PSO选星算法参数分析与改进

多星座组合导航提供更多的可用卫星,但也增大接收机计算复杂度,选取部分可见星代替全部可见星进行接收机位置解算成为选星算法研究的热点。粒子群优化（PSO）选星算法将PSO算法引入到选星过程中,该方法能够减少选星时间,实现北斗/GPS组合星座快速选星。研究了该算法的关键参数包括惯性权重因子、加速系数、种群大小等对PSO选星算法性能的影响,并针对搜索过程容易陷入局部最优问题,提出自适应模拟退火粒子群优化（ASAPSO）选星算法,该算法通过引入随适应值大小自适应调整进化参数及结合模拟退火算法调整粒子速度,以增强算法跳出局部极值的能力。采用实际数据对算法进行验证,结果表明:ASAPSO选星算法在保证选星时间的同时,能够提高算法搜索结果的准确性,其性能优于PSO选星算法。      

改进粒子群优化的卫星导航选星算法

为提高选星算法的性能,提出一种基于人工鱼群算法的粒子群优化（PSO）选星算法。该算法利用人工鱼群算法良好的全局收敛特性,克服了粒子群优化算法易陷入局部最优的缺点。将每种卫星组合看作空间中的一个粒子,选取几何精度因子（GDOP）作为适应度函数。利用所提算法更新粒子自身位置,优化卫星组合与几何精度因子。利用实际数据对所提算法进行验证和对比,结果表明:改进的选星算法在保障选星效率的同时,选星结果的准确性优于标准的粒子群优化选星算法。      

基于GPS/北斗组合系统的高轨卫星定位技术研究

针对目前高轨GPS信号可用性差及定位精度低的特点, 对GPS/北斗组合系统的 高轨卫星定位技术进行研究, 对比分析了单GPS系统与GPS/北斗组合系统的卫 星可见性和几何精度因子. 结果表明, GPS/北斗组合系统比单GPS系统的卫星可 见性好, 且定位精度高. 同时通过提出在星载接收机上采用高精度原子钟, 可实现三星定位, 降低对接收机的技术要求.      

粒子群优化粒子滤波的接收机自主完好性监测

接收机自主完好性监测（RAIM）是航空卫星导航接收机必不可少的功能,为保持全球卫星导航系统（GNSS）在卫星发生故障时系统性能不降级,需要对卫星故障进行检测和隔离。针对接收机观测噪声非高斯分布的特点,提出一种基于粒子群优化粒子滤波（PSO-PF）的故障检测和隔离算法。通过粒子群优化粒子滤波对状态估计进行一致性检验实现故障检测。采集实测数据验证算法的检测性能,并与基于基本粒子滤波的完好性监测算法进行比较,结果表明:本文所提算法在非高斯测量噪声下可检测并隔离全球定位系统（GPS）故障卫星,其性能优于基于基本粒子滤波的完好性监测算法性能,对研究北斗卫星导航系统（BDS）接收机自主完好性监测具有一定的意义。      

基于帝国竞争优化的双目标综合决策选星算法

全球卫星导航系统（GNSS）的应用前景已经得到世界各国的普遍承认,其应用领域也趋于多样化,在此背景下,卫星接收机也要求其具有更快的解算速度和可靠的精度。针对目前多数接收机的选星算法都是固定选星数目从而限制算法机动性的问题,提出基于帝国竞争优化算法（ICA）的双目标综合决策选星算法。为了更好获取几何构型较好的卫星星座,引入可见卫星的卫星仰角和方向角先验信息,进行先验性约束,通过构建几何精度因子（GDOP）以及选星数目2个目标,进行综合决策的快速选星,提高了选星的灵活度,并且在满足用户精度的要求下减轻了多星座卫星接收机的计算负担。通过仿真实验和实测数据对双目标综合决策选星算法验证的结果表明:所提算法在高度截止角5°下引入先验性约束条件后平均选星数目在仿真数据和实测数据中缩减率分别为51.8%和45.4%,平均GDOP值较无约束下分别减少0.209 2和0.248 4。同时,所提算法单次选星平均耗时分别为0.168 4 s和0.303 1 s,与遍历法的选星耗时4 s相比,提高了95.79%和92.42%。      

北斗和GPS双模接收机干扰抑制算法的设计与实现

目前北斗/GPS双模接收系统的抗干扰研究还比较少,主要是针对GPS的抗干扰研究。北斗和GPS接收机易被干扰,为了改善强干扰环境下接收机的性能,研究不同阵列、不同算法对接收机抗干扰性能的影响,在GPS的抗干扰研究的基础上设计并实现了一套北斗和GPS双模接收系统的抗干扰平台。实验结果表明,该系统能使北斗和GPS双模接收机在-30dBm强干扰的环境下搜到6颗北斗导航卫星和5颗GPS导航卫星,并正常定位,说明该系统能达到干扰抑制的目的。该系统也可推广至多种卫星导航接收机的抗干扰平台。     

BDS/GPS组合导航接收机自主完好性监测算法

为使接收机自主完好性监测（RAIM）技术应用于民航垂直引导进近（APV）飞行阶段成为可能,研究了BDS/GPS组合导航RAIM算法。提出了一种基于BDS/GPS定位解最优加权平均解的算法,结合最优加权平均解与BDS/GPS定位解的关系建立检验统计量,根据最大允许的虚警率计算检验门限,实现对故障所在卫星导航系统的检测,并采用加权最小二乘残差法对故障进行检测与识别。研究结果对多星座组合卫星导航系统应用于民航APV飞行阶段的导航具有一定的参考意义。      

基于并行遗传算法的高轨卫星导航选星方法

高轨航天器自主导航能力在北斗三号卫星导航系统建成后得到了增强，但是也带来了部分时刻可见星数量冗余的问题。为降低运算量以保证服务的实时性，提出一种利用多种群并行遗传算法(PGA)进行快速选择当前最优可见星组合的方法。该方法将加权精度因子(WDOP)作为适应度评判标准，利用粗粒度式并行划分成的多个子种群进行搜索加速，并通过变异因子差异化设置与子种群间的信息交流来提高搜索能力。对多个典型高轨环境下7颗及以上选星任务的仿真测试表明，基于PGA的选星方法解相比遍历法所求最优解绝对误差平均值小于0.1，相对误差最大不超过1%。仿真结果表明，在典型高轨环境F1接收机利用四系统组合导航时，所提方法可以有效地快速、准确完成指定卫星数的选星任务。     

基于最小二乘递推估计的GPS定位算法

首先从理论上证明了几何精度因子随卫星数目的增加而减小.然后提出了基于现有软件的几何精度因子和定位解的递推算法.该算法从剩余的可见卫星中选取使GDOP₅达到最小的第五颗星,利用这颗卫星提供的定位信息对四星定位解进行修正.最后给出了第五颗星的选择方法,算法的目的是以最小的计算量换取定位精度的有效提高.     

关于北斗卫星导航系统的被动式定位算法比较研究

我国北斗卫星导航系统空间卫星共有2或3颗,无法单独满足被动导航定位的要求．针对这种卫星稀少的情况提出了3种被动式定位算法: 2星定位算法、 3星3参数定位算法和3星4参数定位算法, 这些算法分别采用气压测高方法增加观测数据和采用数学模型描述接收机钟差的方法减少定位方程求解的未知数;探讨了北斗卫星导航系统备份星的可用性和对导航定位精度的贡献;还提出了准差分修正技术,提高了定位精度．实验证明, 3种算法都取得了100m以内的定位结果,可以满足一般用户定位需求．     

精密进近阶段的多系统GNSS组合RAIM可用性算法及分析

给出了多系统全球卫星导航系统（GNSS）组合接收机自主完好性监测（ReceiverAutonomousIntegrityMonitoring,RAIM）可用性计算方法,在此基础上利用GPS、GLONASS实测数据与BDS、Galileo全星座仿真数据,分析了BDS、GPS、GLONASS和Galileo不同组合在精密进近阶段的RAIM可用性。通过试验分析发现,BDS的5颗地球同步轨道卫星和3颗倾斜地球同步轨道卫星对亚洲、非洲和欧洲大部分地区的RAIM可用性有很大的贡献。这些地区站星间几何观测结构得到改善,使得RAIM可用性相对于其他地区有很大幅度的提升。在亚太地区APV-I阶段单系统导航情况下,北斗导航系统RAIM可用性达到99.5%,高于其他三个导航系统。在精密进近阶段（APV-I、APV-II和CAT-I）,BDS与其他导航系统（GPS、GLONASS和Galileo）的组合导航可以满足全球大部分区域的RAIM可用性需求,大多可达到100%。     

组合卫星导航系统的快速选星方法

分析了选星数目与几何精度因子(GDOP, Geometry Dilution of Precision)及导航运算量的关系,基于遗传算法提出了一种以满足用户定位精度需求为条件的快速选星方法——快速遗传选星法.根据用户需求确定选星数目初值、选星数目最大值和GDOP阈值,构造选星方案的初始种群,在进化代数上限为1的条件下对种群进行选择、交叉和变异运算,获得初始选星解,根据初始解的GDOP与阈值的关系确定是否依据GDOP最小原则对初始解进行优化,直至满足算法终止条件,输出选星解.仿真结果表明,该算法可以在一次进化之内以不低于92.45%的概率满足GDOP阈值在2.5~6的要求,同时可有效降低54.75%以上的导航运算量.      

组合卫星接收机中的选星算法

分析了五阶矩阵的行列式值与5颗星GDOP(Geometry Dilution of Precision)值的关系,并由此提出了一种用于双卫星星座组合接收机(如GPS(Global Position System)和BD2(BeiDou2)组合接收机)中的选星算法——组合优选法.该方法首先选出行列式绝对值最大的几种组合,然后根据需要对每种组合从其余可见星中选出几颗最优星,最后根据GDOP最小原则从这几种组合中选取最终结果.计算机仿真结果显示该方法与直接利用GDOP选星相比,95％以上的GDOP相对比值小于5％,而计算量减小40％以上.      

LEO enhanced Global Navigation Satellite System (LeGNSS) for real-time precise positioning services

Global Navigation Satellite System (GNSS) has been widely used in many geosciences areas with its Positioning, Navigation and Timing (PNT) service. However, GNSS still has its own bottleneck, such as the long initialization period of Precise Point Positioning (PPP) without dense reference network. Recently, the concept of PNTRC (Positioning, Navigation, Timing, Remote sensing and Communication) has been put forward, where Low Earth Orbit (LEO) satellite constellations are recruited to fulfill diverse missions. In navigation aspect, a number of selected LEO satellites can be equipped with a transmitter to transmit similar navigation signals to ground users, so that they can serve as GNSS satellites but with much faster geometric change to enhance GNSS capability, which is named as LEO constellation enhanced GNSS (LeGNSS). As a result, the initialization time of PPP is expected to be shortened to the level of a few minutes or even seconds depending on the number of the LEO satellites involved. In this article, we simulate all the relevant data from June 8th to 14th, 2014 and investigate the feasibility of LeGNSS with the concentration on the key issues in the whole data processing for providing real-time PPP service based on a system configuration with fourteen satellites of BeiDou Navigation Satellite System (BDS), twenty-four satellites of the Global Positioning System (GPS), and sixty-six satellites of the Iridium satellite constellations. At the server-end, Precise Orbit Determination (POD) and Precise Clock Estimation (PCE) with various operational modes are investigated using simulated observations. It is found out that GNSS POD with partial LEO satellites is the most practical mode of LeGNSS operation. At the user-end, the Geometry Dilution Of Precision (GDOP) and Signal-In-Space Ranging Error (SISRE) are calculated and assessed for different positioning schemes in order to demonstrate the performance of LeGNSS. Centimeter level SISRE can be achieved for LeGNSS.     

Calibration errors in determining slant Total Electron Content (TEC) from multi-GNSS data

The global navigation satellite system (GNSS) is presently a powerful tool for sensing the Earth's ionosphere. For this purpose, the ionospheric measurements (IMs), which are by definition slant total electron content biased by satellite and receiver differential code biases (DCBs), need to be first extracted from GNSS data and then used as inputs for further ionospheric representations such as tomography. By using the customary phase-to-code leveling procedure, this research comparatively evaluates the calibration errors on experimental IMs obtained from three GNSS, namely the US Global Positioning System (GPS), the Chinese BeiDou Navigation Satellite System (BDS), and the European Galileo. On the basis of ten days of dual-frequency, triple-GNSS observations collected from eight co-located ground receivers that independently form short-baselines and zero-baselines, the IMs are determined for each receiver for all tracked satellites and then for each satellite differenced for each baseline to evaluate their calibration errors. As first derived from the short-baseline analysis, the effects of calibration errors on IMs range, in total electron content units, from 1.58 to 2.16, 0.70 to 1.87, and 1.13 to 1.56 for GPS, Galileo, and BDS, respectively. Additionally, for short-baseline experiment, it is shown that the code multipath effect accounts for their main budget. Sidereal periodicity is found in single-differenced (SD) IMs for GPS and BDS geostationary satellites, and the correlation of SD IMs over two consecutive days achieves the maximum value when the time tag is around 4?min. Moreover, as byproducts of zero-baseline analysis, daily between-receiver DCBs for GPS are subject to more significant intra-day variations than those for BDS and Galileo.     

Multi-GNSS contributions to differential code biases determination and regional ionospheric modeling in China

Due to the limited number and uneven distribution globally of Beidou Satellite System (BDS) stations, the contributions of BDS to global ionosphere modeling is still not significant. In order to give a more realistic evaluation of the ability for BDS in ionosphere monitoring and multi-GNSS contributions to the performance of Differential Code Biases (DCBs) determination and ionosphere modeling, we select 22 stations from Crustal Movement Observation Network of China (CMONOC) to assess the result of regional ionospheric model and DCBs estimates over China where the visible satellites and monitoring stations for BDS are comparable to those of GPS/GLONASS. Note that all the 22 stations can track the dual- and triple-frequency GPS, GLONASS, and BDS observations. In this study, seven solutions, i.e., GPS-only (G), GLONASS-only (R), BDS-only (C), GPS + BDS (GC), GPS + GLONASS (GR), GLONASS + BDS (RC), GPS + GLONASS + BDS (GRC), are used to test the regional ionosphere modeling over the experimental area. Moreover, the performances of them using single-frequency precise point positioning (SF-PPP) method are presented. The experimental results indicate that BDS has the same ionospheric monitoring capability as GPS and GLONASS. Meanwhile, multi-GNSS observations can significantly improve the accuracy of the regional ionospheric models compared with that of GPS-only or GLONASS-only or BDS-only, especially over the edge of the tested region which the accuracy of the model is improved by reducing the RMS of the maximum differences from 5–15 to 2–3 TECu. For satellite DCBs estimates of different systems, the accuracy of them can be improved significantly after combining different system observations, which is improved by reducing the STD of GPS satellite DCB from 0.243 to 0.213, 0.172, and 0.165 ns after adding R, C, and RC observations respectively, with an increment of about 12.3%, 29.4%, and 32.2%. The STD of GLONASS satellite DCB improved from 0.353 to 0.304, 0.271, and 0.243 ns after adding G, C, and GC observations, respectively. The STD of BDS satellite DCB reduced from 0.265 to 0.237, 0.237 and 0.229 ns with the addition of G, R and GR systems respectively, and increased by 10.6%, 10.4%, and 13.6%. From the experimental positioning result, it can be seen that the regional ionospheric models with multi-GNSS observations are better than that with a single satellite system model.