基于遗传算法选星的高中低轨导航混合星座完好性监测技术

doi:10.11959/j.issn.2096-8930.2023043

摘要/Abstract

摘要：

低轨卫星在通信、导航、遥感等领域应用广泛，对满足通信需求、提升导航定位精度具有重要意义。完好性监测技术是卫星导航系统安全与可靠运行的重要保障，随着低轨技术的成熟发展与海量低轨卫星的逐步应用，亟待开展高中低轨混合星座条件下系统及用户的完好性监测技术研究。提出一种基于遗传算法选星的高中低轨导航混合星座完好性监测技术，在传统最佳几何精度因子选星法的基础上，通过引入遗传算法，构造基于卫星几何观测矩阵特征斜率线性加权的适应度因子，以实现用户保护水平向保护限值的快速收敛。相较于传统算法，此算法通过优化选星的方式，进一步提升了接收机的完好性。在CAT I精密条件下，对于“北斗＋StarNet-1”星座，此算法全球范围可用性水平平均增强了 5.60%，对于东半球中纬地区和东半球低纬地区增强效果最佳，全球范围可用性水平分别增强了7.01%和6.42%。

关键词: 遗传算法, 接收机自主完好性监测, 高中低轨混合, 加权适应度因子

Abstract:

Low-orbit satellites are widely used in communication, navigation, remote sensing and other fields, which is of great significance to meet the needs of communication and improve the accuracy of navigation and positioning.Integrity technology is an important guarantee for the safe and reliable operation of satellite navigation system.With the mature development of low orbit technology and the gradual application of a large number of low orbit satellites, it is urgent to develop the system integrity monitoring technology under the condition of mixed constellation of high and low orbits.This paper proposed a hybrid constellation integrity monitoring technology for high, middle and low orbit navigation based on genetic algorithm for star selection.On the basis of the traditional optimal geometric accuracy factor selection method, genetic algorithm was introduced to construct a fitness factor based on the linear weighted feature slope of the satellite geometric observation matrix, so as to achieve rapid convergence of user protection level to protection limit.This method further improved the integrity of the receiver by optimizing the way of star selection.Under the accuracy requirement of CAT I, for the ＆quot;BeiDou+StarNet-1＆quot; constellation, the global availability level of the proposed algorithm was 5.60%, and the enhancement effect was the best for the mid-latitude and low-latitude of the Eastern Hemisphere, which were increased by 7.01% and 6.42%, respectively.

Key words: genetic algorithm, receiver autonomous integrity monitoring, high and low medium rail mix, weighted fitness factor

中图分类号:

TN927.2

吴政城, 倪少杰, 刘文祥, 肖伟, 李宗楠. 基于遗传算法选星的高中低轨导航混合星座完好性监测技术[J]. 天地一体化信息网络, 2023, 4(4): 61-70.

Zhengcheng WU, Shaojie NI, Wenxiang LIU, Wei XIAO, Zongnan LI. Integrity Monitoring Technology of Mixed Constellation of High, Medium and Low Orbit Navigation Based on Genetic Algorithm Star Selection[J]. Space-Integrated-Ground Information Networks, 2023, 4(4): 61-70.

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星座参数	设置
星座参数	StarNet-1(108颗)		StarNet-2(384颗)
轨道类型	LEO	LEO	LEO	LEO
卫星数/颗	108	108	216	60
星座构型	Walker 108/12/1	Walker 108/12/1	Walker 216/12/1	Walker 60/6/1
轨道倾角	50°	50°	50°	86.5°
轨道高度/km	1 150	1 150	1 150	1 175

对比项	方案	高纬地区		中纬地区		低纬地区
对比项	方案	W	E	W	E	W	E
N _sat /颗	Star I	15	16	10	21	11	24
N _sat /颗	Star II	15	16	12	23	11	25
HPL	Star I	12.60	11.15	38.95	10.84	22.16	7.44
HPL	Star II	12.60	11.15	21.54	9.60	19.69	7.22
VPL	Star I	14.28	13.23	34.47	10.56	21.70	9.11
VPL	Star II	14.28	13.23	18.87	9.05	19.38	8.67

方案	高纬地区		中纬地区		低纬地区		全球平均值
方案	W	E	W	E	W	E	全球平均值
Star II	7.32	18.88	16.94	71.87	5.10	75.81	41.94
Star III	7.50↑	19.80↑	17.33↑	76.91↑	4.39↓	80.68↑	44.29↑
表注：↑为数值优化，↓为数值劣化，单位为%

方案	高纬地区		中纬地区		低纬地区		全球平均值
方案	W	E	W	E	W	E	全球平均值
Star Ⅰ	7.32	18.88	7.15	58.52	2.60	71.21	37.47
Star II	7.32	18.88	16.94	71.87	5.10	75.81	41.94
Star Ⅲ	7.50	19.08	17.33	76.91	4.39	80.68	44.29
Star Ⅳ	14.68	34.58	38.10	86.04	10.71	83.96	51.22
Star Ⅴ	15.87	38.13	38.89	90.62	12.30	88.33	55.08
表注：红色为当前区域最大值，绿色为当前区域最小值，单位为%