Using Random Sampling Consensus (RANSAC) to Detect Errors in Global Navigation Satellite Systems (GNSS) Signals and Data

Abstract

A positioning, navigation, and timing (PNT) signal can be used to estimate a user’s position at an identified time. A global navigation satellite system (GNSS) uses the PNT signal to provide satellite-based navigation. Advanced receivers can track multiple GNSS constellations simultaneously. In order to have a robust and accurate solution, a user needs to detect any faulty measurements and data, and identify which satellite provided them so that faulty satellite can be excluded from a GNSS solution. Differencing techniques, such as time-differenced carrier phase (TDCP), provide for error reduction. The random sample consensus (RANSAC) method allows for the smoothing of data, even when there are a lot of gross errors present in the data set. The residuals from RANSAC and TDCP were studied to determine if they can be used to detect and identify error sources. A downsampling and thresholding method was able to identify first-order biases with slopes on the order of 10^−6 within minutes, while biases with slopes on the order of 10^−7 were identified on the order of one hour. The residuals from RANSAC and TDCP were ultimately able to detect and identify error sources.