Seamless Indoor-Outdoor Infrastructure-free Navigation for Pedestrians and Vehicles with GNSS-aided Foot-mounted IMU

Zhu, Ni; Ortiz, Miguel; Renaudin, Valérie

doi:10.1109/ipin.2019.8911741

Cited by 8 publications

(7 citation statements)

References 17 publications

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“…Foot-mounted PDR systems apply a zero-velocity update when the pedestrian is not moving. However, in [13], it was shown that the analysis of differences between timeshifted measurements of acceleration and magnetic sensors can also contribute to improving the navigation solution. Additionally, a GPS receiver is intended for outdoor use, but it can also detect the transition from outside to inside.…”

Section: Self-localizationmentioning

confidence: 99%

Seamless Navigation, 3D Reconstruction, Thermographic and Semantic Mapping for Building Inspection

Schischmanow

Dahlke

Baumbach

et al. 2022

Sensors

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We present a workflow for seamless real-time navigation and 3D thermal mapping in combined indoor and outdoor environments in a global reference frame. The automated workflow and partly real-time capabilities are of special interest for inspection tasks and also for other time-critical applications. We use a hand-held integrated positioning system (IPS), which is a real-time capable visual-aided inertial navigation technology, and augment it with an additional passive thermal infrared camera and global referencing capabilities. The global reference is realized through surveyed optical markers (AprilTags). Due to the sensor data’s fusion of the stereo camera and the thermal images, the resulting georeferenced 3D point cloud is enriched with thermal intensity values. A challenging calibration approach is used to geometrically calibrate and pixel-co-register the trifocal camera system. By fusing the terrestrial dataset with additional geographic information from an unmanned aerial vehicle, we gain a complete building hull point cloud and automatically reconstruct a semantic 3D model. A single-family house with surroundings in the village of Morschenich near the city of Jülich (German federal state North Rhine-Westphalia) was used as a test site to demonstrate our workflow. The presented work is a step towards automated building information modeling.

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Section: Self-localizationmentioning

confidence: 99%

Seamless Navigation, 3D Reconstruction, Thermographic and Semantic Mapping for Building Inspection

Schischmanow

Dahlke

Baumbach

et al. 2022

Sensors

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show abstract

“…Nowadays, the Location Based Services (LBS) are growing rapidly and attracting much attention with the proliferation of mobile devices [1]. Besides the well known Global Navigation Satellite Systems (GNSS) which can only be used in open areas as their signals are easily blocked or interfered by buildings [2], communication-based positioning methods (5G, Bluetooth, Wi-Fi, etc.) have been greatly developed in recent years as the ready-made communication networks have natural advantages of wide coverage, easy deployment and low-cost [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

“…So we have B f e 2 /Tp. Consequently, a DLL's narrow early-late spacing D can be applied2 . When D → 0, sin (πf DT p ) in (51)-(54) can be replaced by Taylor expansion around 0.…”

mentioning

confidence: 99%

Design and Performance Analysis of Multi-Scale NOMA for Future Communication-Positioning Integration System

Yin

Cao

et al. 2022

IEEE J. Select. Areas Commun.

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This paper presents a feasibility study of a novel multiple access technique called Multi-Scale Non-Orthogonal Multiple Access (MS-NOMA) for the next generation communication-positioning integration system. Different from the traditional positioning signals which are mostly Time Division Multiple Access with communication signals and are broadcast to all users, MS-NOMA supports continuous positioning waveform and flexible configurations for different positioning users to obtain higher ranging accuracy, lower positioning latency, less resource consumption and better signal coverage. Our major contributions are: Firstly, we present the MS-NOMA waveform and evaluate its performances by theoretical and simulation analyses. The results show it is feasible to use the MS-NOMA waveform to achieve high positioning accuracy and low Bit Error Rate with little resource consumption simultaneously. Secondly, to achieve optimal positioning accuracy and signal coverage, we model the power allocation problem for MS-NOMA as a convex optimization problem satisfying the Quality of Services requirement and other constraints. Then, we propose a novel Communication and Positioning Performances constrained Positioning Power Allocation (CP4A) algorithm which allocates the power of all P-Users iteratively. The theoretical and numerical results show our proposed MS-NOMA waveform with CP4A algorithm has great improvements of ranging/positioning accuracy than traditional Positioning Reference Signal in cellular network.

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“…However, receiving a GNSS signal is very problematic in building interiors because direct visibility of the GNSS signal between satellites and receivers is not allowed, which goes to a multipath effect [11]. Therefore, there have been many efforts to refine the acquired position by using high-sensitivity receivers [12] or pseudo-satellites [13] or combining GNSS with inertial sensors [14]. Talking about inertial sensors (i.e., accelerometers and gyroscopes), we also encounter a fundamental problem.…”

Section: Introductionmentioning

confidence: 99%

Indoor Positioning Using PnP Problem on Mobile Phone Images

Kubíčková¹,

Jedlička

Fiala

et al. 2020

IJGI

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As people grow accustomed to effortless outdoor navigation, there is a rising demand for similar possibilities indoors as well. Unfortunately, indoor localization, being one of the requirements for navigation, continues to be a problem without a clear solution. In this article, we are proposing a method for an indoor positioning system using a single image. This is made possible using a small preprocessed database of images with known control points as the only preprocessing needed. Using feature detection with the SIFT (Scale Invariant Feature Transform) algorithm, we can look through the database and find an image that is the most similar to the image taken by a user. Such a pair of images is then used to find coordinates of a database of images using the PnP problem. Furthermore, projection and essential matrices are determined to calculate the user image localization—determining the position of the user in the indoor environment. The benefits of this approach lie in the single image being the only input from a user and the lack of requirements for new onsite infrastructure. Thus, our approach enables a more straightforward realization for building management.

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Seamless Indoor-Outdoor Infrastructure-free Navigation for Pedestrians and Vehicles with GNSS-aided Foot-mounted IMU

Cited by 8 publications

References 17 publications

Seamless Navigation, 3D Reconstruction, Thermographic and Semantic Mapping for Building Inspection

Seamless Navigation, 3D Reconstruction, Thermographic and Semantic Mapping for Building Inspection

Design and Performance Analysis of Multi-Scale NOMA for Future Communication-Positioning Integration System

Indoor Positioning Using PnP Problem on Mobile Phone Images

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