基于GNSS通道差分的紧组合滤波方法研究

在基于伪距、伪距率的常规紧组合导航系统中,若GNSS出现时钟异常等情况,则会引起伪距、伪距率误差异常,从而导致组合导航精度下降;与松组合滤波器相比,常规紧组合滤波器扩充了状态变量的维数,增加了运算复杂度,降低了组合滤波的实时性.本文提出了一种双通道降维滤波算法,其中状态变量不再包含伪距、伪距率误差;以GNSS通道伪距、伪距率差分信息作为观测量.通过仿真表明,采用双通道降维滤波算法可以有效削弱时钟异常等的影响,并且有效提高组合滤波的实时性.     

GNSS无源 MIMO雷达系统及其探测性能分析

提出一种综合使用多GNSS系统可用导航卫星信号源和基于MIMO信号处理体制的无源多基地雷达系统结构,利用M IM O处理获得的空间分集增益来改善雷达探测性能。分析了系统的可用信号源情况,讨论了系统中前向散射区的确定和目标前向散射RCS的计算问题,在此基础上,对基于GNSS信号的无源MIMO雷达系统的探测性能进行了深入研究并给出了仿真计算结论。     

Medium Earth Orbit dynamical survey and its use in passive debris removal

The Medium Earth Orbit (MEO) region hosts satellites for navigation, communication, and geodetic/space environmental science, among which are the Global Navigation Satellites Systems (GNSS). Safe and efficient removal of debris from MEO is problematic due to the high cost for maneuvers needed to directly reach the Earth (reentry orbits) and the relatively crowded GNSS neighborhood (graveyard orbits). Recent studies have highlighted the complicated secular dynamics in the MEO region, but also the possibility of exploiting these dynamics, for designing removal strategies. In this paper, we present our numerical exploration of the long-term dynamics in MEO, performed with the purpose of unveiling the set of reentry and graveyard solutions that could be reached with maneuvers of reasonable $\mathrm{\Delta }V$ cost. We simulated the dynamics over 120–200?years for an extended grid of millions of fictitious MEO satellites that covered all inclinations from 0 to 90°, using non-averaged equations of motion and a suitable dynamical model that accounted for the principal geopotential terms, 3rd-body perturbations and solar radiation pressure (SRP). We found a sizeable set of usable solutions with reentry times that exceed $～40$ years, mainly around three specific inclination values: 46°, 56°, and 68°; a result compatible with our understanding of MEO secular dynamics. For $\mathrm{\Delta }V?300$ m/s (i.e., achieved if you start from a typical GNSS orbit and target a disposal orbit with $e<0.3$), reentry times from GNSS altitudes exceed $～70$ years, while low-cost ($\mathrm{\Delta }V?5–35$ m/s) graveyard orbits, stable for at lest 200?years, are found for eccentricities up to $e\approx 0.018$. This investigation was carried out in the framework of the EC-funded “ReDSHIFT” project.     

基于随机森林的航天器电信号多分类识别方法

针对航天器电特性信号数据存在数据量大、特征维数高、计算复杂度大和识别率低等问题,提出基于主成分分析(PCA)的特征提取方法和随机森林(RF)算法,对原始数据进行降维,提高计算效率和识别率,实现对航天器电信号数据的快速、准确识别分类。随机森林算法在处理高维数据上具有优越的性能,但是考虑到时间复杂度问题,利用主成分分析方法对数据进行压缩和降维,在保证准确率的同时提高了计算效率。实验结果表明:与其他算法相比,针对航天器电特性信号数据,本文方法在准确率、计算效率和稳定性等方面均显示出优异的性能。     

Multipath mitigation method based on Gaussian mixture model in RF relative measurement

Radio Frequency (RF) technology represents a high-precision relative navigation solution that has significant potential for application to earth-orbiting satellites. In precision applications, multipath errors dominate the total error because observables, which are used to estimate carrier-phase integer ambiguity, are not always subject to a Gaussian distribution when dual-frequency ambiguity estimation methods are used in the presence of multipath. As it has been shown that ranging observables obey a Gaussian mixture distribution, this study proposes improvements to the accuracy of estimation based on multipath mitigation founded on the Gaussian mixture model. To this end, such a model is created for integer ambiguity resolution in the presence of multipath, using which the theoretical error in dual-frequency ambiguity estimation is derived. Expectation Maximization (EM), which aids dual-frequency ambiguity estimation, is subsequently proposed to reduce the effect of multipath errors. Finally, two experimental scenarios are implemented to test the performance of the proposed method. The results show that EM-aided dual-frequency ambiguity estimation reduces the range error to approximately 20% in comparison with simple dual-frequency ambiguity estimation. Therefore the proposed technique is effective for multipath mitigation in RF relative measurement.     

一种改善GNSS弱信号动态跟踪性能的FFT鉴频方法

基于快速傅里叶变换（FFT）鉴频器的GNSS弱信号跟踪技术可以有效改善城市峡谷环境的行人导航,然而现有的复数平方FFT （SFFT）鉴频器在车载等较高动态应用中弱信号跟踪性能大幅度下降。本文提出了一种在保证弱信号跟踪灵敏度的前提下,能显著提高动态性能的FFT鉴频方法——非相干FFT鉴频器（NonCoh-FFT）。首先,介绍了SFFT鉴频器和NonCoh-FFT鉴频器的结构原理;然后,从理论上分析了两者的灵敏度和动态性能;最后,基于GNSS信号模拟器产生的静态和动态场景,对比测试验证了SFFT和NonCoh-FFT性能。结果表明,NonCoh-FFT可以明显提高GNSS弱信号动态性能,与理论分析吻合。     

多无人机辅助定位信标的区域导航定位算法

针对卫星导航系统在受到干扰不可用的情况,研究了多无人机（UAV）辅助的区域导航定位算法。以无人机作为空基信号播发平台,向地面用户广播其位置信息及同步时钟信号,地面用户通过接收无人机位置及与无人机的距离计算出其实时位置。以地面战车为例,为解决伪距单点定位算法中的矩阵不可逆问题,消除地面用户接收机的钟差,基于列文伯格-马夸尔特（LM）算法,提出一种地面用户的定位解算模型,同时,为提高一般最小二乘算法的计算精度,提出了两步最小二乘定位算法。在分析2种算法静态定位精度的基础上,设计了基于车载惯性传感器和无人机辅助定位信息的组合导航实现算法,实现了对战车的连续定位。仿真结果表明,在GNSS拒止环境下,利用无人机播发的定位信标信号并结合地面用户战车自带的惯性导航系统,可以实现对地面用户的可靠连续定位,满足一定区域范围内用户的导航定位需求。     

欺骗环境下GNSS信号估计与定位修正技术

欺骗信号以其极强的隐蔽性使卫星导航接收机难以察觉并迅速定位到错误位置,严重影响了卫星导航的安全性。现有抗欺骗技术需要其他导航系统辅助来修正受欺骗影响的定位解算,针对该问题,本文提出了一种GNSS欺骗信号参数估计与辨识方法,能够在欺骗干扰环境下估计并辨识出真实信号所对应的伪距,进而解算出接收机真实位置。该方法通过研究欺骗干扰下接收机相关值模型,在信号跟踪阶段建立真实与欺骗双信号状态模型与基于九路相关器输出的观测模型,利用扩展卡尔曼滤波（EKF）估计真实信号与欺骗信号的伪码延时与信号相关幅值,进而获得真实与欺骗伪距,在定位解算阶段利用改进观测量残差检测方法辨识出真实与欺骗伪距,最终使用真实伪距定位获得真实位置。仿真结果表明对相对码延时介于0.3~0.9 chip之间且欺骗/真实信号幅度比介于1~5之间的隐蔽欺骗攻击,所提方法的码延时估计误差约0.1 chip,可有效估计真实信号与欺骗信号参数,辨识出真实伪距,并使被欺骗的定位结果重新回到真实位置结果,改善GNSS接收机抗欺骗能力,提高卫星导航安全性。     

低成本GNSS终端中北斗三号多频观测的分析及应用CSCD

低成本消费级GNSS芯片相较于传统测绘级接收机在体积、功耗等方面具有突出优势,在未来无人驾驶、物联网等新兴应用领域具有极大潜力。然而当前低成本GNSS芯片的观测量存在非常严重的噪声和误差,为了改善观测质量,低成本芯片正逐渐从单频向多频过渡。首先调研了目前低成本GNSS接收机对多频信号的支持情况,然后介绍了北斗三号多频观测在电离层延迟和整周模糊度估计等方面的应用。通过对真实数据的采集和分析,针对当前原始观测量存在的诸多问题,提出了具体的预处理方案,并在此基础上开展了信号强度、电离层和模糊度实验。实验结果表明,基于华为Mate 40手机的低成本GNSS方案的北斗三频电离层延迟估计误差的均值为-2.97m,三频整周模糊度估计的成功率达93.8%,相较于单频整周模糊度估计的3.11%成功率有显著提升。