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      Loose and Tight GNSS/INS Integrations: Comparison of Performance Assessed in Real Urban Scenarios

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          Abstract

          Global Navigation Satellite Systems (GNSSs) remain the principal mean of positioning in many applications and systems, but in several types of environment, the performance of standalone receivers is degraded. Although many works show the benefits of the integration between GNSS and Inertial Navigation Systems (INSs), tightly-coupled architectures are mainly implemented in professional devices and are based on high-grade Inertial Measurement Units (IMUs). This paper investigates the performance improvements enabled by the tight integration, using low-cost sensors and a mass-market GNSS receiver. Performance is assessed through a series of tests carried out in real urban scenarios and is compared against commercial modules, operating in standalone mode or featuring loosely-coupled integrations. The paper describes the developed tight-integration algorithms with a terse mathematical model and assesses their efficacy from a practical perspective.

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          Most cited references34

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          Precise positioning with current multi-constellation Global Navigation Satellite Systems: GPS, GLONASS, Galileo and BeiDou

          The world of satellite navigation is undergoing dramatic changes with the rapid development of multi-constellation Global Navigation Satellite Systems (GNSSs). At the moment more than 70 satellites are already in view, and about 120 satellites will be available once all four systems (BeiDou + Galileo + GLONASS + GPS) are fully deployed in the next few years. This will bring great opportunities and challenges for both scientific and engineering applications. In this paper we develop a four-system positioning model to make full use of all available observations from different GNSSs. The significant improvement of satellite visibility, spatial geometry, dilution of precision, convergence, accuracy, continuity and reliability that a combining utilization of multi-GNSS brings to precise positioning are carefully analyzed and evaluated, especially in constrained environments.
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            GPS/MEMS INS integrated system for navigation in urban areas

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              INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm

              This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                29 January 2017
                February 2017
                : 17
                : 2
                : 255
                Affiliations
                Istituto Superiore Mario Boella, Torino 10138, Italy; pini@ 123456ismb.it (M.P.); marucco@ 123456ismb.it (G.M.)
                Author notes
                [* ]Correspondence: falco@ 123456ismb.it ; Tel.: +39-011-227-6404
                Article
                sensors-17-00255
                10.3390/s17020255
                5335985
                28146058
                a9ee49c2-f8c2-4d7e-9ceb-add050d4125c
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 30 November 2016
                : 19 January 2017
                Categories
                Article

                Biomedical engineering
                gnss/ins integration,horizontal positioning errors,urban navigation
                Biomedical engineering
                gnss/ins integration, horizontal positioning errors, urban navigation

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