Improvements on the particle-filter-based GLONASS phase inter-frequency bias estimation approach

The carrier phase inter-frequency bias (IFB) of GLONASS between receivers of different types is usually not zero. This bias must be estimated and removed in data processing so that the integer double difference (DD) ambiguities can be fixed successfully. Recently, the particle filter approach has been proposed to estimate the IFB rate in real time. In this approach, the IFB rate samples are first generated and used to correct the phase IFB in the GLONASS observations. Then, the weights of the rate samples are updated with a function related to RATIO which is for ambiguity acceptance testing in integer ambiguity resolution. Afterwards, the IFB rate is estimated according to the weighted particles. This approach can estimate IFB accurately with short convergence time and without prior information. However, when the system noise is set too low, the estimated results are unstable due to the serious problem of particle diversity-loss, even though the system model is accurate. Additionally, the computational burden is dependent on the number of particles, which has to be optimized for the computation at hand. Therefore, this study proposes two improvements for the IFB estimation in regard to the above two aspects. The first improvement is to solve the noise setting problem by employing a regularized particle filter (RPF). The second improvement optimizes the number of particles in the resampling step according to the standard deviation (STD) of the weighted particles via a controlling function. The two improvements result in significantly better performances. The regularization method allows for the system noise to be set as zero without disturbing the estimates, and consequently, more precise estimates can be achieved. In addition, the approach using the controlling function for adapting the number of particles has comparable performance in precision but the computation load is largely reduced.     

Influence of the GLONASS inter-frequency bias on differential code bias estimation and ionospheric modeling

GPS Solutions - Due to the application of frequency division multiple access, the signals of GLONASS satellites suffer from code and carrier phase inter-frequency biases (IFBs). In this study, the...     

A new method for GLONASS inter-frequency bias estimation based on long baselines

GPS Solutions - Frequency division multiplexing of GLONASS signals causes inter-frequency bias (IFB) in receiving equipment. IFB significantly increases the difficulties of fixing GLONASS...     

顾及频率间偏差的GPS/GLONASS卫星钟差实时估计

GPS/GLONASS卫星钟差联合估计过程中,由于GLONASS系统采用频分多址技术区分卫星信号,因而会产生频率间偏差（IFB）^[1]。本文在GPS/GLONASS卫星定轨过程中的IFB参数特性分析的基础上,引入IFB参数,实现顾及频率间偏差的GPS/GLONASS卫星钟差实时估计。同时,为解决实时估计中待估参数过多导致的实时性较弱等问题,基于非差伪距观测值和历元间差分相位观测值改进实时估计数学模型,实现多系统卫星钟差的联合快速估计。结果表明：GPS/GLONASS联合估计时需引入IFB参数并优化其估计策略,采用MGEX和iGMAS跟踪站的实测数据进行实时钟差解算,快速估计方法可实现1.6 s逐历元快速、高精度估计,与GBM提供的最终精密卫星钟差相比,GPS卫星钟差实时精度约为0.210 ns,GLONASS卫星约为0.298 ns。     

GLONASS频间码偏差实时估计方法及其在RTK定位中的应用

GLONASS伪距频间偏差难以利用经验模型消除。在RTK定位解算中,尤其是需顾及大气延迟的中长距离异质基线,IFCB会降低模糊度收敛速度,甚至导致模糊度固定错误。本文基于双差HMW组合和消电离层组合,提出一种站间IFCB实时估计算法,实时获取各频段的非组合站间单差IFCB。试验结果表明,站间IFCB长期稳定,可达数个纳秒;在GPS/GLONASS观测值先验误差比值为3：5的条件下,未改正的IFCB可能导致基线GPS/GLONASS组合RTK定位性能比单GPS差。将本文提出算法应用于RTK定位,能够有效消除IFCB的影响,RTK模糊度浮点解精度、定位收敛速度和固定率都有明显改善,部分基线的RTK定位首次固定时间从9.2 s提高到2.1 s,固定解比率从84.5%提高到97.9%。     

GLONASS phase bias estimation and its PPP ambiguity resolution using homogeneous receivers

Integer ambiguity resolution (IAR) appreciably improves the position accuracy and shortens the convergence time of precise point positioning (PPP). However, while many studies are limited to GPS, there is a need to investigate the performance of GLONASS PPP ambiguity resolution. Unfortunately, because of the frequency-division multiple-access strategy of GLONASS, GLONASS PPP IAR faces two obstacles. First, simultaneously observed satellites operate at different wavelengths. Second and most importantly, distinct inter-frequency bias (IFB) exists between different satellites. For the former, we adopt an undifferenced method for uncalibrated phase delay (UPD) estimation and proposed an undifferenced PPP IAR strategy. We select a set of homogeneous receivers with identical receiver IFB to perform UPD estimation and PPP IAR. The code and carrier phase IFBs can be absorbed by satellite wide-lane and narrow-lane UPDs, respectively, which is in turn consistent with PPP IAR using the same type of receivers. In order to verify the method, we used 50 stations to generate satellite UPDs and another 12 stations selected as users to perform PPP IAR. We found that the GLONASS satellite UPDs are stable in time and space and can be estimated with high accuracy and reliability. After applying UPD correction, 91 % of wide-lane ambiguities and 99 % of narrow-lane ambiguities are within (?0.15, +0.15) cycles of the nearest integer. After ambiguity resolution, the 2-hour static PPP accuracy improves from (0.66, 1.42, 1.55) cm to (0.38, 0.39, 1.39) cm for the north, east, and up components, respectively.     

Method for real-time self-calibrating GLONASS code inter-frequency bias and improvements on single point positioning

Utilization of frequency-division multiple access (FDMA) leads to GLONASS pseudorange and carrier phase observations suffering from variable levels inter-frequency bias (IFB). The bias related with carrier phase can be absorbed by ambiguities. However, the unequal code inter-frequency bias (cIFB) will degrade the accuracy of pseudorange observations, which will affect positioning accuracy and convergence of precise point positioning (PPP) when including GLONASS satellites. Based on observations made on un-differenced (UD) ionospheric-free combinations, GLONASS cIFB parameters are estimated as a constant to achieve GLONASS cIFB real-time self-calibration on a single station. A total of 23 stations, with different manufacturing backgrounds, are used to analyze the characteristics of GLONASS cIFB and its relationship with variable receiver hardware. The results show that there is an obvious common trend in cIFBs estimated using broadcast ephemeris for all of the different manufacturers, and there are unequal GLONASS inter-satellite cIFB that match brand manufacture. In addition, a particularly good consistency is found between self-calibrated receiver-dependent GLONASS cIFB and the IFB products of the German Research Centre for Geosciences (GFZ). Via a comparative experiment, it is also found that the algorithm of cIFB real-time self-calibration not only corrects receiver-dependent cIFB, but can moreover eliminate satellite-dependent cIFB, providing more stable results and further improving global navigation satellite system (GNSS) point positioning accuracy. The root mean square (RMS) improvements of single GLONASS standard point positioning (SPP) reach up to 54.18 and 53.80% in horizontal and vertical direction, respectively. The study’s GLONASS cIFB self-estimation can realize good self-consistency between cIFB and stations, working to further promote convergence efficiency relative to GPS?+?GLONASS PPP. An average improvement percentage of 19.03% is observed, realizing a near-consistent accuracy with GPS?+?GLONASS fusion PPP.     

Understanding the characteristic of GLONASS inter-frequency clock bias using both FDMA and CDMA signals

GPS Solutions - High-frequency global navigation satellite system (GNSS) observations are of great significance for structural health monitoring. At present, most studies on high-frequency GNSS...     

一种UKF与PF相结合的相位解缠算法

针对干涉相位图解缠问题,该文提出一种基于掩膜图的无损卡尔曼滤波与粒子滤波相结合的相位解缠算法,并结合基于AMPM局部相位梯度估计技术快速和精确地从复干涉相位图中获取相位梯度等信息以及最大堆排序算法从高质量像元到低质量像元的路径快速地搜索最佳待解缠像元,减少在路径跟踪过程中所消耗的时间。该文算法不仅可以高效、精确地在相位解缠的同时进行干涉图滤波,降低前置预滤波器的难度与复杂度,甚至可以在解缠高信噪比干涉相位图时免去预滤波的过程,而且在一定程度上能将相位解缠误差限制在低质量像元区域,减少误差传递效应,提高相位解缠的精度,在实测数据和模拟数据实验结果中表明:比现有的传统算法如枝切法等InSAR干涉相位解缠算法有更高的精度和稳健性。     

顾及模型误差的卡尔曼滤波相位解缠

本文提出一种顾及模型误差的卡尔曼滤波相位解缠算法,该算法在卡尔曼滤波的状态空间模型中引入一与误差因素有关的控制变量,对相位误差进行补偿,通过在解缠过程中将卡尔曼滤波增益限制在一定范围内,把误差阻遏在相当小的区域,最后对解缠相位进行卡尔曼滤波平滑操作,减少了误差的传播.分别采用仿真数据和真实InSAR数据进行实验,并与原卡尔曼滤波相位解缠结果进行对比分析,验证了本文方法的有效性.     

Simultaneous estimation of GLONASS pseudorange inter-frequency biases in precise point positioning using undifferenced and uncombined observations

GLONASS precise point positioning (PPP) performance is affected by the inter-frequency biases (IFBs) due to the application of frequency division multiple access technique. In this contribution, the impact of GLONASS pseudorange IFBs on convergence performance and positioning accuracy of GLONASS-only and GPS + GLONASS PPP based on undifferenced and uncombined observation models is investigated. Through a re-parameterization process, the following four pseudorange IFB handling schemes were proposed: neglecting IFBs, modeling IFBs as a linear or quadratic polynomial function of frequency number, and estimating IFBs for each GLONASS satellite. One week of GNSS observation data from 132 International GNSS Service stations was selected to investigate the contribution of simultaneous estimation of GLONASS pseudorange IFBs on GLONASS-only and combined GPS + GLONASS PPP in both static and kinematic modes. The results show that considering IFBs can speed up the convergence of PPP using GLONASS observations by more than 20%. Apart from GLONASS-only kinematic PPP, the positioning accuracy of GLONASS-only and GPS + GLONASS PPP is comparable among the four schemes. Overall, the scheme of estimating IFBs for each GLONASS satellite outperforms the other schemes in both convergence time reduction and positioning accuracy improvement, which indicates that the GLONASS IFBs may not strictly obey a linear or quadratic function relationship with the frequency number.     

基于状态矩阵卡尔曼滤波的姿态估计算法研究

设计一种组合GPS／速率陀螺定姿系统。系统以方向余弦矩阵表示姿态,建立GPS／速率陀螺组合状态模型和观测模型。结合kalman滤波算法,提出一种状态矩阵卡尔曼滤波（StateMatrixKalmanKilter,SMKF）姿态估计算法,并采用拉格朗日算法对姿态矩阵进行正交化约束。与传统的基于四元数的扩展卡尔曼滤波（EKF）算法相比,基于方向余弦矩阵的姿态系统状态方程与测量方程均为线性方程,无需线性化处理,对初始姿态误差更具有较好的鲁棒性。数值仿真表明,该方法具有精度高和稳定性强等优点。     

一种基于扩展卡尔曼滤波的多基线相位噪声抑制及展开方法

针对传统多基线干涉合成孔径雷达存在系统高度模糊数与缠绕相位解缠可靠性之间不可兼顾的矛盾,该文提出一种基于扩展卡尔曼滤波(EKF)的多基线SAR干涉相位展开方法。该方法利用全方位局部相位梯度联合估计技术直接从多幅复干涉图抽样谱中提取相位梯度信息,同时利用EKF强大的数据融合能力以信息融合的方式同时完成二维噪声抑制及相位展开,既有利于解决相位展开中的"坡度欠估计"问题,又避免了传统方法在相位展开之前须进行噪声滤波的不足。多基线模拟数据和单基线实测数据处理结果验证了方法的有效性。     

Fast estimation and analysis of the inter-frequency clock bias for Block IIF satellites

The inter-frequency bias of PRN25 was noticed by the scientific community and considered to be caused by thermal variations. The inter-frequency bias leads to an apparent inter-frequency clock bias (IFCB), which could be obtained using the difference of two ionosphere-free phase combinations (L1/L2 and L1/L5). We present an efficient approach derived from the epoch-differenced strategy for fast estimation of IFCBs for Block IIF satellites. For the analysis, data from 32 stations from the IGS network spanning 10 months (DOY 213, 2011–153, 2012) are processed. The processing times show that the epoch-differenced method is more efficient than the undifferenced one. In order to study the features of IFCB, a harmonic analysis is performed by using a FFT (fast Fourier transformation), and significant periodic variations with the periods of 12, 6 and 8 h are noticed. The fourth-order period is determined by comparing the performances of the model with different periods. After determination, a harmonics-based function of order 4 is used to model the IFCB, and the single-day amplitudes and phases are estimated for the 10 months from a least squares fit. Based on the estimated results, the characterization of IFCB is discussed. The algorithm is incorporated into the MGPSS software developed at SHAO (Shanghai Astronomical Observatory, Chinese Academy of Sciences) and used to monitor the IFCB variations of GPS and COMPASS systems in near real time.     

结合卡尔曼滤波的城市路段速度估计

本文以城市出租车为浮动车数据采集源,介绍了基于GPS数据的实时路段速度估计的基本方法。针对目标路段GPS数据样本量不足的情况,考虑邻近区域的路段速度、上周同日速度、前一时刻速度等与目标路段当前时刻速度等密切相关的变量,建立多元线性回归方程,利用卡尔曼滤波融合预测值和测量值,从而提高路段行驶速度的估计精度。选择广州市东风路作为测试实例,融合值比测量值误差降低9%,绝对相对误差变动系数减少4%,表明结合卡尔曼滤波技术的城市路段速度估计精度和稳定性均得到提高。     

卡尔曼滤波方法的BDS/GLONASSRTK定位算法

针对单系统RTK定位精度以及稳定性不足的问题,该文提出了BDS、GLONASS双系统联合RTK定位方法,通过对双系统进行时空基准统一,基于附加模糊度参数的卡尔曼滤波函数模型双系统RTK定位算法的研究,开发了BDS/GLONASS双系统RTK定位程序,对超短基线、短基线实测数据进行计算,并且与GPS系统结果进行比对。实验结果表明,BDS、GLONASS、BDS/GLONASS这3种模式定位精度虽稍逊于GPS,但也能够达到厘米级精度,从而提供高精度的定位服务。     

基于DEM的低相干区SAR干涉图卡尔曼滤波相位解缠算法

相位解缠是利用干涉合成孔径雷达(InSAR)进行DEM提取和微小地表形变测量的关键技术之一.常规的卡尔曼滤波相位解缠算法在地形平坦区域可以获得可靠的结果,但是在地形起伏较大的区域却容易产生误差的传递,致使其结果无法准确反演地表形变信息.为此,提出了一种基于DEM的SAR干涉图卡尔曼滤波相位解缠算法.该算法借助美国航天飞机测绘任务(SRTM)获得的DEM信息指导SAR干涉图解缠,以提高解缠的速度和精度.通过与常规卡尔曼滤波解缠算法的结果比较分析表明,利用SRTM DEM地形信息指导卡尔曼滤波相位解缠尤其能够提高低相干区域相位的解缠精度.     

单频RTK动态解算的卡尔曼滤波算法研究

本文针对单频RTK提出了一种快速动态定位卡尔曼滤波算法,该方法使用C码和L1观测值,用模型改正对流层干延迟,双差大气延迟分解为测站大气天顶延迟和投影函数,与流动站位置以及站间单差模糊度组成观测方程进行卡尔曼滤波,得到单差模糊度浮点解及方差阵,通过星间求差得到双差模糊度浮点解及方差阵,结合MLAMBDA方法实时动态确定模糊度。经实测数据和IGS站数据验证该算法具有较好定位结果。