GLONASS pseudorange inter-channel biases and their effects on combined GPS/GLONASS precise point positioning

Combined GPS/GLONASS precise point positioning (PPP) can obtain a more precise and reliable position than GPS PPP. However, because of frequency division multiple access, GLONASS carrier phase and pseudorange observations suffer from inter-channel biases (ICBs) which will influence the accuracy and convergence speed of combined GPS/GLONASS PPP. With clear understanding of the characteristics of carrier phase ICBs, we estimated undifferenced GLONASS pseudorange ICBs for 133 receivers from five manufacturers and analyzed their characteristics. In general, pseudorange ICBs corresponding to the same firmware have strong correlations. The ICB values of two receivers with the same firmware may be different because of different antenna types, and their differences are closely related to frequency. Pseudorange ICBs should be provided for each satellite to obtain more precise ICBs as the pseudorange ICBs may vary even on the same frequency. For the solutions of standard point positioning (SPP), after pseudorange ICB calibration, the mean root mean square (RMS) improvements of GLONASS SPP reach up to 57, 48, and 53 % for the East, North, and Up components, while combined GPS/GLONASS SPP reach up to 27, 17, and 23 %, respectively. The combined GPS/GLONASS PPP after pseudorange ICB calibration evidently improved the convergence speed, and the mean RMS of PPP improved by almost 50 % during the convergence period.     

Impact of GLONASS pseudorange inter-channel biases on satellite clock corrections

GLONASS carrier phase and pseudorange observations suffer from inter-channel biases (ICBs) because of frequency division multiple access (FDMA). Therefore, we analyze the effect of GLONASS pseudorange inter-channel biases on the GLONASS clock corrections. Different Analysis Centers (AC) eliminate the impact of GLONASS pseudorange ICBs in different ways. This leads to significant differences in the satellite and AC-specific offsets in the GLONASS clock corrections. Satellite and AC-specific offset differences are strongly correlated with frequency. Furthermore, the GLONASS pseudorange ICBs also leads to day-boundary jumps in the GLONASS clock corrections for the same analysis center between adjacent days. This in turn will influence the accuracy of the combined GPS/GLONASS precise point positioning (PPP) at the day-boundary. To solve these problems, a GNSS clock correction combination method based on the Kalman filter is proposed. During the combination, the AC-specific offsets and the satellite and AC-specific offsets can be estimated. The test results show the feasibility and effectiveness of the proposed clock combination method. The combined clock corrections can effectively weaken the influence of clock day-boundary jumps on combined GPS/GLONASS kinematic PPP. Furthermore, these combined clock corrections can improve the accuracy of the combined GPS/GLONASS static PPP single-day solutions when compared to the accuracy of each analysis center alone.     

GLONASS ambiguity resolution of mixed receiver types without external calibration

GLONASS processing from mixed receiver types is typically subject to unmodeled inter-frequency phase biases which prevent carrier phase ambiguity parameters from converging to integers. Receiver-dependent values have been proposed to mitigate the contribution of these biases, but are still subject to a number of issues, such as firmware updates. Recent studies have demonstrated that the origin of inter-frequency biases is a misalignment between phase and code observations, and could be calibrated to first order by manufacturers. In this contribution, a calibration-free method for GLONASS ambiguity resolution is presented in which ambiguities naturally converge to integers. A mandatory condition is that two GLONASS satellites with adjacent frequency numbers are observed simultaneously, although this condition can be relaxed once a fixed solution has been obtained. This approach then permits the integration of different receiver types and firmware versions into seamless processing.     

Group delay variations of GPS transmitting and receiving antennas

GPS code pseudorange measurements exhibit group delay variations at the transmitting and the receiving antenna. We calibrated C1 and P2 delay variations with respect to dual-frequency carrier phase observations and obtained nadir-dependent corrections for 32 satellites of the GPS constellation in early 2015 as well as elevation-dependent corrections for 13 receiving antenna models. The combined delay variations reach up to 1.0 m (3.3 ns) in the ionosphere-free linear combination for specific pairs of satellite and receiving antennas. Applying these corrections to the code measurements improves code/carrier single-frequency precise point positioning, ambiguity fixing based on the Melbourne–Wübbena linear combination, and determination of ionospheric total electron content. It also affects fractional cycle biases and differential code biases.     

Undifferenced ionospheric-free ambiguity resolution using GLONASS data from inhomogeneous stations

GLONASS frequency division multiple access signals render ambiguity resolution (AR) rather difficult because: (1) Different wavelengths are used by different satellites, and (2) pseudorange inter-frequency biases (IFBs) cannot be precisely modeled by means of a simple function. In this study, an AR approach based on the ionospheric-free combination with a wavelength of about 5.3 cm is assessed for GLONASS precise point positioning (PPP). This approach simplifies GLONASS AR because pseudorange IFBs do not matter, and PPP-AR can be enabled across inhomogeneous receivers. One month of GLONASS data from 165 European stations were processed for different network size and different durations of observation periods. We find that 89.9% of the fractional parts of ionospheric-free ambiguities agree well within ± 0.15 cycles for a small network (radius = 500 km), while 77.6% for a large network (radius = 2000 km). In case of the 3-hourly GLONASS-only static PPP solutions for the small network, reliable AR can be achieved where the number of fixed GLONASS ambiguities account for 97.6% within all candidate ambiguities. Meanwhile, the RMS of the east, north and up components with respect to daily solutions is improved from 1.0, 0.6, 1.2 cm to 0.4, 0.4, 1.1 cm, respectively. When GPS PPP-AR is carried out simultaneously, the positioning performance can be improved significantly such that the GLONASS ambiguity fixing rate rises from 74.4 to 95.4% in case of hourly solutions. Finally, we introduce ambiguity-fixed GLONASS orbits to re-attempt GLONASS PPP-AR in contrast to the above solutions with ambiguity-float orbits. We find that ambiguity-fixed orbits lead to clearly better agreement among ionospheric-free ambiguity fractional parts in case of the large network, that is 80.5% of fractional parts fall in ± 0.15 cycles in contrast to 74.6% for the ambiguity-float orbits. We conclude that highly efficient GLONASS ionospheric-free PPP-AR is achievable in case of a few hours of data when GPS PPP-AR is also accomplished, and ambiguity-fixed GLONASS orbits will contribute significantly to PPP-AR over wide areas.     

Assessment of PPP integer ambiguity resolution using GPS,GLONASS and BeiDou (IGSO,MEO) constellations

Although integer ambiguity resolution (IAR) can improve positioning accuracy considerably and shorten the convergence time of precise point positioning (PPP), it requires an initialization time of over 30 min. With the full operation of GLONASS globally and BDS in the Asia–Pacific region, it is necessary to assess the PPP–IAR performance by simultaneous fixing of GPS, GLONASS, and BDS ambiguities. This study proposed a GPS + GLONASS + BDS combined PPP–IAR strategy and processed PPP–IAR kinematically and statically using one week of data collected at 20 static stations. The undifferenced wide- and narrow-lane fractional cycle biases for GPS, GLONASS, and BDS were estimated using a regional network, and undifferenced PPP ambiguity resolution was performed to assess the contribution of multi-GNSSs. Generally, over 99% of a posteriori residuals of wide-lane ambiguities were within ±0.25 cycles for both GPS and BDS, while the value was 91.5% for GLONASS. Over 96% of narrow-lane residuals were within ±0.15 cycles for GPS, GLONASS, and BDS. For kinematic PPP with a 10-min observation time, only 16.2% of all cases could be fixed with GPS alone. However, adding GLONASS improved the percentage considerably to 75.9%, and it reached 90.0% when using GPS + GLONASS + BDS. Not all epochs could be fixed with a correct set of ambiguities; therefore, we defined the ratio of the number of epochs with correctly fixed ambiguities to the number of all fixed epochs as the correct fixing rate (CFR). Because partial ambiguity fixing was used, when more than five ambiguities were fixed correctly, we considered the epoch correctly fixed. For the small ratio criteria of 2.0, the CFR improved considerably from 51.7% for GPS alone, to 98.3% when using GPS + GLONASS + BDS combined solutions.     

基于小波变换的单频GPS快速精密定位整周模糊度的解算

对于GPS短基线,载波相位双差观测量已基本消除了卫星轨道误差、钟差、大气折射误差等系统偏差的影响,主要包含距离观测量信息及随机测量误差,其中测量误差是高频的测量噪声,小波变换可将GPS载波相位双差观测量中的观测噪声(高频部分)分解出来。本文利用Coiflets小波基函数对GPS快速定位的原始载波相位双差观测量进行5层分解,通过重构第5层低频系数获得去除噪声的"干净"的载波相位双差观测量,然后利用"干净"的双差观测量进行最小二乘参数估计,以减小测量噪声对GPS快速定位病态方程解的扰动。计算结果表明该方法能够显著提高GPS快速定位中模糊度浮点解的精度,仅利用几个观测历元的数据就可以准确地固定模糊度。     

基于车载移动测量的GNSS定位方法

针对车载移动测量需要高频高精度的动态差分定位解算的问题,文中介绍利用GPS、北斗、GLONASS三个卫星导航系统进行载波相位动态差分的解算方法。首先利用双频观测值组成双差宽巷观测方程,利用M-W组合求出较高精度的宽巷模糊度浮点解,然后对宽巷模糊度进行搜索固定;接着对载波双差的基础模糊度进行搜索固定;最后将固定的模糊度代入载波相位双差观测方程,利用最小二乘求解测站坐标。文中使用该方法对车载GNSS实测数据进行解算,最终可得到厘米级别的定位结果。     

用遗传算法搜索GPS单频单历元整周模糊度

介绍了短基线利用单频单历元双差载波相位定位时模糊度固定的基本理论，探讨了利用遗传算法快速搜索GPS单频单历元整周模糊度的一些理论和实现的方法．提出了用改进的正则化方法改善浮动解来提高搜索成功率的新思路。算例分析表明，在一定的条件下．应用遗传算法搜索整周模糊度成功率高、稳键性较好。     

An approach to GLONASS ambiguity resolution

 When processing global navigation satellite system (GLONASS) carrier phases, the standard double-differencing (DD) procedure cannot cancel receiver clock terms in the DD phase measurement equations due to the multiple frequencies of the carrier phases. Consequently, a receiver clock parameter has to be set up in the measurement equations in addition to baseline components and DD ambiguities. The resulting normal matrix unfortunately becomes singular. Methods to deal with this problem have been proposed in the literature. However, these methods rely on the use of pseudo-ranges. As pseudo-ranges are contaminated by multi-path and hardware delays, biases in these pseudo-ranges are significant, which may result in unreliable ambiguity resolution. A new approach is addressed that is not sensitive to the biases in the pseudo-ranges. The proposed approach includes such steps as converting the carrier phases to their distances to cancel the receiver clock errors, and searching for the most likely single-differenced (SD) ambiguity. Based on the results from the theoretical investigation, a practical procedure for GLONASS ambiguity resolution is presented. The initial experimental results demonstrate that the proposed approach is useable in cases of GLONASS and combined global positioning system (GPS) and GLONASS positioning. Received: 19 August 1998 / Accepted: 12 November 1999     

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.     

Integrating GPS and GLONASS to accelerate convergence and initialization times of precise point positioning

The main challenge of dual-frequency precise point positioning (PPP) is that it requires about 30 min to obtain centimeter-level accuracy or to succeed in the first ambiguity-fixing. Currently, PPP is generally conducted with GPS only using the ionosphere-free combination. We adopt a single-differenced (SD) between-satellite PPP model to combine the GPS and GLONASS raw dual-frequency carrier phase measurements, in which the GPS satellite with the highest elevation is selected as the reference satellite to form the SD between-satellite measurements. We use a 7-day data set from 178 IGS stations to investigate the contribution of GLONASS observations to both ambiguity-float and ambiguity-fixed SD PPP solutions, in both kinematic and static modes. In ambiguity-fixed PPP, we only attempt to fix GPS integer ambiguities, leaving GLONASS ambiguities as float values. Numerous experimental results show that PPP with GLONASS and GPS requires much less convergence time than that of PPP with GPS alone. For ambiguity-float PPP, the average convergence time can be reduced by 45.9 % from 22.9 to 12.4 min in static mode and by 57.9 % from 40.6 to 17.7 min in kinematic mode, respectively. For ambiguity-fixed PPP, the average time to the first-fixed solution can be reduced by 27.4 % from 21.6 to 15.7 min in static mode and by 42.0 % from 34.4 to 20.0 min in kinematic mode, respectively. Experimental results also show that the less the GPS satellites are used in float PPP, the more significant is the reduction in convergence time when adding GLONASS observations. In addition, on average, more than 4 GLONASS satellites can be observed for most 2-h observation sessions. Nearly, the same improvement in convergence time reduction is achieved for those observations.     

Examining the C1-P1 Pseudorange Bias

Use of GPS tracking data from different dual-frequency receiver types (cross-correlating vs. codeless) has revealed satellite-dependent biases in pseudorange observables P1 (Y-code) and C1 (C/A, Clear Acquisition code). These biases can have a direct effect on clock estimates, carrier phase bias fixing, and other parameters estimated in GPS data processing. A set of satellite-specific compensatory pseudorange offsets is calculated, and each is applied to a wee of daily global network analyses in which satlellite, receiver, atmospheric, and Earth rotation parameters are estimated. Results from these analyses are then compared to those from corresponding baseline cases in which no biases were applied. There is also some evidence that suggests that the pseudorange biases differ even among codeless receiver models. Hence, a second set of offsets is computed on a different basis, and compared with the baseline model in a similar manner. A preliminary examination of C1-P1 variations over time is presented. Finally, recommendations are made for the use of the calculated offsets, and consideration is given to a future dissemination of updates to these values as necessary. ? 2001 John Wiley & Sons, Inc.     

TJS-2 geostationary satellite orbit determination using onboard GPS measurements

This study analyzes the quality of onboard data of tracking signals from GPS satellites on the far side of the earth and determines the orbit of the geostationary satellite using code and carrier phase observations with 30-h and 3-day orbit arc length. According to the analysis results, the onboard receiver can track 6–8 GPS satellites, and the minimum and maximum carrier to noise spectral densities were 24 and 45 dB-Hz, respectively. For a GPS receiver on a high-altitude platform above the navigation constellations, the blocking of the earth and a weak signal strength usually cause a piece-wise GPS signal tracking and an increase in the number of ambiguity parameters. Individual GPS satellites may be continuously tracked for as little as several minutes and as long as 3 h. Moreover, considering the negative sign of elevation angles reflects the fact that GPS satellites are tracked below the receiver in the study. GPS satellites appear mainly in the elevation angle range of ??53° to ??83°, and dilution of precision values could reach ten or one hundred and more. Also, it is observed that when a signal suffers from atmospheric refraction, other GPS signals tracked simultaneously by the receiver experience strong systematic errors in the code observations. Based on single-frequency code and carrier phase measurements, the mean 3D root mean square (RMS) value of the overlap comparisons between 30-h orbit determination arcs is 2.14 m. However, we found that there were also some biases in the carrier phase residuals, which contributed to poor orbit accuracy. To eliminate the effects of the biases, we established a correction sequence for each GPS satellite. After corrections, the mean 3D RMS was reduced to 0.99 m, representing a 53% improvement.     

Multi-GNSS precise point positioning (MGPPP) using raw observations

A joint-processing model for multi-GNSS (GPS, GLONASS, BDS and GALILEO) precise point positioning (PPP) is proposed, in which raw code and phase observations are used. In the proposed model, inter-system biases (ISBs) and GLONASS code inter-frequency biases (IFBs) are carefully considered, among which GLONASS code IFBs are modeled as a linear function of frequency numbers. To get the full rank function model, the unknowns are re-parameterized and the estimable slant ionospheric delays and ISBs/IFBs are derived and estimated simultaneously. One month of data in April, 2015 from 32 stations of the International GNSS Service (IGS) Multi-GNSS Experiment (MGEX) tracking network have been used to validate the proposed model. Preliminary results show that RMS values of the positioning errors (with respect to external double-difference solutions) for static/kinematic solutions (four systems) are 6.2 mm/2.1 cm (north), 6.0 mm/2.2 cm (east) and 9.3 mm/4.9 cm (up). One-day stabilities of the estimated ISBs described by STD values are 0.36 and 0.38 ns, for GLONASS and BDS, respectively. Significant ISB jumps are identified between adjacent days for all stations, which are caused by the different satellite clock datums in different days and for different systems. Unlike ISBs, the estimated GLONASS code IFBs are quite stable for all stations, with an average STD of 0.04 ns over a month. Single-difference experiment of short baseline shows that PPP ionospheric delays are more precise than traditional leveling ionospheric delays.     

Characterization of between-receiver GPS-Galileo inter-system biases and their effect on mixed ambiguity resolution

The Global Positioning System (GPS) and Galileo will transmit signals on similar frequencies, that is, the L1–E1 and L5–E5a frequencies. This will be beneficial for mixed GPS and Galileo applications in which the integer carrier phase ambiguities need to be resolved, in order to estimate the positioning unknowns with centimeter accuracy or better. In this contribution, we derive the mixed GPS + Galileo model that is based on “inter-system” double differencing, that is, differencing the Galileo phase and code observations relative to those corresponding to the reference or pivot satellite of GPS. As a consequence of this, additional between-receiver inter-system bias (ISB) parameters need to be solved as well for both phase and code data. We investigate the size and variability of these between-receiver ISBs, estimated from L1 and L5 observations of GPS, as well as E1 and E5a observations of the two experimental Galileo In-Orbit Validation Element (GIOVE) satellites. The data were collected using high-grade multi-GNSS receivers of different manufacturers for several zero- and short-baseline setups in Australia and the USA. From this analysis, it follows that differential ISBs are only significant for receivers of different types and manufacturers; for baselines formed by identical receiver types, no differential ISBs have shown up; thus, implying that the GPS and GIOVE data are then fully interoperable. Fortunately, in case of different receiver types, our analysis also indicates that the phase and code ISBs may be calibrated, since their estimates, based on several datasets separated in time, are shown to be very stable. When the single-frequency (E1) GIOVE phase and code data of different receiver types are a priori corrected for the differential ISBs, the short-baseline instantaneous ambiguity success rate increases significantly and becomes comparable to the success rate of mixed GPS + GIOVE ambiguity resolution based on identical receiver types.     

A two-step ionospheric modeling algorithm considering the impact of GLONASS pseudo-range inter-channel biases

The Global Navigation Satellite System presents a plausible and cost-effective way of computing the total electron content (TEC). But TEC estimated value could be seriously affected by the differential code biases (DCB) of frequency-dependent satellites and receivers. Unlike GPS and other satellite systems, GLONASS adopts a frequency-division multiplexing access mode to distinguish different satellites. This strategy leads to different wavelengths and inter-frequency biases (IFBs) for both pseudo-range and carrier phase observations, whose impacts are rarely considered in ionospheric modeling. We obtained observations from four groups of co-stations to analyze the characteristics of the GLONASS receiver P1P2 pseudo-range IFB with a double-difference method. The results showed that the GLONASS P1P2 pseudo-range IFB remained stable for a period of time and could catch up to several meters, which cannot be absorbed by the receiver DCB during ionospheric modeling. Given the characteristics of the GLONASS P1P2 pseudo-range IFB, we proposed a two-step ionosphere modeling method with the priori IFB information. The experimental analysis showed that the new algorithm can effectively eliminate the adverse effects on ionospheric model and hardware delay parameters estimation in different space environments. During high solar activity period, compared to the traditional GPS + GLONASS modeling algorithm, the absolute average deviation of TEC decreased from 2.17 to 2.07 TECu (TEC unit); simultaneously, the average RMS of GPS satellite DCB decreased from 0.225 to 0.219 ns, and the average deviation of GLONASS satellite DCB decreased from 0.253 to 0.113 ns with a great improvement in over 55%.     

Rapid PPP ambiguity resolution using GPS+GLONASS observations

Integer ambiguity resolution (IAR) in precise point positioning (PPP) using GPS observations has been well studied. The main challenge remaining is that the first ambiguity fixing takes about 30 min. This paper presents improvements made using GPS+GLONASS observations, especially improvements in the initial fixing time and correct fixing rate compared with GPS-only solutions. As a result of the frequency division multiple access strategy of GLONASS, there are two obstacles to GLONASS PPP-IAR: first and most importantly, there is distinct code inter-frequency bias (IFB) between satellites, and second, simultaneously observed satellites have different wavelengths. To overcome the problem resulting from GLONASS code IFB, we used a network of homogeneous receivers for GLONASS wide-lane fractional cycle bias (FCB) estimation and wide-lane ambiguity resolution. The integer satellite clock of the GPS and GLONASS was then estimated with the wide-lane FCB products. The effect of the different wavelengths on FCB estimation and PPP-IAR is discussed in detail. We used a 21-day data set of 67 stations, where data from 26 stations were processed to generate satellite wide-lane FCBs and integer clocks and the other 41 stations were selected as users to perform PPP-IAR. We found that GLONASS FCB estimates are qualitatively similar to GPS FCB estimates. Generally, 98.8% of a posteriori residuals of wide-lane ambiguities are within \(\pm 0.25\) cycles for GPS, and 96.6% for GLONASS. Meanwhile, 94.5 and 94.4% of narrow-lane residuals are within 0.1 cycles for GPS and GLONASS, respectively. For a critical value of 2.0, the correct fixing rate for kinematic PPP is only 75.2% for GPS alone and as large as 98.8% for GPS+GLONASS. The fixing percentage for GPS alone is only 11.70 and 46.80% within 5 and 10 min, respectively, and improves to 73.71 and 95.83% when adding GLONASS. Adding GLONASS thus improves the fixing percentage significantly for a short time span. We also used global ionosphere maps (GIMs) to assist the wide-lane carrier-phase combination to directly fix the wide-lane ambiguity. Employing this method, the effect of the code IFB is eliminated and numerical results show that GLONASS FCB estimation can be performed across heterogeneous receivers. However, because of the relatively low accuracy of GIMs, the fixing percentage of GIM-aided GPS+GLONASS PPP ambiguity resolution is very low. We expect better GIM accuracy to enable rapid GPS+GLONASS PPP-IAR with heterogeneous receivers.     

谷歌Nexus 9智能终端原始GNSS观测值的质量分析

从信噪比、伪距残差、相位残差等方面对开阔环境下的静态谷歌Nexus 9智能平板终端的原始全球导航卫星系统（Global Navigation Satellite System,GNSS）观测数据质量进行了分析评估,结果表明,Nexus 9平板的全球定位系统（Global Positioning System,GPS）、GLONASS观测值的信噪比比测量型接收机低10 dBHz左右;伪距精度分别为5.43 m、11.39 m,相位精度分别为4.44 mm、4.99 mm;相对于高度角来说,信噪比与伪距残差的相关性更强,更能反映观测数据的质量。在此基础上给出了信噪比定权的随机模型,并进行了开阔环境下的伪距单点定位测试。实验结果表明,基于信噪比定权的单点定位平面精度为2.74 m,高程精度为4.56m,比高度角定权精度提高了约26%。     

Performance analysis of integrated GPS/GLONASS carrier phase-based positioning

Due to the different signal frequencies for the GLONASS satellites, the commonly-used double-differencing procedure for carrier phase data processing can not be implemented in its straightforward form, as in the case of GPS. In this paper a novel data processing strategy, involving a three-step procedure, for integrated GPS/GLONASS positioning is proposed. The first is pseudo-range-based positioning, that uses double-differenced (DD) GPS pseudo-range and single-differenced (SD) GLONASS pseudo-range measurements to derive the initial position and receiver clock bias. The second is forming DD measurements (expressed in cycles) in order to estimate the ambiguities, by using the receiver clock bias estimated in the above step. The third is to form DD measurements (expressed in metric units) with the unknown SD integer ambiguity for the GLONASS reference satellite as the only parameter (which is constant before a cycle slip occurs for this satellite). A real-time stochastic model estimated by residual series over previous epochs is proposed for integrated GPS/GLONASS carrier phase and pseudo-range data processing. Other associated issues, such as cycle slip detection, validation criteria and adaptive procedure(s) for ambiguity resolution, is also discussed. The performance of this data processing strategy will be demonstrated through case study examples of rapid static positioning and kinematic positioning. From four experiments carried out to date, the results indicate that rapid static positioning requires 1 minute of single frequency GPS/GLONASS data for 100% positioning success rate. The single epoch positioning solution for kinematic positioning can achieve 94.6% success rate over short baselines (<6 km).