. Journal of Geodesy, 1997, 71(6):370-383.
[15] DAI Liwen, WANG Jinling, RIZOS C, et al. Predicting atmospheric biases for real-time ambiguity resolution in GPS/GLONASS reference station networks[J]. Journal of Geodesy, 2003, 76(11-12):617-628.
[16] CHEN H Y, RIZOS C, HAN S. An instantaneous ambiguity resolution procedure suitable for medium-scale GPS reference station networks[J]. Survey Review, 2004, 37(291):396-410.
[17] KASHANI I, GREJNER-BRZEZINSKA D, WIELGOSZ P. Towards instantaneous network-based RTK GPS over 100 km distance[C]//Proceedings of the 60th Annual Meeting of the Institute of Navigation. Dayton, OH:ION, 2004:679-686.
[18] HU G, ABBEY D A, CASTLEDEN N, et al. An approach for instantaneous ambiguity resolution for medium-to long-range multiple reference station networks[J]. GPS Solutions, 2005, 9(1):1-11.
[19] WIELGOSZ P, KRANKOWSKI A, SIERADZKI R, et al. Application of predictive regional ionosphere model to medium range RTK positioning[J]. Acta Geophysica, 2008, 56(4):1147-1161.
[20] TU Rui, LU Cuixian, ZHANG Pengfei, et al. The study of BDS RTK algorithm based on zero-combined observations and ionosphere constraints[J]. Advances in Space Research, 2019, 63(9):2687-2695.
[21] TAKASU T, YASUDA A. Kalman-filter-based integer ambiguity resolution strategy for long-baseline RTK with ionosphere and troposphere estimation[C]//Proceedings of the 23rd International Technical Meeting of the Satellite Division of the Institute of Navigation. Portland, OR, USA:ION, 2010:161-171.
[22] TEUNISSEN P J G. An optimality property of the integer least-squares estimator[J]. Journal of Geodesy, 1999, 73(11):587-593.
[23] LI Bofeng, VERHAGEN S, TEUNISSEN P J G. Robustness of GNSS integer ambiguity resolution in the presence of atmospheric biases[J]. GPS Solutions, 2014, 18(2):283-296.
[24] KLOBUCHAR J A. Ionospheric effects on GPS[M]//SPILKER J J JR, AXELRAD P, PARKINSON B W, et al. Global Positioning System:Theory and Applications. Washington, DC:The American Institute of Aeronautics and Astronautics, 1996:485-515.
[25] YANG Yuanxi, LI Jinlong, WANG Aibing, et al. Preliminary assessment of the navigation and positioning performance of BeiDou regional navigation satellite system[J]. Science China Earth Sciences, 2014, 57(1):144-152.