Reliability control of single-epoch RTK ambiguity resolution

GPS Solutions - Reliability is an important indicator of GNSS performance, especially for the safety-critical applications. Carrier phase-based GNSS positioning can achieve high precision, but its...     

Improved network-based single-epoch ambiguity resolution using centralized GNSS network processing

Network real-time kinematic (NRTK) positioning is today’s industry standard for high-precision applications. Once network ambiguities are fixed, the network engine processes simultaneous observations from a number of continuously operating reference stations to compute corrections for users operating within the network area. Users are treated as passive nodes of the network. However, if two-way communication is available, then users could transmit their observations to the central processing facility where the network can treat them as active nodes, densifying the existing network infrastructure. This multiple rover network (MRN) concept exploits the additional information provided by users in a GNSS network. One application is to use the shorter inter-receiver distances to improve the success rate of single-epoch ambiguity resolution. This is also the goal of the subset ambiguity resolution algorithm, which improves the single-epoch success rate by allowing a subset of ambiguities to be resolved. We present an enhanced processing strategy to complement centimeter-level single-epoch NRTK positioning. This approach combines a single-baseline and an MRN solution with the partial ambiguity resolution algorithm and is only possible for a centralized GNSS network architecture. The algorithm is tested against the standard network ambiguity resolution strategy of full-set ambiguity fixing with respect to the nearest reference station. A 24-h dataset from the Southern California Integrated GNSS network is used with a configuration of three reference stations and four users. The enhanced solution achieves a mean ambiguity resolution success rate of 83% over all four users and all epochs, compared to 32% for the conventional technique.     

一种GPS整周模糊度单历元解算方法

仅利用单历元的载波相位观测值进行整周模糊度解算,观测方程秩亏,给单历元模糊度解算带来很大困难.因此,本文提出一种单历元确定GPS整周模糊度的方法.利用单历元测码伪距观测值和双频载波相位观测值组成双差观测方程,根据方差矩阵对宽巷模糊度进行分组,采用基于LABMDA方法的逐步解算方法来确定双差相位观测值的宽巷模糊度.确定宽...     

GNSS ambiguity resolution with controllable failure rate for long baseline network RTK

Many large-scale GNSS CORS networks have been deployed around the world to support various commercial and scientific applications. To make use of these networks for real-time kinematic positioning services, one of the major challenges is the ambiguity resolution (AR) over long inter-station baselines in the presence of considerable atmosphere biases. Usually, the widelane ambiguities are fixed first, followed by the procedure of determination of the narrowlane ambiguity integers based on the ionosphere-free model in which the widelane integers are introduced as known quantities. This paper seeks to improve the AR performance over long baseline through efficient procedures for improved float solutions and ambiguity fixing. The contribution is threefold: (1) instead of using the ionosphere-free measurements, the absolute and/or relative ionospheric constraints are introduced in the ionosphere-constrained model to enhance the model strength, thus resulting in the better float solutions; (2) the realistic widelane ambiguity precision is estimated by capturing the multipath effects due to the observation complexity, leading to improvement of reliability of widelane AR; (3) for the narrowlane AR, the partial AR for a subset of ambiguities selected according to the successively increased elevation is applied. For fixing the scalar ambiguity, an error probability controllable rounding method is proposed. The established ionosphere-constrained model can be efficiently solved based on the sequential Kalman filter. It can be either reduced to some special models simply by adjusting the variances of ionospheric constraints, or extended with more parameters and constraints. The presented methodology is tested over seven baselines of around 100 km from USA CORS network. The results show that the new widelane AR scheme can obtain the 99.4 % successful fixing rate with 0.6 % failure rate; while the new rounding method of narrowlane AR can obtain the fix rate of 89 % with failure rate of 0.8 %. In summary, the AR reliability can be efficiently improved with rigorous controllable probability of incorrectly fixed ambiguities.     

基于部分模糊度解算的BDS/GPS组合RTK算法

GNSS多频率组合RTK定位逐步进入实际应用,存在模糊度维数增多、搜索空间增大,导致模糊度搜索运算量增大及模糊度固定效率低等问题。文中提出一种多星座部分模糊度解算算法,该算法综合考虑卫星高度角、模糊度固定成功率及Ratio值来筛选卫星进行模糊度解算。通过一组动态跑车实验分析表明:相比于全模糊度解算(FAR),部分模糊度解算(PAR)可以有效地提高BDS/GPS组合RTK的模糊度固定率,其模糊度固定率从79.9%(FAR)提高到99.1%(PAR),且PAR算法定位结果可靠性更高。     

A new method for three-carrier GNSS ambiguity resolution

A new method for resolving the carrier-phase integer ambiguity in Global Navigation Satellite Systems (GNSS) is presented: the MOdified Cholesky factorization for Ambiguity (MOCA) resolution. The characteristics and features of this method are described and results obtained using a software simulator and an emulator are presented to validate its efficiency. The results are then compared to those obtained using another existing method and good performance of the MOCA method in new GNSS systems is shown. Furthermore, the proposed method yields accurate results even when short time spans are used or when there are poor estimations of measurement error, making it immune to non-ideal conditions and ultimately a practical solution for real applications.     

利用迭代加权模糊度函数法的单历元模糊度固定

为提高全球导航卫星系统GNSS在复杂环境下的定向成功率,将迭代加权的思想与模糊度函数法（AFM）相结合,提出迭代加权模糊度函数法（IWAFW）。基于AFM算法,通过设计新的适应度函数,利用残差计算权重,实现对不同卫星信号权重的自动调节,并结合惯性传感器给出的姿态信息,压缩搜索空间,降低计算量。通过实测试验验证,在复杂环境中,相比于AFM和带基线长度约束的最小二乘模糊度去相关算法（CLAMBDA）,该算法能够有效提高模糊度固定成功率。     

信噪比的GNSS宽巷模糊度单历元固定算法

针对常规GNSS解算模糊度存在的问题,该文提出了一种新的GNSS宽巷模糊度单历元求解算法。利用单历元双频码伪距观测值和载波相位观测值得到双差宽巷模糊度浮点解,将所有浮点宽巷模糊度分别向上、向下取整建立模糊度搜索空间;将模糊度空间中的所有备选组合代入双差宽巷观测方程中进行最小二乘解算,其中单位权中误差最小的组合就是最优的宽巷模糊度组合;然后对最优组合进行正确性检验以确定宽巷模糊度。确定宽巷模糊度后,可以利用宽巷观测值和载波观测值求出基础模糊度整周解。实验表明,该文提出的模糊度固定方法具有较高的成功率和可靠性,静态数据中模糊度固定成功率达到98.84%,动态数据中模糊度固定成功率达到了99.60%。     

GNSS antenna array-aided CORS ambiguity resolution

Array-aided precise point positioning is a measurement concept that uses GNSS data, from multiple antennas in an array of known geometry, to realize improved GNSS parameter estimation proposed by Teunissen (IEEE Trans Signal Process 60:2870–2881, 2012). In this contribution, the benefits of array-aided CORS ambiguity resolution are explored. The mathematical model is formulated to show how the platform-array data can be reduced and how the variance matrix of the between-platform ambiguities can profit from the increased precision of the reduced platform data. The ambiguity resolution performance will be demonstrated for varying scenarios using simulation. We consider single-, dual- and triple-frequency scenarios of geometry-based and geometry-free models for different number of antennas and different standard deviations of the ionosphere-weighted constraints. The performances of both full and partial ambiguity resolution (PAR) are presented for these different scenarios. As the study shows, when full advantage is taken of the array antennas, both full and partial ambiguity resolution can be significantly improved, in some important cases even enabling instantaneous ambiguity resolution. PAR widelaning and its suboptimal character are hereby also illustrated.     

网络RTK流动站整周模糊度的单历元解算

传统网络RTK模糊度解算方法需要多个历元的观测数据,并且要进行周跳的探测和修复,影响模糊度解算的效率。本文提出一种单历元确定网络RTK双差整周模糊度的新方法。首先利用测码伪距观测值和载波相位观测值的单历元数据组成双差联合观测方程,采用改进LABMDA算法进行两步搜索确定GPS双差相位观测值的宽巷模糊度。确定宽巷模糊度后,再用宽巷模糊度值和载波相位观测值组成新的联合观测方程,大大改善了方程的状态,可以准确解算出GPS双差整周模糊度,显著提高了网络RTK整周模糊度固定的效率。     

Reliability of partial ambiguity fixing with multiple GNSS constellations

Reliable ambiguity resolution (AR) is essential to real-time kinematic (RTK) positioning and its applications, since incorrect ambiguity fixing can lead to largely biased positioning solutions. A partial ambiguity fixing technique is developed to improve the reliability of AR, involving partial ambiguity decorrelation (PAD) and partial ambiguity resolution (PAR). Decorrelation transformation could substantially amplify the biases in the phase measurements. The purpose of PAD is to find the optimum trade-off between decorrelation and worst-case bias amplification. The concept of PAR refers to the case where only a subset of the ambiguities can be fixed correctly to their integers in the integer least squares (ILS) estimation system at high success rates. As a result, RTK solutions can be derived from these integer-fixed phase measurements. This is meaningful provided that the number of reliably resolved phase measurements is sufficiently large for least-square estimation of RTK solutions as well. Considering the GPS constellation alone, partially fixed measurements are often insufficient for positioning. The AR reliability is usually characterised by the AR success rate. In this contribution, an AR validation decision matrix is firstly introduced to understand the impact of success rate. Moreover the AR risk probability is included into a more complete evaluation of the AR reliability. We use 16 ambiguity variance–covariance matrices with different levels of success rate to analyse the relation between success rate and AR risk probability. Next, the paper examines during the PAD process, how a bias in one measurement is propagated and amplified onto many others, leading to more than one wrong integer and to affect the success probability. Furthermore, the paper proposes a partial ambiguity fixing procedure with a predefined success rate criterion and ratio test in the ambiguity validation process. In this paper, the Galileo constellation data is tested with simulated observations. Numerical results from our experiment clearly demonstrate that only when the computed success rate is very high, the AR validation can provide decisions about the correctness of AR which are close to real world, with both low AR risk and false alarm probabilities. The results also indicate that the PAR procedure can automatically chose adequate number of ambiguities to fix at given high-success rate from the multiple constellations instead of fixing all the ambiguities. This is a benefit that multiple GNSS constellations can offer.     

Fast GNSS ambiguity resolution as an ill-posed problem

A linear observational equation system for real-time GNSS carrier phase ambiguity resolution (AR) is often severely ill-posed in the case of poor satellite geometry. An ill-posed system may result in unreliable or unsuccessful AR if no care is taken to mitigate this situation. In this paper, the GNSS AR model as an ill-posed problem is solved by regularizing its baseline and ambiguity parameters, respectively, with the threefold contributions: (i) The regularization parameter is reliably determined in context of minimizing mean square error of regularized solution where the covariance matrix of initial values of unknowns is used as an approximate smoothness term instead of the quadratic matrix of the true values of unknowns; (ii) The different models for computing initial values of unknowns are systematically discussed in order to address the potential schemes in real world applications; (iii) The superior performance of the regularized AR are demonstrated through the numerically random simulations as well as the real GPS experiments. The results show that the proposed regularization strategies can effectively mitigate the model’s ill-condition and improve the success AR probability of the observational system with a severely ill-posed problem.     

The ratio test for future GNSS ambiguity resolution

The performance of the popular ambiguity ratio test is analyzed. Based on experimental and simulated data, it is demonstrated that the current usage of the ratio test with fixed critical value is not sustainable in light of the enhanced variability that future global navigation satellite system (GNSS) ambiguity resolution will bring. As its replacement, the model-driven ratio test with fixed failure rate is proposed. The characteristics of this fixed-failure rate ratio test are described, and a performance analysis is given. The relation between its critical value and various GNSS model parameters is also studied. Finally, a procedure is presented for the creation of fixed failure rate look-up tables for the critical values of the ratio test.     

Reliable single-epoch ambiguity resolution for short baselines using combined GPS/BeiDou system

GNSS single-epoch real-time kinematic (RTK) positioning depends on correct ambiguity resolution. If the number of observed satellites in a single epoch is insufficient, which often happens with a standalone GNSS system, the ambiguity resolution is difficult to achieve. China’s BeiDou Navigation Satellite System has been providing continuous passive positioning, navigation and timing services since December 27, 2012, covering China and the surrounding area. This new system will increase the number of satellites in view and will have a significant effect on successful ambiguity resolution. Since the BeiDou system is similar to GPS, the procedure of data processing is easier than that for the Russian GLONASS system. We briefly introduce the time and the coordinate system of BeiDou and also the BeiDou satellite visibility in China, followed by the discussion on the combined GPS/BeiDou single-epoch algorithm. Experiments were conducted and are presented here, in which the GPS/BeiDou dual-frequency static data were collected in Wuhan with the baseline distance varying from 5 to 13 km, and processed in separate and combined modes. The results indicate that, compared to a standalone GPS or BeiDou system, the combined GNSS system can increase the successful ambiguity fixing rate for single epochs and can also improve the precision of short baselines determination.     

长距离网络RTK基准站间整周模糊度的快速解算

由于电离层延迟、对流层延迟等系统误差具有随测站间距离增加而相关性降低的特性,长距离情况下准确快速得到载波相位整周模糊度十分困难.因此文章提出了一种长距离网络RTK基准站间双差整周模糊度的快速解算方法,该方法利用M-W组合观测值进行双差宽巷整周模糊度的计算,结合无电离层组合观测值进行基准站间双差载波相位整周模糊度的确定,且不需线性化、不需解求方程组,各双差整周模糊度之间相互独立.最后通过实测数据进行算法验证,证明了该方法能够快速、可靠地解算长距离基准站间的双差整周模糊度.     

GNSS three carrier ambiguity resolution using ionosphere-reduced virtual signals

This paper presents a general modeling strategy for ambiguity resolution (AR) and position estimation (PE) using three or more phase-based ranging signals from a global navigation satellite system (GNSS). The proposed strategy will identify three best “virtual” signals to allow for more reliable AR under certain observational conditions characterized by ionospheric and tropospheric delay variability, level of phase noise and orbit accuracy. The selected virtual signals suffer from minimal or relatively low ionospheric effects, and thus are known as ionosphere-reduced virtual signals. As a result, the ionospheric parameters in the geometry-based observational models can be eliminated for long baselines, typically those of length tens to hundreds of kilometres. The proposed modeling comprises three major steps. Step 1 is the geometry-free determination of the extra-widelane (EWL) formed between the two closest L-band carrier measurements, directly from the two corresponding code measurements. Step 2 forms the second EWL signal and resolves the integer ambiguity with a geometry-based estimator alone or together with the first EWL. This is followed by a procedure to correct for the first-order ionospheric delay using the two ambiguity-fixed widelane (WL) signals derived from the integer-fixed EWL signals. Step 3 finds an independent narrow-lane (NL) signal, which is used together with a refined WL to resolve NL ambiguity with geometry-based integer estimation and search algorithms. As a result, the above two AR processes performed with WL/NL and EWL/WL signals respectively, either in sequence or in parallel, can support real time kinematic (RTK) positioning over baselines of tens to hundreds of kilometres, thus enabling centimetre-to-decimentre positioning at the local, regional and even global scales in the future.     

Generalized integer aperture estimation for partial GNSS ambiguity fixing

In satellite navigation, the key to high precision is to make use of the carrier-phase measurements. The periodicity of the carrier-phase, however, leads to integer ambiguities. Often, resolving the full set of ambiguities cannot be accomplished for a given reliability constraint. In that case, it can be useful to resolve a subset of ambiguities. The selection of the subset should be based not only on the stochastic system model but also on the actual measurements from the tracking loops. This paper presents a solution to the problem of joint subset selection and ambiguity resolution. The proposed method can be interpreted as a generalized version of the class of integer aperture estimators. Two specific realizations of this new class of estimators are presented, based on different acceptance tests. Their computation requires only a single tree search, and can be efficiently implemented, e.g., in the framework of the well-known LAMBDA method. Numerical simulations with double difference measurements based on Galileo E1 signals are used to evaluate the performance of the introduced estimation schemes under a given reliability constraint. The results show a clear gain of partial fixing in terms of the probability of correct ambiguity resolution, leading to improved baseline estimates.