Self-Contained Sensor Aided Kinematic HSGPS Positioning Algorithm

O. A. Mezentsev

Abstract:	High Sensitivity GPS (HSGPS) provides significantly better availability in challenging urban environments but is also subjected to harsh cross-correlation interference and erroneous signal tracking due to multi-path and echo-only signals (Lachapelle et al., 2003b). These effects can cause very large errors in the pseudorange measurements. Often, lack of redundancy at a single epoch limits the detection of such blunders by Receiver Autonomous Integrity Monitoring (RAIM) or other statistical testing techniques (Lu, 1991; Brown, 1992; Parkinson and Spilker, 1996). The inability to perform such testing, results in a poor estimation of navigation solution accuracy. In this work, a novel approach to process sensor aided HSGPS data especially in a very challenging GPS environment is proposed. The approach takes advantage of a self-contained sensor augmentation to HSGPS that provides additional information, such as travelled distance and heading between epochs, thus enabling a batch LSQ procedure in a kinematic mode. In the case under study, a pedestrian navigation application is selected. It should be noted that this paper is not aiming at an optimal strategy of sensor integration with HSGPS, but rather considers a particular novel approach of kinematic LSQ batch processing of HSGPS data with the sensor aiding. The proposed method intends to provide a means for better accuracy assessment of HSGPS results, and thus a more reliable HSGPS position solution that later can be successfully used in other filtering methods, such a Kalman Filter.
Published in:	Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004) September 21 - 24, 2004 Long Beach Convention Center Long Beach, CA
Pages:	2468 - 2478
Cite this article:	Mezentsev, O. A., "Self-Contained Sensor Aided Kinematic HSGPS Positioning Algorithm," Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004), Long Beach, CA, September 2004, pp. 2468-2478.
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