Unbiased vs biased estimation of GPS phase ambiguities from dual-frequency code and phase observables

Abstract

With access to dual-frequency pseudorange and phase Global Positioning System (GPS) data, the wide-lane ambiguity can easily be fixed. Advantage is taken of this information in the linear combination of the above four observables for base ambiguity estimation (i.e. of N 1 and N 2). Starting points for our analysis are the Best Linear Unbiased Estimators BLUE1 and BLUE2. BLUE1 is the best one (with minimum mean square error, MSE) if the ionosphere effect is negligible. If this is not the case, BLUE2 has the smallest variance, but not necessarily the least mean square error. Hence, both estimators may suffer from a non-optimal treatment of the ionosphere bias. BLUE1 ignores possible ionosphere bias, while BLUE2 compensates for this bias in a less favourable way by eliminating it at the price of increased noise. As an alternative, linear estimators are derived, which make a compromise between the ionosphere bias and the random observation errors. This leads to the derivation of the Best Linear Estimator (BLE) and the Restricted Best Linear Estimator (RBLE) with minimum MSE. The former is generally not very useful, while the RBLE is recommended for practical use. It is shown that the MSE of the RBLE is limited by the variances of BLUE1 and BLUE2, i.e. However, as is always the case with a BLE, it cannot be used strictly: some parameter (in this case the ionosphere bias) must be approximately known.