Real-Time Multipath Mitigation with Sensor-Aided Long Coherent Integration (SALI)

We present a novel multipath mitigation scheme, based on Sensor-Aided Long coherent Integration (SALI), for Sensor Fusion (SF) Global Navigation Satellite System (GNSS) receivers (RXs). Applied to terrestrial mobile channels in the GNSS downlink, the upgraded SF RX significantly outperforms the conventional SF RX based on ?20ms Coherent Integration (CI). The benefits are twofold: higher line-of-sight measurement accuracy in the presence of multipaths and enhanced immunity against non-line-of-sight measurements. Both are achieved with a marked drop of overall computational complexity. An embedded implementation of the SALI-based positioning and measurement engine on a single chip with conventional GNSS accelerators and an ARM Cortex M3 processor is proven feasible. In extensive road tests, conducted in open sky, foliage, suburban and deep urban environments, we analyze the pseudo-range and Doppler errors as well as position fix performance in terms of accuracy, integrity and availability w.r.t. the required 2m accuracy using L1 signals. In addition, we compare those statistics for different carrier-to-noise density ratio (C/N0) and for different rover speeds. We demonstrate that the improved measurement quality translates into substantially enhanced position solutions in all challenging environments. The SALI-based SF RX can run real-time CI of ?1s, perfectly aligned with 1Hz GNSS-based navigation rate. This, in turn, allows for enhanced real-time position output in high-rate such as 100Hz, using sensor-based propagation. In the absence of sensor-aided motion compensation, we introduce a backup solution that runs 100ms CI without estimating Doppler rates explicitly. The shorter snapshots drive a Kalman filter that exploits the inherent motion dynamics. Even here, road test results are considerably improved in multipath rich environments with significant frequency dispersion.