Carrier phase-based integrity monitoring for high-accuracy positioning

Abstract

Pseudorange-based integrity monitoring, for example receiver autonomous integrity monitoring (RAIM), has been investigated for many years and is used in various applications such as non-precision approach phase of flight. However, for high-accuracy applications, carrier phase-based RAIM (CRAIM), an extension of pseudorange-based RAIM (PRAIM) must be used. Existing CRAIM algorithms are a direct extension of PRAIM in which the carrier phase ambiguities are estimated together with the estimation of the position solution. The main issues with the existing algorithms are reliability and robustness, which are dominated by the correctness of the ambiguity resolution, ambiguity validation and error sources such as multipath, cycle slips and noise correlation. This paper proposes a new carrier phase-based integrity monitoring algorithm for high-accuracy positioning, using a Kalman filter. The ambiguities are estimated together with other states in the Kalman filter. The double differenced pseudorange, widelane and carrier phase observations are used as measurements in the Kalman filter. This configuration makes the positioning solution both robust and reliable. The integrity monitoring is based on a number of test statistics and error propagation for the determination of the protection levels. The measurement noise and covariance matrices in the Kalman filter are used to account for the correlation due to differencing of measurements and in the construction of the test statistics. The coefficient used to project the test statistic to the position domain is derived and the synthesis of correlated noise errors is used to determine the protection level. Results from four cases based on limited real data injected with simulated cycle slips show that residual cycle slips have a negative impact on positioning accuracy and that the integrity monitoring algorithm proposed can be effective in detecting and isolating such occurrences if their effects violate the integrity requirements. The CRAIM algorithm proposed is suitable for use within Kalman filter-based integrated navigation systems.

An assessment of static precise point positioning using GPS only, GLONASS only, and GPS plus GLONASS

“…The POINT software is programmed in C++, and its core is the extended Kalman filter (EKF), as presented in Feng et al (2008).…”

Performance Comparison of GPS Fault Detection and Isolation via Pseudorange Prediction Model based Test Statistics

“…This method, however, has a limitation that it is only realized under the assumption that integrity information and carrier phase measurement are continuously received from GIC link. Besides, Feng implemented Carrier RAIM using carrier phase instead of pseudorange measurement from the existing RAIM method [7]. Carrier RAIM is applicable to the applied areas where a higher accuracy is required than the existing code-based RAIM.…”

GPS Integrity Monitoring Method Using Auxiliary Nonlinear Filters with Log Likelihood Ratio Test Approach

“…In the residual test scheme, picking out the sporadic errors is easy, but detecting the gradually increasing error in the measurement is not. FD may be conducted by examining the probabilistic property of the estimated state itself instead of the residuals [5], yet a precise reference system unaffected by failures is required in implementation [17].…”