Adaptive filtering applications to satellite navigation

PhDDifferential Global Navigation Satellite Systems employ the extended Kalman filter to estimate the reference position error. High accuracy integrated navigation systems have the ability to mix traditional inertial sensor outputs with navigation satellite based position information and can be used to develop high accuracy landing systems for aircraft. This thesis considers a host of estimation problems associated with aircraft navigation systems that currently rely on the extended Kalman filter and proposes to use a nonlinear estimation algorithm, the unscented Kalman filter (UKF) that does not rely on Jacobian linearisation. The objective is to develop high accuracy positioning algorithms to facilitate the use of GNSS or DGNSS for aircraft landing. Firstly, the position error in a typical satellite navigation problem depends on the accuracy of the orbital ephemeris. The thesis presents results for the prediction of the orbital ephemeris from a customised navigation satellite receiver's data message. The SDP4/SDP8 algorithms and suitable noise models are used to establish the measured data. Secondly, the differential station common mode position error not including the contribution due to errors in the ephemeris is usually estimated by employing an EKF. The thesis then considers the application of the UKF to the mixing problem, so as to facilitate the mixing of measurements made by either a GNSS or a DGNSS and a variety of low cost or high-precision INS sensors. Precise, adaptive UKFs and a suitable nonlinear propagation method are used to estimate the orbit ephemeris and the differential position and the navigation filter mixing errors. The results indicate the method is particularly suitable for estimating the orbit ephemeris of navigation satellites and the differential position and navigation filter mixing errors, thus facilitating interoperable DGNSS operation for aircraft landing

Ionospheric path delay models for spaceborne GPS receivers flying in formation with large baselines

GPS relative navigation filters could benefit notably from an accurate modeling of the ionospheric delays, especially over large baselines (>100 km) where double difference delays can be higher than several carrier wavelengths. This paper analyzes the capability of ionospheric path delay models proposed for spaceborne GPS receivers in predicting both zero-difference and double difference ionospheric delays. We specifically refer to relatively simple ionospheric models, which are suitable for real-time filtering schemes. Specifically, two ionospheric delay models are evaluated, one assuming an isotropic electron density and the other considering the effect on the electron density of the Sun aspect angle. The prediction capability of these models is investigated by comparing predicted ionospheric delays with measured ones on real flight data from the Gravity Recovery and Climate Experiment mission, in which two satellites fly separated of more than 200 km. Results demonstrate that both models exhibit a correlation in the excess of 80% between predicted and measured double-difference ionospheric delays. Despite its higher simplicity, the isotropic model performs better than the model including the Sun effect, being able to predict double differenced delays with accuracy smaller than the carrier wavelength in most cases. The model is thus fit for supporting integer ambiguity fixing in real-time filters for relative navigation over large baselines. Concerning zero-difference ionospheric delays, results demonstrate that delays predicted by the isotropic model are highly correlated (around 90%) with those estimated using GPS measurements. However, the difference between predicted and measured delays has a root mean square error in the excess of 30 cm. Thus, the zero-difference ionospheric delays model is not likely to be an alternative to methods exploiting carrier-phase observables for cancelling out the ionosphere contribution in single-frequency absolute navigation filters

Effectiveness of observation-domain sidereal filtering for GPS precise point positioning

Sidereal filtering is a technique used to reduce errors caused by multipath in the positioning of static receivers via the Global Positioning System (GPS). It relies upon the receiver and its surrounding environment remaining static from one day to the next and takes advantage of the approximately sidereal repeat time of the GPS constellation geometry. The repeating multipath error can thus be identified, usually in the position domain, and largely removed from the following day. We describe an observation-domain sidereal filter algorithm that operates on undifferenced ionospheric-free GPS carrier phase measurements to reduce errors caused by multipath. It is applied in the context of high-rate (1 Hz) precise point positioning of a static receiver. An observation-domain sidereal filter (ODSF) is able to account for the slightly different repeat times of each GPS satellite, unlike a position-domain sidereal filter (PDSF), and can hence be more effective at reducing high-frequency multipath error. Using 8-h long datasets of GPS measurements from two different receivers with different antenna types and contrasting environments, the ODSF algorithm is shown overall to yield a position time series 5–10 % more stable, in terms of Allan deviation, than a PDSF over nearly all time intervals below about 200 s in length. This may be particularly useful for earthquake and tsunami early warning systems where the accurate measurement of small displacements of the ground over the period of just a few minutes is crucial. However, the sidereal filters are also applied to a third dataset during which two short episodes of particularly high-frequency multipath error were identified. These two periods are analyzed in detail and illustrate the limitations of using sidereal filters with important implications for other methods of correcting for multipath at the observation level

Attitude determination of GPS satellite vehicles

There is an increasing demand for navigation systems that has led to rapid development of Global Positioning System (GPS) across industries. Apart from position and speed, precise attitude measurements are needed for many GPS applications. This thesis presents techniques for attitude determination of satellite vehicles in both real-time and stand-alone positioning applications. The GPS system used is a differential GPS system that estimates the body frame baselines using at least four receivers. The attitude information is obtained using these baselines and projecting them onto a local level frame. Integer ambiguity is a major constraint in attitude determination. Least Squares Ambiguity Deco-relation method is implemented to fix the ambiguities prior to baseline estimation. Estimation techniques such as Least Squares and Kalman Filter are implemented for deriving baseline components. Finally, this system will compute body frame coordinates and attitude components in reference to the desired coordinate frames.Engineering Technology, Department o

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

Višerazinska procjena faznih i kodnih pomaka satelitskog signala

Precise point positioning with satellite navigation signals requires knowledge of satellite code and phase biases. In this paper, a new multi-stage method is proposed for estimating of these biases using measurements from a geodetic network. Themethod first subtracts all available a priori knowledge on orbits, satellite clocks andmultipath from the measurements to reduce their dynamics. Secondly, satellite phase biases, ionospheric delays, carrier phase integer ambiguities and the geometry combining all non-dispersive parameters are jointly estimated in a Kalman filter. Finally, the a posteriori geometry estimates are refined in a second Kalman filter for the computation of orbital errors, code biases and tropospheric delays. As the first Kalman filter introduces time correlation, a generalized Kalman filter for colored measurement noise is applied in the second stage. The proposed algorithm is applied to dual frequency GPS measurements from a local geodetic network in Germany. A remarkable bias stability with variations of less than 3 cm over 4 hours is observed.Precizno odre.ivanje položaja uporabom satelitske navigacije zahtjeva poznavanje satelitskog koda te fazna mjerenja. U ovom radu predložena je nova metoda za procjenu faznih pomaka signala uporabom rezultata mjerenja iz geodetske mreže. U prvom koraku iz mjerenja se izuzimaju poznati podaci o orbitama, satelitskim satovima i višestrukim putevima, kako bi se smanjila njihova dinamika. U drugom se koraku uporabom Kalmanovog filtra procjenjuju fazni pomaci, ionosferska kašnjenja, neodre.enost broja valnih duljina nosioca i geometrija koja uključuje sve nedisperzivne parametre. Konačno, odre.uje se korigirana geometrija u drugom Kalmanovom filtru radi proračuna orbitalnih pogrešaka, pogrešaka koda i troposferskog kašnjenja. S obzirom na to da prvi Kalmanov filtar unosi vremensku korelaciju, opći Kalmanov filtar primjenjuje se u drugom koraku. Predloženi algoritam primijenjen je u dvofrekvencijskim GPS-mjerenjima u lokalnoj geodetskoj mreži u Njemačkoj. Postignuta je visoka stabilnost rezultata uz varijacije manje od 3 cm tijekom 4 sata

Robust Positioning in the Presence of Multipath and NLOS GNSS Signals

GNSS signals can be blocked and reflected by nearby objects, such as buildings, walls, and vehicles. They can also be reflected by the ground and by water. These effects are the dominant source of GNSS positioning errors in dense urban environments, though they can have an impact almost anywhere. Non- line-of-sight (NLOS) reception occurs when the direct path from the transmitter to the receiver is blocked and signals are received only via a reflected path. Multipath interference occurs, as the name suggests, when a signal is received via multiple paths. This can be via the direct path and one or more reflected paths, or it can be via multiple reflected paths. As their error characteristics are different, NLOS and multipath interference typically require different mitigation techniques, though some techniques are applicable to both. Antenna design and advanced receiver signal processing techniques can substantially reduce multipath errors. Unless an antenna array is used, NLOS reception has to be detected using the receiver's ranging and carrier-power-to-noise-density ratio (C/N0) measurements and mitigated within the positioning algorithm. Some NLOS mitigation techniques can also be used to combat severe multipath interference. Multipath interference, but not NLOS reception, can also be mitigated by comparing or combining code and carrier measurements, comparing ranging and C/N0 measurements from signals on different frequencies, and analyzing the time evolution of the ranging and C/N0 measurements

Carrier-phase based real-time static and kinematic precise point positioning Using GPS and GALILEO

Over the last few years, there has been a rising demand for sub-metre accuracy (and higher) for navigation and surveying using signals from Global Navigation Satellite Systems (GNSS). To meet this rising demand, many precise positioning techniques and algorithms using the carrier-phase observable have been developed. Currently, high accuracy Real-Time Kinematic (RTK) positioning is possible using relative or differential techniques which require one GNSS user receiver and at least one other as the reference (known) station within a certain distance from the user. Unlike these conventional differential positioning techniques, Precise Point Positioning (PPP) is based on processing carrier phase observations from only one GNSS receiver. This is more cost-effective as it removes the need for reference receivers and therefore, is not limited by baseline length. However, errors mitigated by ‘differencing’ in conventional methods must be modelled accurately and reliably for PPP. This thesis develops a PPP software platform in Matlab code and uses it to investigate the state-of-the-art PPP algorithms and develop enhancements. Specifically, it is well documented that conventional PPP algorithms suffer from long convergence periods ranging from thirty minutes (for static users) to hours (for dynamic users). Therefore, to achieve fast convergence, two approaches are developed in this thesis. Firstly, a combination of the state-of-the-art GNSS error models and new algorithms for measurement weighting, management of receiver clock jumps and assignment of a dynamic covariance factor, are exploited. Secondly, based on the results of the analysis of the quantitative relationships between the PPP convergence and each of the residual measurement noise level and satellite geometry, a strategy for the selection of satellites (GPS and GALILEO) for PPP is developed and exploited. Tests using 24 hours of real data show that the two developments above contribute to the realisation of static PPP positioning accuracies of 40 cm (3D, 100%) within a convergence time of 20 minutes. Furthermore, based on simulated data, the same accuracy is achieved in kinematic mode but within a convergence time of one hour. These levels of performance represent significant improvements over the state-of-the-art (i.e. convergence time of twenty minutes instead of thirty for static users and one hour instead of hours for dynamic users). The potential of the use of multiple frequencies from modernised GPS and GALILEO on float ambiguity PPP is demonstrated with simulated data, and shown to have the potential to offer significant improvement in the availability of PPP in difficult user environments such as urban areas. Finally, the thesis addresses the potential application of PPP for mission (e.g. safety critical) applications and the need for integrity monitoring. An existing Carrier-phase Receiver Autonomous Integrity Monitoring (CRAIM) algorithm is implemented and shown to have the potential to protect PPP users against abnormally large errors

Satellite Formation-Flying and Rendezvous

GNSS has come to play an increasingly important role in satellite formation-flying and rendezvous applications. In the last decades, the use of GNSS measurements has provided the primary technique for determining the relative position of cooperative co-orbiting satellites in low Earth orbit