المؤلفون: Lai, Qifeng, Yuan, Hong, Wei, Dongyan, Wang, Ningbo, Li, Zishen, Ji, Xinchun

المصدر: Sensors (14248220); May2020, Vol. 20 Issue 9, p2551, 1p

مصطلحات موضوعية: MULTISENSOR data fusion, GLOBAL Positioning System, INERTIAL navigation systems, TELECOMMUNICATION satellites

مستخلص: Using the Global Navigation Satellite System (GNSS), it is difficult to provide continuous and reliable position service for vehicle navigation in complex urban environments, due to the natural vulnerability of the GNSS signal. With the rapid development of the sensor technology and the reduction in their costs, the positioning performance of GNSS is expected to be significantly improved by fusing multi-sensors. In order to improve the continuity and reliability of the vehicle navigation system, we proposed a multi-sensor tight fusion (MTF) method by combining the inertial navigation system (INS), odometer, and barometric altimeter with the GNSS technique. Different fusion strategies were presented in the open-sky, insufficient satellite, and satellite outage environments to check the performance improvement of the proposed method. The simulation and real-device tests demonstrate that in the open-sky context, the error of sensors can be estimated correctly. This is useful for sensor noise compensation and position accuracy improvement, when GNSS is unavailable. In the insufficient satellite context (6 min), with the help of the barometric altimeter and a clock model, the accuracy of the method can be close to that in the open-sky context. In the satellite outage context, the error divergence of the MTF is obviously slower than the traditional GNSS/INS tightly coupled integration, as seen by odometer and barometric altimeter assisting. [ABSTRACT FROM AUTHOR]

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المؤلفون: Wei, Dongyan¹ (AUTHOR) weidy@aircas.ac.cn, Huang, Lichen^1,2 (AUTHOR) huanglichen17@mails.ucas.ac.cn, Ji, Xinchun^1,2 (AUTHOR), Li, Wen^1,2 (AUTHOR), Lu, Yi^1,2 (AUTHOR), Yuan, Hong¹ (AUTHOR)

المصدر: Sensors (14248220). 12/15/2019, Vol. 19 Issue 24, p5410. 1p.

مصطلحات موضوعية: *GLOBAL Positioning System

مستخلص: Magnetic navigation is a promising positioning technique for scenarios where a global navigation satellite system (GNSS) is unavailable, such as for underwater submarines and aircraft in space. For ground scenarios, it faces more challenges, since the magnetic distribution suffers interference from surrounding objects such as buildings, bridges, and vehicles. It is natural to think how feasible it is to apply magnetic matching positioning to vehicles. In this paper, a theoretic distribution model is proposed to analyze the magnetic field around objects such as buildings, bridges, and vehicles. According to the experiments, it is shown that the proposed model matches the experimental data well. In addition, a comprehensive indicator metric is defined in this paper to describe the feasibility of the magnetic matching method based on the statistical characteristics of magnetic maps. The best length of matching window, anti-noise performance, and pre-comparison of positioning accuracy in different regions can be easily derived using the proposed comprehensive indicator metric. Finally, the metric is verified through a drive test using different building densities. [ABSTRACT FROM AUTHOR]

المؤلفون: Zhang, Wenchao^1,2 (AUTHOR) yuanhong@aircas.ac.cn, Wei, Dongyan² (AUTHOR) zhangwenchao@aoe.ac.cn, Yuan, Hong² (AUTHOR)

المصدر: Sensors (14248220). Sep2019, Vol. 19 Issue 18, p3962-3962. 1p.

مصطلحات موضوعية: *INERTIAL navigation systems, *KALMAN filtering, *DRIVER assistance systems

مستخلص: The zero-velocity update (ZUPT)-aided extended Kalman filter (EKF) is commonly used in the traditional inertial navigation system (INS)-based foot-mounted pedestrian dead reckoning (PDR) system, which can effectively suppress the error growth of the inertial-based pedestrian navigation systems. However, in the realistic test, the system still often suffers from drift, which is commonly caused by two reasons: failed detection of the stationary phase in the dynamic pedestrian gait and heading drift, which is a poorly observable variable of the ZUPT method. In this paper, firstly, in order to improve the initial heading alignment accuracy, a novel method to calibrate the PDR system's initial absolute heading is proposed which is based on the geometric method. By using a calibration line rather than only using the heading of the starting point, the method can calibrate the initial heading of the PDR system more accurately. Secondly, for the problem of failed detection of the stationary phase in the dynamic pedestrian gait, a novel stationary phase detection method is proposed, which is based on foot motion periodicity rather than the threshold comparison principle in the traditional method. In an experiment, we found that the zero-speed state points always occur around the minimum value of the stationary detector in each gait cycle. By taking the minimum value in each gait cycle as the zero-speed state point, it can effectively reduce the failed detection of the zero-speed interval. At last, in order to reduce the heading drifts during walking over time, a new motion constraint method is exploited based on the range constraint principle. During pedestrian walking, the distance between the foot position estimates of the current moment and the previous stationary period is within the maximum stride length. Once the distance is greater than the maximum stride length, the constraint method is used to confine the current estimated foot position to the sphere of the maximum stride length relative to the previous stationary foot position. Finally, the effectiveness of all proposed methods is verified by the experiments. [ABSTRACT FROM AUTHOR]

المؤلفون: Li, Wen^1,2 wen.li@aoe.ac.cn, Wei, Dongyan¹ weidongyan@aoe.ac.cn, Lai, Qifeng^1,2, Li, Xianghong^1,2, Yuan, Hong¹

المصدر: Sensors (14248220). May2018, Vol. 18 Issue 5, p1462. 1p.

مصطلحات موضوعية: *GEOMAGNETISM, *IEEE 802.11 (Standard), *SMARTPHONES, *CROWDSOURCING, *PROBLEM solving

مستخلص: Wi-Fi radio-map construction is an important phase in indoor fingerprint localization systems. Traditional methods for Wi-Fi radio-map construction have the problems of being time-consuming and labor-intensive. In this paper, an indoor Wi-Fi radio-map construction method is proposed which utilizes crowdsourcing data contributed by smartphone users. We draw indoor pathway map and construct Wi-Fi radio-map without requiring manual site survey, exact floor layout and extra infrastructure support. The key novelty is that it recognizes road segments from crowdsourcing traces by a cluster based on magnetism sequence similarity and constructs an indoor pathway map with Wi-Fi signal strengths annotated on. Through experiments in real world indoor areas, the method is proved to have good performance on magnetism similarity calculation, road segment clustering and pathway map construction. The Wi-Fi radio maps constructed by crowdsourcing data are validated to provide competitive indoor localization accuracy. [ABSTRACT FROM AUTHOR]