S-system theory applied to array-based GNSS ionospheric sensing

The GPS carrier-phase and code data have proven to be valuable sources of measuring the Earth’s ionospheric total electron content (TEC). With the development of new GNSSs with multi frequency data, many more ionosphere-sensing combinations of different precision can be formed as input of ionospheric modelling. We present the general way of interpreting such combinations through an application of S-system theory and address how their precision propagates into that of the unbiased TEC solution. Presenting the data relevant to TEC determination, we propose the usage of an array of GNSS antennas to improve the TEC precision and to expedite the rather long observational time-span required for high-precision TEC determination

A review of system integration and current integrity monitoring methods for positioning in intelligent transport systems

Applications of intelligent transportation systems are continuously increasing. Since positioning is a key component in these systems, it is essential to ensure its reliability and robustness, and monitor its integrity so that the required levels of positioning accuracy, integrity, continuity and availability can be maintained. In challenging environments, such as urban areas, a single navigation system is often difficult to fulfil the positioning requirements. Therefore, integrating different navigation sensors becomes intrinsic, which may include the global navigation satellite systems, the inertial navigation systems, the odometers and the light detection and ranging sensors. To bind the positioning errors within a pre-defined integrity risk, the integrity monitoring is an essential step in the positioning service, which needs to be fulfilled for integrated vehicular navigation systems used in intelligent transportation systems. Developing such innovative integrity monitoring techniques requires knowledge of many relevant aspects including the structure, positioning methodology and different errors affecting the positioning solution of the individual and integrated systems. Moreover, knowledge is needed for the current mitigation techniques of these errors, for possible fault detection and exclusion algorithms and for computation of protection levels. This paper provides an overview and discussion of these aspects with a focus on intelligent transportation systems

Best integer equivariant estimation for elliptically contoured distributions

This contribution extends the theory of integer equivariant estimation (Teunissen in J Geodesy 77:402–410, 2003) by developing the principle of best integer equivariant (BIE) estimation for the class of elliptically contoured distributions. The presented theory provides new minimum mean squared error solutions to the problem of GNSS carrier-phase ambiguity resolution for a wide range of distributions. The associated BIE estimators are universally optimal in the sense that they have an accuracy which is never poorer than that of any integer estimator and any linear unbiased estimator. Next to the BIE estimator for the multivariate normal distribution, special attention is given to the BIE estimators for the contaminated normal and the multivariate t-distribution, both of which have heavier tails than the normal. Their computational formulae are presented and discussed in relation to that of the normal distribution.</p

Best prediction in linear models with mixed integer/real unknowns: Theory and application

Civil Engineering and Geoscience