Applying the Genetic NIORAIM Algorithm to High Sensitivity GNSS Receivers Operating Indoor

A.J. Joseph, G. Lachapelle

Abstract:	NIORAIM (Novel Integrity Optimized RAIM) is a method to improve RAIM availability by weighting the pseudorange measurements in a non-linear fashion. The non-linearly weighted measurements are then used to compute a position fix. The NIORAIM weights are chosen to improve availability of integrity at the cost of accuracy. The NIORAIM algorithm lowers the deterministic position error that is caused by a bias in a range measurement. In a previous paper (Joseph & Lachapelle 2009) the authors introduced a genetic algorithm implementation to calculate the NIORAIM weights and the associated protection levels. That paper was primarily targeted at airborne GNSS receivers. The genetic NIORAIM algorithm introduced previously can be implemented in a real-time embedded platform. In this paper the application of the NIORAIM algorithm to indoor and degraded signal environments is studied. The primary difference is that the likelihood of simultaneous multiple large errors due to multipath is much greater in the indoors and urban canyons. This paper outlines the theory behind NIORAIM for both single and multiple satellite faults. The challenges involved in calculating the protections levels and the software optimizations required is discussed. An analytical method is used to calculate the probability density functions at runtime to determine the NIORAIM protection levels. This method is very efficient in terms of speed and memory usage when compared to the Look-Up table approach proposed by Hwang & Brown (2005b). A number of efficient numerical methods were implemented to ensure that NIORAIM can perform in a real-time receiver. In airborne applications the primary focus was to reduce the horizontal protection level (HPL). For current WAAS certified airborne receivers the requirement is to assume single satellite faults. In degraded signal environments like indoors and urban canyons it is more useful to reduce position errors than to compute protection levels. NIORAIM reduces the protection level by reducing the position error corresponding to a given pseudo range error. Hence it is an ideal choice for indoor applications. This paper extends the principles behind the NIORAIM algorithm that was earlier implemented by the authors for an airborne receiver to a receiver that can be used in indoor applications. Earlier the NIORAIM algorithm was used exclusively to improve availability of integrity by reducing the protection level. In this paper it is shown that by choosing the appropriate optimization function the non-linear NIORAIM weights will reduce the position error caused by multipath errors in degraded signal environments. This method also obviates the need to perform global tests and local tests to detect and isolate measurement faults. Performance improvements are expected if this method is combined with a robust estimator. The algorithms used in computing the NIORAIM weights will be presented. The NIORAIM algorithm was tested by using data from a high sensitivity GPS receiver in a degraded signal environment. The results from the road test will be discussed. The results show that this modified weighted least squares method that is based on the NIORAIM algorithm removes positions errors that are caused large multipath errors in urban canyons.
Published in:	Proceedings of the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2009) September 22 - 25, 2009 Savannah International Convention Center Savannah, GA
Pages:	1726 - 1741
Cite this article:	Joseph, A.J., Lachapelle, G., "Applying the Genetic NIORAIM Algorithm to High Sensitivity GNSS Receivers Operating Indoor," Proceedings of the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2009), Savannah, GA, September 2009, pp. 1726-1741.
Full Paper:	ION Members/Non-Members: 1 Download Credit Sign In