Sequential Quadratic Method for GPS NLOS Positioning in Urban Canyon Envi-ronments

Abstract

In this paper, the problem of GPS non-line-of-sight (NLOS) positioning in urban canyon environment is considered. We propose a new position-determination estimator based on the sequential quadratic programming (SQP) that is able to estimate and eliminate the path-delay error caused by the indirect transmission of the GPS signal. The estimator takes into account the measurement bias resulting from NLOS transmission, and in the mean-time also improves the location accuracy of a satellite positioning system. The present method can effectively eliminate the NLOS delay errors and is also able to improve the location accuracy of a satellite navigation receiver in an urban canyon environment. A Wilcoxon-norm-based regressor is further derived to improve the probability of detection of the NLOS biases. The Wilcoxon regressor is a robust estimator that is well suitable for identifying outliers (in our case, the NLOS biases) during the regression process. In our experimental results, it is demonstrated that the proposed estimator can compute the coordinate of a user location in an accurate fashion after identifying and removing the measurement biases.

Keywords

• Non-Line-of-Sight
• Sequential Quadratic Programming
• Global Positioning System
• Wilcoxon Regression
• Urban Canyon Environment.