Improved urban navigation with shadow matching and specular matching

Abstract

As the dependence of Global Navigation Systems (GNSS) increases, so does a growing demand for GNSS accuracy in urban environments. This research aims to improve navigation in these environments by integrating non‐line‐of‐sight signals, building models, and measured signal to noise ratios in ways not typically used in GNSS positioning. We propose a technique of combining elements of shadow matching, non‐line‐of‐sight signal prediction through ray tracing, and collaborative navigation. A specularity metric is developed, which predicts the likelihood of building reflections resulting in non‐line‐of‐sight signal reception, and is used in conjunction with shadow matching techniques to improve positioning. A framework for implementing these approaches is presented and demonstrated using improved positioning techniques built and tested using real‐world data collected in urban surroundings.

Performance Evaluation and Hybrid Application of the Greedy and Predictive UAV Trajectory Optimization Methods for Localizing a Target Mobile Device

“…To meet those requirements and provide various location-based services (LBS), most modern mobile devices contain global navigation satellite system (GNSS) chipsets. However, the accuracy and availability of GNSS may be largely degraded in harsh environments, such as urban or indoors, owing to signal blockage and attenuation by buildings (Soloviev, 2010;Strandjord et al, 2020;Lee et al, 2022c;Kim et al, 2021;Lee and Park, 2022). Further, in countries where emergency positioning services are non-mandatory for manufacturers or carriers, the position information of a user in an emergency may not be accessible on some devices.…”

Multi-Epoch Kriging-Based 3D Mapping-Aided GNSS and Doppler Measurement Fusion using Factor Graph Optimization

“…A study on integrating the shadow-matching concept with direct positioning estimation has been conducted to improve positioning accuracy (Strandjord et al, 2020a(Strandjord et al, , 2020b. Another study proposed the combination of shadow matching and ray-tracing and the development of a secularity metric to simultaneously predict the likelihood of building reflections and improve positioning (Strandjord, Axelrad, & Mohiuddin, 2020).…”