为了提高接收机导航定位的实时性,需要从大量的可见卫星中选取几何布局较好的星座组合进行定位解算.提出多星座选星可以作为有约束条件的离散型多目标优化问题求解,并基于NSGA-II遗传算法提出了一种多星座选星方法.该方法能综合优化几何精度因子(GDOP)和选星数目,可以在减少接收机运算量的同时获得良好的定位精度.仿真结果表明,利用该方法在静态和动态情况下均有良好的有效性和实时性.
With the development of multi-global navigation satellite system (GNSS) constellations, more and more satellites will be available. To ensure the accuracy of positioning, we have to select optimal satellites to improve the real-time performance of the receiver. In this paper, we firstly consider that satellite selection of multi-GNSS constellation can be used as a discrete multi-objective optimization problem with constraint conditions, and a new method based on non-dominated sorting genetic algorithm (NSGA)-II is proposed. This method can comprehensively optimize the geometric dilution of precision (GDOP) and the number of selected satellites at the same time. We can obtain good positioning accuracy while reducing the amount of computation of the receiver. The simulation results show that the proposed method is effective in both static and dynamic conditions with good real-time capabilities.
[1]LI X, ZHANG X, REN X, et al. Precise positioning with current multi-constellation global navigation satellite systems: GPS, GLONASS, Galileo and BeiDou[J]. Scientific Reports, 2015, 5: 8328.
[2]FERRARA N G, NURMI J, LOHAN E S. Multi-GNSS analysis based on full constellations simulated data[C]∥2016 International Conference on. Barcelona: IEEE, 2016: 1-6.
[3]BLANCO-DELGADO N, NUNES F D. Satellite selection method for multi-constellation GNSS using convex geometry[J]. IEEE Transactions on Vehicular Technology, 2010, 59(9): 4289-4297.
[4]ROONGPIBOONSOPIT D, KARIMI H A. A multi-constellations satellite selection algorithm for integrated global navigation satellite systems[J]. Journal of Intelligent Transportation Systems, 2009, 13(3): 127-141.
[5]WU C H, SU W H, HO Y W. A study on GPS GDOP approximation using support-vector machines[J]. IEEE Transactions on Instrumentation and Meas-urement, 2011, 60(1): 137-145.
[6]宋丹, 许承东, 胡春生, 等.基于遗传算法的多星座选星方法[J].宇航学报, 2015, 36(3): 300-308.
SONG Dan, XU Chengdong, HU Chunsheng, et al. Satellite selection with genetic algorithm under multi-constellation[J]. Journal of Astronautics, 2015, 36(3): 300-308.
[7]陈灿辉,朱红,詹景坤,等.一种新的遗传算法交叉算子及其在GNSS星座选择中的应用[J].计算机测量与控制, 2015, 23(10): 3452-3454.
CHEN Canhui, ZHU Hong, ZHAN Jingkun, et al. A novel crossover operator of genetic algorithm and its application in satellite selection of GNSS[J]. Computer Measurement and Control, 2015, 23(10): 3452-3454.
[8]霍航宇,张晓林.组合卫星导航系统的快速选星方法[J]. 北京航空航天大学学报, 2015, 41(2): 273-282.
HUO Hangyu, ZHANG Xiaolin. Fast satellite selection method for integraed navigation systems[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(2): 273-282.
[9]BLANCO-DELGADO N, NUNES F D, SECO-GRANADOS G. Relation between GDOP and the geometry of the satellite constellation[C]∥2011 International Conference on Localization and GNSS (ICL-GNSS). Tampere: IEEE, 2011: 175-180.
[10]TENG Y, WANG J. New characteristics of geometric dilution of precision (GDOP) for multi-GNSS constellations[J]. Journal of Navigation, 2014, 67(06): 1018-1028.
[11]DEB K. Multi-objective optimization using evolutionary algorithms[M]. New York: John Wiley & Sons, 2001.
[12]KONAK A, COIT D W, SMITH A E. Multi-objective optimization using genetic algorithms: A tutorial[J]. Reliability Engineering & System Safety, 2006, 91(9): 992-1007.
[13]SRINIVAS N, DEB K. Muiltiobjective optimization using nondominated sorting in genetic algorithms[J]. Evolutionary Computation, 1994, 2(3): 221-248.
[14]DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197.
[15]COELLO C A C, CHRISTIANSEN A D. MOSES: A multiobjective tool for engineering design[J]. Engineering Optimization, 1999, 31(3): 337-368.