Using multiple reference station GPS networks for category III airborne navigation

Multiple real-time GPS reference stations (RTK Networks) were originally developed for surveying purposes to achieve cm-level positioning accuracy using a single GPS receiver. These networks can however replace the proposed airport LAAS systems for positioning during the aircraft’s precision approach and airport surface navigation. They also have the advantage of improving coverage area to include small airports. Real-time testing of this approach was carried out in Dubai, UAE, with a helicopter and a small fixed-wing aircraft using a network known as the DVRS. Results proved the idea and showed that cm to sub-meter positioning accuracy can be achieved. However, the accuracy deteriorates when temporary breaks in reception are encountered. To solve this problem, the GPS can be integrated with IMU unit, or the corrections can be predicted as a time series

Advanced receiver autonomous integrity monitoring using triple frequency data with a focus on treatment of biases

Most current Advanced Receiver Autonomous Integrity Monitoring (ARAIM) methods are designed to use dual-frequency ionosphere-free observations. These methods assume that receiver bias is absorbed in the common receiver clock offset and bound satellite biases by nominal values. However, most multi-constellation Global Navigation Satellite Systems (GNSS) can offer triple frequency data that can be used for civilian applications in the future, which can improve observation redundancy, solution precision and detection of faults. In this contribution, we explore the use of this type of observations from GPS, Galileo and BeiDou in ARAIM. Nevertheless, the use of triple frequency data introduces receiver differential biases that have to be taken into consideration. To demonstrate the significance of these additional biases we first present a method to quantify them at stations of known coordinates and using available products from the International GNSS service (IGS). To deal with the additional receiver biases, we use a between-satellite single difference (BSSD) observation model that eliminates their effect. A pilot test was performed to evaluate ARAIM availability for Localizer Performance with Vertical guidance down to 200. feet (LPV-200) when using the triple-frequency observations. Real data were collected for one month at stations of known coordinates located in regions of different satellite coverage characteristics. The BSSD triple-frequency model was evaluated to give early indication about its feasibility, where the implementation phase still requires further comprehensive studies. The vertical position error was always found to be bounded by the protection level proven initial validity of the proposed integrity model. © 2017 COSPAR

Estimation of Multi-Constellation GNSS Observation Stochastic Properties Using a Single-Receiver Single-Satellite Data Validation Method

The single receiver single satellite validation method is a technique that screens data from each satellite independently to detect and identify faulty observations. A new method for estimation of the stochastic properties of multi-constellation GNSS observation is presented utilising parameters of this validation method. Agreement of the characteristics of the validation statistics with theory is used as the criterion to select the best precision of the observations, spectral density and correlation time of the unknowns. A curve fitting approach in an iterative scheme is employed. The method is applicable to any GNSS with any arbitrary number of frequencies. Demonstration of the method results and performance is given using multiple-frequency data from GPS, GLONASS and Galileo in static and kinematic modes

Local Statistical Testing in Quality Control of GNSS Observations

The paper discusses GNSS statistical-testing methods for detection and identifications of observation outliers at the estimation "current" epoch, defined here as local testing. First, detection methods are discussed including testing the probability distribution (likelihood) of the residuals, testing using dynamic control limits of the range, the mean and standard deviation of the residuals. A method is proposed examining the difference between the mean and the median of the residuals. To identify the satellites with faulty measurements, several methods were investigated, including checking the likelihood of the residuals at the present epoch, and in a time series. A test is presented utilizing the control limits of the residuals' moving range for each satellite. Testing of the proposed methods was carried out using only GPS phase measurements in the kinematic mode. Results show that the proposed methods are efficient for detection and identification of large errors/outliers. However, the performance degrades with error values less than 5 cycles and when using small significance levels