Implementation of Parallel Cascade Identification at Various Phases for Integrated Navigation System

Global navigation satellite systems (GNSS) are widely used for the of land vehicles. However, positioning accuracy GNSS, such as global system (GPS), deteriorates in urban areas due to signal blockage and multipath effects. GNSS can be integrated with a micro-electro-mechanical (MEMS)–based inertial (INS), reduced sensor (RISS) using Kalman filter (KF) enhance performance solution challenging environments. The linearized KF cannot model low-cost small-size sensors relatively high noise levels compound error characteristics. This paper reviews two approaches employing parallel cascade identification (PCI), non-linear technique, augmented navigational solution. First, PCI models azimuth errors loosely coupled 2D RISS obtain experimental results demonstrated that improved RISS/GNSS by modeling linear, non-linear, other residual errors. For second scenario, is utilized pseudorange correlated KF-based tightly Experimental have shown enhances provide an enhanced more reliable first algorithm, 77% compared during outages. improvement proposed technique availability three satellites was 39%