Modeling Residual Errors of GPS Pseudoranges by Augmenting Kalman Filter with PCI for Tightly-Coupled RISS/GPS Integration

U. Iqbal, J. Georgy, M.J. Korenberg, A. Noureldin

Abstract:	Over the past couple of decades, road systems are becoming more dense, layered and complex with increasingly heavy traffic that demands modern navigation systems. GPS system alone cannot provide a continuous positioning solution in urban areas where skyscrapers, overpasses, underpasses and tunnels are familiar attributes of present-day cities as line-of-sight (LOS) between the receiver antenna and the satellites is mandatory. GPS signal interruption is a primary cause which affects the continuity and reliability of the navigation solution. In order to obtain continuous positioning services in all environments, GPS can be integrated with inertial sensors and vehicle odometer. Integration between GPS and the other aiding sensors are traditionally performed using Kalman filtering (KF). For car navigation, low-cost positioning solution is always targeted. Thus, low-cost MEMS-based inertial sensors are utilized. To enhance the performance of vehicular navigation along with reducing the cost, reduced inertial sensor system (RISS) consisting of only one gyroscope, two accelerometers and speed measurement (obtained from the car odometer) are integrated with GPS. Tightlycoupled systems can provide GPS aiding during limited GPS satellite availability and thus can improve the operation of the navigation system. Typically KF is used to integrate low-cost MEMS-based RISS with GPS in a tightly-coupled scheme. The KF employed in tightly-coupled RISS/GPS integration utilizes pseudoranges and pseudorange rates measured by the GPS receiver. The accuracy of the positional estimates is highly dependent on the accuracy of the range measurements. This research proposes using a nonlinear system identification technique called Parallel Cascade Identification (PCI), to model pseudoranges correlated errors. When less than four satellites are visible, the identified parallel cascades for the remaining visible satellites will be used to predict the pseudorange errors for these respective satellites and correct the pseudorange value to be provided to KF. This improvement of pseudorange measurement will result in a more accurate aiding for RISS, and thus more accurate estimates of position and velocities. The performance of the proposed technique is examined by conducting road tests in real life trajectories using low cost MEMS-based RISS. This research has strong potential to enhance a navigational solution for land vehicles positioning in dense urban areas, where clear view of sky shrivels limiting satellite visibility and GPS signals suffer from multipath effects resulting in degraded GPS performance. The proposed navigation system provides continuous positioning with higher performance along with considerable reduction in the cost, size, and power consumption due to the use of fewer low-cost MEMSbased inertial sensors and low-cost GPS receiver. These features make the proposed system a highly competitive consumer product.
Published in:	Proceedings of the 23rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2010) September 21 - 24, 2010 Oregon Convention Center, Portland, Oregon Portland, OR
Pages:	2271 - 2279
Cite this article:	Iqbal, U., Georgy, J., Korenberg, M.J., Noureldin, A., "Modeling Residual Errors of GPS Pseudoranges by Augmenting Kalman Filter with PCI for Tightly-Coupled RISS/GPS Integration," Proceedings of the 23rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2010), Portland, OR, September 2010, pp. 2271-2279.
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