Multipath Mitigation of Continuous GPS Measurements Using an Adaptive Filter

Though state-of-the-art dual-frequency receivers are employed in the Continuous GPS arrays (CGPS), the CGPS coordinate time series are typically very noisy due to the effects of atmospheric biases, multipath, receiver noise, etc., with multipath generally being considered the major noise contributor. An adaptive Finite-duration Impulse Response filter, based on a least-mean-square algorithm, has been developed to derive a relatively noise-free time series from the CGPS results. Furthermore, this algorithm is suitable for realtime applications. Numerical simulation studies indicate that the adaptive filter is a powerful signal decomposer, which can significantly mitigate multipath effects. By applying the filter to both pseudo-range and carrier phase multipath sequences derived from some experimental GPS data, multipath models have been reliably derived. It is found that the best multipath mitigation strategy is forward filtering using data on two adjacent days, which reduces the standard deviations of the pseudo-range multipath time series to about one fourth it's magnitude before correction, and to about half in the case of carrier phase. The filter has been successfully applied to the pseudo-range multipath sequences derived from CGPS data. The benefit of this technique is that the affected observable sequences can be corrected, and then these corrected observables can be used to improve the quality of the GPS coordinate results.