GPS动态定位中自适应卡尔曼滤波研究

采用描述机动载体运动的“当前”统计模型，建立了一种新的GPS动态定位自适应卡尔曼滤波模型。为了进一步提高滤波器的动态性能，提出一种改进的自适应滤波算法，大大提高了GPS动态定位卡尔曼滤波器的跟踪能力，改善了滤波效果。计算机仿真结果验证了该算法的有效性。     

一种新的GPS快速整周模糊度解算算法

本文实现了一种新的GPS快速整周模糊度解算算法,首先采用Kalman滤波估计初始浮点模糊值,然后采用FASF（快速模糊度搜索滤波器）和Z变换联合的方法解算整周模糊度,并给出了计算机实验结果。相对于传统的模糊度解算算法,本文采用的整周模糊度解算方法具有效率更高、更便于实时和动态应用的特点,本文的研究可作为GPS实时高动态定位和GPS实时姿态测量的工程应用的参考。     

基于SR-UKF的高动态GPS信号参数估计

高动态环境下,全球定位系统（GPS）信号具有较强的非线性特性,为了更好地对高动态条件下的GPS信号载波进行跟踪,提出了一种基于平方根UKF（SR-UKF）算法的高动态GPS信号参数估计方法。分析了高动态环境下GPS信号载波相位模型,运用SR-UKF算法对高动态GPS信号的载波相位及其前三阶导数进行估计。仿真对比了SR-UKF、不敏卡尔曼滤波（UKF,Unscented Kalman Filter）和扩展卡尔曼滤波（EKF）载波跟踪算法的性能。仿真结果表明,SR-UKF的估计精度要好于EKF,与UKF基本一致,验证了该算法的可靠性和有效性。     

超级航姿中基于变阈值判据的自适应Kalman滤波

超级航姿系统因受外界干扰而使加速度计输出稳定性发生变化时,传统航姿算法易引起载体机动状态误判,且易导致滤波器振荡甚至发散,因此,该文提出了一种基于模糊推理系统的变阈值载体机动判据自适应Kalman滤波算法。该算法能根据加速度计输出稳定性的变化,自适应地调节载体机动判据及滤波器的量测噪声阵,从而降低载体机动状态的误判率,并提高滤波器对量测信息的利用程度。仿真实验表明,当加表稳定性发生变化时,该算法仍能较好地判断出载体的机动状态,并对量测噪声阵作出相应调整,使超级航姿系统的长航时姿态精度和滤波稳定性得到提高。     

利用Kalman滤波修正卫星导航差分RTK定位坐标

卫星导航差分RTK(Real Time Kinematic)定位方法的定位精度极易受到载波相位整周模糊度固定算法的影响,在模糊度固定失败的情况下,差分RTK定位将出现大幅偏差.针对该问题,基于Jerk模型提出了一种利用Kalman滤波修正差分RTK定位坐标的方法.在传统Jerk模型基础上,将卫星导航系统输出的载体运动速度信息引入状态空间模型的观测方程.基于扩展状态空间模型,利用Kalman滤波器实时修正载体的位置坐标.半实物仿真表明,所提方法能大幅改善卫星导航差分RTK定位精度.     

低载噪比GPS信号载波跟踪环路滤波算法

抑制锁相环（PLL）中的抖动噪声对于连续精确跟踪低载噪比GPS信号具有重要意义。本文设计了一种基于Kalman滤波理论的PLL模型用于处理GPS软件接收机中的弱载波信号。该模型通过去相关模型误差噪声和测量噪声,使PLL具有更小的过冲和噪声干扰的载波相位差和多普勒频移的正确估计,保持了PLL对GPS信号的有效跟踪。最后,通过仿真实验说明了基于Kalman滤波器的PLL的可行性。     

基于Kalman滤波预测主动段卫星测控信号质量的方法

通过建立卫星运动学模型,采用kalnmn滤波算法得到主动段卫星飞行弹道的最优估计以及卫星飞行姿态变化情况,利用其与卫星天线辐射方向图的对应关系,修正星地理论接收电平,最终实现主动段卫星姿态变化情;兄下,星地测控信号质量的预测,为地面决策指挥提『盐科学的信息支持。     

GPS相位观测值中周跳的探测与修复

对于初始化载波相位整周模糊度的GPS定位而言,如果在整周模糊度初始化过程中发生载波相位周跳,将严重影响整周模糊度的确定.针对GPS载波相位定位中出现的周跳问题,提出了一种新的周跳的检测方法,首先用多项式模型的卡尔曼滤波对载波相位测量值进行预处理,然后再用奇偶矢量法探测和修复周跳.通过某OEM板输出的数据计算结果仿真,验证了新方法可以有效地探测出一周周跳.     

基于自适应锁相环的高动态GPS信号载波跟踪算法

提出了一种基于四维卡尔曼滤波的自适应锁相环算法,并将该算法用于高动态GPS信号的载波跟踪.详细推导了卡尔曼滤波与数字锁相环之间的等效性,并给出了相应的环路更新步骤.仿真结果表明,该算法相对于采用固定增益数字锁相环的算法明显地降低了载波跟踪过程的均方根频率误差,提高了接收机的测速精度.     

关于GPS单星定时提高定时精度的研究

为满足特殊用户或固定站点对高精度定时信息的需求,文中重点研究位置已知情况下基于卡尔曼滤波算法的GPS单颗星定时的方法。理论分析及仿真结果表明：与位置未知时四颗星联合定位／定时方法相比,位置已知情况下单颗星定时的精度优于位置未知时多星联合定位定时的时间精度,同时,利用观测到的多颗GPS卫星分别进行单星定时得到的信息,可进一步提高时间精度。     

合成孔径雷达卫星姿态指向稳定度与图像质量关系的研究

姿态指向稳定度是合成孔径雷达(SAR)卫星平台设计的重要参数.本文基于成对回波畸变理论研究了存在姿态指向变化时星载SAR的点目标扩展函数表达式,在理论分析与大量计算机仿真实验基础上,总结了姿态指向变化对星载SAR图像质量影响的本质规律,推导了工程上分析卫星姿态指向稳定度同SAR图像质量之间定量关系的解析表达式,提出了适用于SAR卫星特点的姿态指向稳定度定量分析方法,为SAR卫星系统总体分析与设计提供了理论依据.根据L、C和X波段SAR卫星参数进行计算机仿真实验,验证了结论的正确性.     

A Nonlinear Filtering Approach for Robust Multi-GNSS RTK Positioning in Presence of Multipath and Ionospheric Delays

In this paper, we develop a new approach of precise positioning using three carrier phase multi-Global Navigation Satellite System (GNSS) measurements in presence of multipath and ionospheric delays. We propose a new nonlinear filter to estimate the user position as well as all the unknown parameters including the integer ambiguities and the ionospheric errors. First, we use a kernel representation of the conditional density and apply a local linearization which yields a Kalman-like correction enhancing the particle filter correction. This new particle Kalman filter approach, is designed to be efficient for the non-Gaussian state and nonlinear measurements model, reduces the number of needed particles, and reduces the risk of divergence. The proposed procedure for multifrequency ambiguity resolution is based on four steps: 1) at each epoch, we compute the float solution adaptively to the dynamic environment by minimizing the noise level and estimating the ionospheric errors using the proposed robust Bayesian particle Kalman filter (RobPKF); 2) we introduce a new carrier phase multipath indicator and use it to derive a related constraint to reject integers candidates that are affected by multipath errors; 3) we apply the LAMBDA method to search the integer ambiguities; and finally 4) validate the fixed solution using a statistical test. We show in this work that the efficient integration of multifrequency/multisystem carriers provides more redundancy in the measurements and better observability for multipath and ionospheric errors estimation for long-baseline RTK positioning. A major advantage of this method is that it is independent of frequencies choice and therefore can be applied for any multi-GNSS measurements (e.g., Global Positioning System (GPS), Galileo, and their combination). Real-time and postprocessing test results show the effectiveness of the developed overall real-time kinematic (RTK) software.     

基于QEKF的四旋翼飞行器姿态估计

提出了一种基于四元数扩展卡尔曼滤波(QEKF)数据融合算法,应用于四旋翼飞行器的姿态估计。首先,用四元数表示航向姿态参考系统(AHRS)中的坐标旋转关系,获取飞行器的姿态信息;然后,结合扩展卡尔曼滤波算法,融合低成本的MPU9250中陀螺仪、加速度计、磁力计传感器的9轴原始输出数据,对飞行器的真实姿态进行跟踪估计;最后,通过MATLAB实验仿真,与互补滤波(CF)和梯度下降法(GD)算法进行比较,实验证明QEKF对姿态的估计更加精准。     

Satellite attitude determination based on GPS signal-to-noise ratio

A method is presented for coarse attitude determination using the Global Positioning System (GPS) signal-to-noise ratio (SNR) from a single antenna mounted on a near-Earth satellite. It comprises a calibration procedure and a single-point optimal solution for the orientation of the antenna boresight vector. The calibration step creates an empirical mapping of the SNR to the angle between the antenna boresight and the GPS line-of-sight vector, based upon a ground or flight data set. The rms attitude accuracy at the level of 3°-10° is demonstrated with actual flight data from several spacecraft. Performance is shown to depend strongly on the number of GPS signals available and the quality of the calibration mapping function. The method is suitable as a backup attitude sensor for low-cost satellite and terrestrial applications, and as a coarse reference for ambiguity resolution and integrity verification of phase-based GPS attitude-determination algorithms     

基于扩展卡尔曼滤波的GPS动态测速算法

为使车载GPS测速精度满足应用于汽车电子控制系统的要求,提出一种对包含白噪声的时变GPS位置数据采用扩展卡尔曼滤波进行测速算法。通过扩展卡尔曼滤波和位差法融合对实车采集到的汽车位置等信息进行处理得到行车速度。通过实验结果对比分析,基于扩展卡尔曼滤波的测速算法比位置差分法的均方差提高了92.499%,测速精度明显提升。     

对角加载对信号源数检测性能的改善

对角加载技术可抑制小特征值对自适应权值的影响来加速自适应波束形成器的收敛性以及抑制导向矢量误差的影响避免信号相消,该技术通常用于稳健的波束形成算法.基于对角加载技术,本文提出了一种信号源数目判定的改进方法,通过对角加载数据协方差阵,可以平滑小快拍数和空间色噪声时的噪声特征值分散程度从而减轻其对信号源数目估计的影响,证明了该估计器的强一致性,分析了加载量对信号源数目估计的影响.最后通过仿真以及实测数据比较了本文方法和已有方法的性能,验证了所提方法的有效性.     

基于GPS和改进MapDrift的机载UWB SAR运动补偿

传统的基于载机运动传感器的SAR运动补偿对传感器测量精度提出了很高的要求,而基于回波数据的Map- Drift(MD)自聚焦效果对成像场景存在一定的依赖性。本文针对UWB SAR系统的特点,提出了一种结合GPS(Global Position System)粗补偿和改进重叠MD精补偿的机载SAR运动补偿方法。利用GPS的三维位置信息补偿回波时移误差,利用三维速度信息补偿回波相位误差,然后再利用改进重叠MD补偿剩余误差。本文提出的UWB SAR运动补偿方法没有使用高精度的惯导系统,节约了系统成本,降低了补偿系统的实现难度,并减小了MD算法对成像场景的依赖性,有效提升了SAR图像质量。实际UWB SAR数据的处理验证了本文方法的有效性。     

基于SCKF和姿态估计的SINS/GPS在线对准方法

该文提出了基于平方根容积卡尔曼滤波和初始姿态估计的捷联惯导/全球定位系统组合在线对准法。构建平方根容积卡尔曼滤波器来对初始姿态估计的非线性量测模型进行滤波,估计代表初始姿态转换矩阵的罗德里格参数,并以此求出当前时刻的姿态转换矩阵,从而求出当前时刻准确的姿态。该文分别对制导武器系统和车载系统进行了半实物仿真。仿真结果表明,此方法可在25 s左右完成在线对准。其中短距离制导武器仿真结果航向角及俯仰角误差在0.1°内,横滚角误差在0.3°内;低成本车载导航系统仿真结果航向角误差在0.2°内,俯仰角及横滚角误差在1°内,可满足制导武器及低成本民用车辆的对准需求。     

高阶QAM信号多状态自适应卡尔曼滤波载波同步算法

通信信号盲载波恢复是非协作模式下接收方解调的关键环节之一。为提高频偏捕获范围与速度,同时有效增强算法跟踪时变频偏能力,本文针对正交幅度调制(QAM)信号,通过理论推导得出滤波器环路带宽的变化特性,提出一种基于自适应判决引导扩展卡尔曼滤波的载波同步算法。该算法在现有卡尔曼滤波载波同步算法的基础上,引入多状态自适应切换机制自适应地改变滤波器参数,并依据实验测试数据分析得出调整原则并完成滤波器参数的选取。理论分析和仿真表明,与已有的卡尔曼载波同步算法及二阶数字锁相环算法相比,该算法不仅捕获速度更快范围更大,且能在存在时变多普勒频移的情况下较好地跟踪时变频偏和相位,在大频偏条件下的算法跟踪性能与鲁棒性等方面均有优势。      

Position Estimation in Single-Frequency GPS Receivers Using Kalman Filter with Pseudo-Range and Carrier Phase Measurements

Today Global Positioning System (GPS) is the most important system of positioning in the world and is used in different industries. Basic positioning methods in GPS receivers are based on pseudo-range and carrier phase measurements types whilst each of which has its own advantages and disadvantages. Pseudo-range method is not very much accurate. Carrier phase has a substantial accuracy, but its main problem is that it is an indirect measurement which only computes the displacement. Carrier phase measurement can include some whole cycles plus a fraction of carrier phase. The number of whole cycles may change through time however this change is unknown for us. Code measurements (based on pseudo-range) and carrier phase are corrupted with the same error sources, but with main differences. Basically, code tracking with low accuracy makes unambiguous pseudo-ranges. Carrier phase measurements are highly accurate, but get limited with integer ambiguity. Integer is fixed until the time that carrier tracking loop is saved. Every kind of gap in tracking, no matter how short it is, changes the amount of integer which is the biggest problem in carrier phase utilization. In this paper, the corporation of pseudo-range capability and carrier phase in single-frequency GPS receivers will be discussed which makes a substitute for the pure pseudo-range observations and provides a high level of positioning accuracy. To achieve this aim, Kalman filter will be used.