Kinematic Galileo and GPS Performances in Aerial, Terrestrial, and Maritime Environments

Bastos, L.; Buist, Peter J.; Cefalo, Raffaela; Gonçalves, J.; Ivan, Antonia Nicoleta; Magalhães, A.; Pandele, Alexandru; Porretta, Marco; Radutu, Alina; Sluga, Tatiana; Snider, Paolo

doi:10.3390/rs14143414

Cited by 4 publications

(2 citation statements)

References 23 publications

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“…MEMS sensor devices are becoming increasingly popular and cheaper, and have been widely used in various fields and applications, such as motion monitoring and management, healthcare, location-based services (LBS), and navigation. In addition, the advancement of micro-electro-mechanical-system (MEMS) technology has made accelerometers, magnetometers and gyroscopes more and more accurate, lightweight, and low cost, which has greatly promoted their application in indoor positioning [ 5 ]. Accelerometers, magnetometers, and gyroscopes provide beaconless solutions.…”

Section: Introductionmentioning

confidence: 99%

Research on Pedestrian Indoor Positioning Based on Two-Step Robust Adaptive Cubature Kalman Filter with Smartphone MEMS Sensors

Geng

et al. 2023

Micromachines

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With the development of location-based service (LBS), indoor positioning based on pedestrian dead reckoning (PDR) has become a hot research topic. Smartphones are becoming more popular for indoor positioning. This paper proposes a two-step robust-adaptive-cubature Kalman filter (RACKF) algorithm based on smartphone micro-electro-mechanical-system (MEMS) sensor fusion for indoor positioning. To estimate pedestrian heading, a quaternion-based robust-adaptive-cubature Kalman filter algorithm is proposed. Firstly, the model noise parameters are adaptively corrected based on the fading-memory-weighting method and the limited-memory-weighting method. The memory window of the limited-memory-weighting algorithm is modified based on the characteristics of pedestrian walking. Secondly, an adaptive factor is constructed based on the partial state inconsistency to overcome filtering-model deviation and abnormal disturbances. Finally, to identify and control the measurement outliers, the robust factor based on maximum-likelihood estimation is introduced into the filtering to enhance the robustness of heading estimation and support more robust dynamic-position estimation. In addition, based on the accelerometer information, a nonlinear model is constructed and the empirical model is used to estimate the step length. Combining heading and step length, the two-step robust-adaptive-cubature Kalman filter is proposed to improve the pedestrian-dead-reckoning method, which enhances the adaptability and robustness of the algorithm and further improves the accuracy of the plane-position solution. The adaptive factor based on the prediction residual and the robust factor based on the maximum-likelihood estimation are introduced into the filter to improve the adaptability and robustness of the filter, reduce the positioning error, and improve the accuracy of the pedestrian-dead-reckoning method. Three different smartphones are used to validate the proposed algorithm in an indoor environment. Additionally, the experimental results confirm the algorithm’s effectiveness. From the results of the three smartphones, the root mean square error (RMSE) of the indoor-positioning results obtained by the proposed method is about 1.3–1.7 m.

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Section: Introductionmentioning

confidence: 99%

Research on Pedestrian Indoor Positioning Based on Two-Step Robust Adaptive Cubature Kalman Filter with Smartphone MEMS Sensors

Geng

et al. 2023

Micromachines

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“…This article presents some results of the terrestrial campaigns performed starting from 2019 using the GeoSNav Lab MMS (Mobile Mapping System), a Septentrio ® AsterX-U geodetic GNSS multi-constellation/multi-frequency receiver and a multiconstellation/double frequencies smartphone with the principal aim of evaluating the Galileo performances. These performances were evaluated comparing the Galileo PVT (Positioning, Velocity, Time) parameters (Leick et al, 2003;Subirana et al, 2013;Hofmann-Wellenhof et al, 2015; obtained using GPS, GLONASS, GPS+GLONASS, GPS+Galileo and GPS+GLONASS+Galileo, both in urban and extra-urban areas (Bastos et al, 2022;Tarantino et al, 2018). The processed rover trajectories and the produced outputs were compared with integrated high-performance trajectory obtained from GNSS/INS (INertial System), giving a "reference", stable and highly accured trajectory.…”

Section: Introductionmentioning

confidence: 99%

Geodetic Kinematic Terrestrial Navigation Using a MMS – Multi-Constellation and Multi-Frequency Galileo/GPS/Glonass Performance Comparisons

Cefalo

Snider

Sluga

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. This paper presents a part of the research activities performed from 2019 to 2022 in the framework of WP 5.3 “Field campaign” and in particular, the activities “Land urban and extra-urban data measurement campaigns” of the European GRC-MS (Galileo Reference Center – Member States) Project - GSA/GRANT/04/2016.The dynamic data-collection campaigns were conducted by three participating member states (Portugal, Italy, and Romania), in three different environments: aerial, terrestrial, and maritime, respectively.This article presents a comparison of the results obtained for the terrestrial environment, considering the performance of Galileo used in conjunction with other GNSS systems, such as GPS, using different geodetic and navigational multi-constellation and multi-frequency receivers/devices experimental dynamic activities. Starting from the user’s needs and requirements, the experimental setup and the methodology for the estimation of the reference («actual») trajectory are provided. These are complemented by numerical results and reasons for possible performance degradations analyses.The processed rover trajectories and the produced outputs were compared to the reference trajectory obtained from GNSS/INS (INertial System) integrated high-performance solution.Galileo-only and GPS-only solutions, so as multi-system solutions (GPS+Galileo, GPS+GLONASS and GPS+GLONASS+Galileo) were analysed. PVT (Position Velocity Time) solutions were computed using post-processing geodetic interferential techniques.From the performed analyses, some preliminary conclusions relative to the Galileo performances applied to terrestrial urban and extra-urban navigation were derived.These activities need to be continued in the near future, taking into consideration the Galileo constellation improvements and the ITS (Intelligent Transport Systems) applications in order to improve the offered services and the road safety.

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Assessment of Galileo FOC + IOV Signals and Geometry-Based Single-Epoch Resolution of Quad-Frequency Carrier Ambiguities

Liu

Wang

et al. 2022

Remote Sensing

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Galileo can independently provide navigation and positioning services globally. Galileo satellites transmit quad-frequency E1, E5a, E5b, and E5 signals, which can benefit the integer ambiguity rapid resolution. Firstly, the qualities of Galileo signals from Carrier-to-Noise (C/N0), Multipath Combination (MPC), and pseudo-range and phase noise using the ultra-short baseline were evaluated. The experimental results indicated that the Galileo E5 signal has the highest C/N0, while the C/N0 of other signals is lower and almost equal. In terms of MPC, the Galileo E1 was the most severe followed by E5a and E5b, and the MPC of E5 is less severe. As for the precision of un-differenced observations, the carrier phase and pseudo-range observations of Galileo E5 had higher accuracy than those of Galileo E5a, E5b, and E1. Secondly, the quad-frequency observations allowed for various linear combinations of different frequencies, which provides some feasibility for improving the performance of ambiguity resolution. Assuming that the phase noise and the first-order ionosphere , the total noise of the Extra-Wide-Lane (EWL) combination observation ((0, 0, 1, −1) and (0, −1, 1, 0)) and Very-Wide-Lane (VWL) combination observation ((0, −2, 1, 1), (0, −3, 2, 1)) are still less than 0.5 cycles. Finally, a geometry-based quad-frequency carrier ambiguities (GB-QCAR) method was developed, and all different options of linear combinations were investigated systematically from the ambiguity-fixed rate with two baselines. Experimental results demonstrated that, the ambiguity fixed rate of combination observation (0, −1, 1, 0), (0, −3, 5, −2), (1, −1, 0, 0) and (0, 0, 0, 1) is the highest and the positioning accuracy of VWL combination observation (0, −3, 5, −2) is equivalent to that of the EWL combination observation (0, −1, 1, 0). The positioning accuracies of WL combination observation (1, −1, 0, 0) are preferable to 3 cm and 10 cm in the horizontal and vertical, respectively. The positioning accuracy of NL combination observation E5 in the horizontal direction is about 1 cm, and is better than 4 cm in the vertical direction. Therefore, we can use Galileo observations to realize high-precise navigation services utilizing the proposed GB-QCAR method.

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Kinematic Galileo and GPS Performances in Aerial, Terrestrial, and Maritime Environments

Cited by 4 publications

References 23 publications

Research on Pedestrian Indoor Positioning Based on Two-Step Robust Adaptive Cubature Kalman Filter with Smartphone MEMS Sensors

Research on Pedestrian Indoor Positioning Based on Two-Step Robust Adaptive Cubature Kalman Filter with Smartphone MEMS Sensors

Geodetic Kinematic Terrestrial Navigation Using a MMS – Multi-Constellation and Multi-Frequency Galileo/GPS/Glonass Performance Comparisons

Assessment of Galileo FOC + IOV Signals and Geometry-Based Single-Epoch Resolution of Quad-Frequency Carrier Ambiguities

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