A Numeric-Symbolic Solution of GNSS Phase Ambiguity

Solution of the Global Navigation Satellite Systems (GNSS) phase ambiguity is considered as a global quadratic mixed integer programming task, which can be transformed into a pure integer problem with a given digit of accuracy. In this paper, three alter-native algorithms are suggested. Two of them are based on local and global linearization via McCormic Envelopes, respectively. These algorithms can be effective in case of simple configuration and relatively modest number of satellites. The third method is a locally nonlinear, iterative algorithm handling the problem as {-1, 0, 1} programming and also lets compute the next best integer solution easily. However, it should keep in mind that the algorithm is a heuristic one, which does not guarantee to find the global integer optimum always exactly. The procedure is very powerful utilizing the ability of the numeric-symbolic abilities of a computer algebraic system, like Wolfram Mathematica and it is properly fast for minimum 4 satellites with normal configuration, which means the Geometric Dilution of Precision (GDOP) should be between 1 and 8. Wolfram Alpha and Wolfram Clouds Apps give possibility to run the suggested code even via cell phones. All of these algorithms are illustrated with numerical examples. The result of the third one was successfully compared with the LAMBDA method, in case of ten satellites sending signals on two carrier frequencies (L1 and L2) with weighting matrix used to weight the GNSS observation and computed as the inverse of the corresponding covariance matrix

A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning

A novel Bayesian technique for the joint estimation of real and integer parameters in a linear measurement model is presented. The integer parameters take values on a finite set, and the real ones are assumed to be a Gaussian random vector. The posterior distribution of these parameters is sequentially determined as new measurements are incorporated. This is a mixed distribution with a Gaussian continuous part and a discrete one. Estimators for the integer and real parameters are derived from this posterior distribution. A Maximum A Posteriori (MAP) estimator modified with the addition of a confidence threshold is used for the integer part and a Minimum Mean Squared Error (MMSE) is used for the real parameters. Two different cases are addressed: i) both real and integer parameters are time invariant and ii) the integer parameters are time invariant but the real ones are time varying. Our technique is applied to the GNSS carrier phase ambiguity resolution problem, that is key for high precision positioning applications. The good performance of the proposed technique is illustrated through simulations in different scenarios where different kind of measurements as well as different satellite visibility conditions are considered. Comparisons with state-of-the-art ambiguity solving algorithms confirm performance improvement. The new method is shown to be useful not only in the estimation stage but also for validating the estimates ensuring a predefined success rate through proper threshold selection

A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning

A novel Bayesian technique for the joint estimation of real and integer parameters in a linear measurement model is presented. The integer parameters take values on a finite set, and the real ones are assumed to be a Gaussian random vector. The posterior distribution of these parameters is sequentially determined as new measurements are incorporated. This is a mixed distribution with a Gaussian continuous part and a discrete one. Estimators for the integer and real parameters are derived from this posterior distribution. A Maximum A Posteriori (MAP) estimator modified with the addition of a confidence threshold is used for the integer part and a Minimum Mean Squared Error (MMSE) is used for the real parameters. Two different cases are addressed: i) both real and integer parameters are time invariant and ii) the integer parameters are time invariant but the real ones are time varying. Our technique is applied to the GNSS carrier phase ambiguity resolution problem, that is key for high precision positioning applications. The good performance of the proposed technique is illustrated through simulations in different scenarios where different kind of measurements as well as different satellite visibility conditions are considered. Comparisons with state-of-the-art ambiguity solving algorithms confirm performance improvement. The new method is shown to be useful not only in the estimation stage but also for validating the estimates ensuring a predefined success rate through proper threshold selection.Facultad de Ingenierí

A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning

A novel Bayesian technique for the joint estimation of real and integer parameters in a linear measurement model is presented. The integer parameters take values on a finite set, and the real ones are assumed to be a Gaussian random vector. The posterior distribution of these parameters is sequentially determined as new measurements are incorporated. This is a mixed distribution with a Gaussian continuous part and a discrete one. Estimators for the integer and real parameters are derived from this posterior distribution. A Maximum A Posteriori (MAP) estimator modified with the addition of a confidence threshold is used for the integer part and a Minimum Mean Squared Error (MMSE) is used for the real parameters. Two different cases are addressed: i) both real and integer parameters are time invariant and ii) the integer parameters are time invariant but the real ones are time varying. Our technique is applied to the GNSS carrier phase ambiguity resolution problem, that is key for high precision positioning applications. The good performance of the proposed technique is illustrated through simulations in different scenarios where different kind of measurements as well as different satellite visibility conditions are considered. Comparisons with state-of-the-art ambiguity solving algorithms confirm performance improvement. The new method is shown to be useful not only in the estimation stage but also for validating the estimates ensuring a predefined success rate through proper threshold selection.Facultad de Ingenierí

Improving Reliability and Assessing Performance of Global Navigation Satellite System Precise Point Positioning Ambiguity Resolution

Conventional Precise Point Positioning (PPP) has always required a relatively long initialization period (few tens of minutes at least) for the carrier-phase ambiguities to converge to constant values and for the solution to reach its optimal precision. The classical PPP convergence period is primarily caused by the estimation of the carrier-phase ambiguity from the relatively noisy pseudoranges and the estimation of atmospheric delay. If the underlying integer nature of the ambiguity is known, it can be resolved, thereby reducing the convergence time of conventional PPP. To recover the underlying integer nature of the carrier-phase ambiguities, different strategies for mitigating the satellite and receiver dependent equipment delays have been developed, and products made publicly available to enable ambiguity resolution without any baseline restrictions. There has been limited research within the scope of interoperability of the products, combining the products to improve reliability and assessment of ambiguity resolution within the scope of being an integrity indicator. This study seeks to develop strategies to enable each of these and examine their feasibility. The advantage of interoperability of the different PPP ambiguity resolution (PPP-AR) products would be to permit the PPP user to transform independently generated PPP-AR products to obtain multiple fixed solutions of comparable precision and accuracy. The ability to provide multiple solutions would increase the reliability of the solution for, e.g., real-time processing: if there were an outage in the generation of the PPP-AR products, the user could instantly switch streams to a different provider. The satellite clock combinations routinely produced within the International GNSS Service (IGS) currently disregard that analysis centers (ACs) provide products which enable ambiguity resolution. Users have been expected to choose either an IGS product which is a combined product from multiple ACs or select an individual AC solution which provides products that enable PPP-AR. The goal of the novel research presented was to develop and test a robust satellite clock combination preserving the integer nature of the carrier-phase ambiguities at the user end. mm-level differences were noted, which was expected as the strength lies mainly in its reliability and stable median performance and the combined product is better than or equivalent to any single ACs product in the combination process. As have been shown in relative positioning and PPP-AR, ambiguity resolution is critical for enabling cm-level positioning. However, what if specifications where at the few dm-level, such as 10 cm and 20 cm horizontal what role does ambiguity resolution play? The role of ambiguity resolution relies primarily on what are the user specifications. If the user specifications are at the few cm-level, ambiguity resolution is an asset as it improves convergence and solution stability. Whereas, if the users specification is at the few dm-level, ambiguity resolution offers limited improvement over the float solution. If the user has the resources to perform ambiguity resolution, even when the specifications are at the few dm-level, it should be utilized

GNSS precise point positioning :the enhancement with GLONASS

PhD ThesisPrecise Point Positioning (PPP) provides GNSS navigation using a stand-alone receiver with no base station. As a technique PPP suffers from long convergence times and quality degradation during periods of poo satellite visibility or geometry. Many applications require reliable realtime centimetre level positioning with worldwide coverage, and a short initialisation time. To achieve these goals, this thesis considers the use of GLONASS in conjunction with GPS in kinematic PPP. This increases the number of satellites visible to the receiver, improving the geometry of the visible satellite constellation. To assess the impact of using GLONASS with PPP, it was necessary to build a real time mode PPP program. pppncl was constructed using a combination of Fortran and Python to be capable of processing GNSS observations with precise satellite ephemeris data in the standardised RINEX and SP3 formats respectively. pppncl was validated in GPS mode using both staticsites and kinematic datasets.In GPS only mode,one sigma accuracy of 6.4mm and 13mm in the horizontal and vertical respectively for 24h static positioning was seen. Kinematic horizontal and vertical accuracies of 21mm and 33mm were demonstrated. pppncl was extended to assess the impact of using GLONASS observations in addi- tion to GPS instatic and kinematic PPP. Using ESA and Veripos Apex G2 satel- lite orbit and clock products,the average time until 10cm 1D static accuracy was achieved, over arange of globally distributed sites, was seen to reduce by up to 47%. Kinematic positioning was tested for different modes of transport using real world datasets. GPS/GLONAS SPPP reduced the convergence time to decimetre accuracy by up to a factor of three. Positioning was seen to be more robust in comparison to GPS only PPP, primarily due to cycle slips not being present on both satellite systems on the occasions when they occurred,and the reduced impact of undetected outliersEngineering and Physical Sciences Research Council, Verip os/Subsea