DINGPOS: High sensitivity GNSS platform for deep indoor scenarios (original) (raw)
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DINGPOS, a GNSS-based multi-sensor demonstrator for indoor navigation: Preliminary results
IEEE/ION Position, Location and Navigation Symposium, 2010
The goal of this paper is to present the architecture and first performance results of the DINGPOS platform. The DINGPOS platform (Demonstrator for INdoor GNSS POSitioning) is a project funded by the ESA that covers the design, development and integration of an experimental indoor positioning system based on the fusion of three different technologies: High Sensitivity GNSS (GPS and the future Galileo), MEMS-based Pedestrian Navigation System and WIFI. This paper introduces the different architectural trade-offs of the final platform and presents the first results of its performance and capabilities with real data.
Challenges in Indoor Global Navigation Satellite Systems
2012
ccurately determining one's position has been a recurrent problem in history [1]. It even precedes the first deep-sea navigation attempts of ancient civilizations and reaches the present time with the issue of legal mandates for the location identification of emergency calls in cellular networks and the emergence of location-based services. The science and technology for positioning and navigation has experienced a dramatic evolution [2]. The observation of celestial bodies for navigation purposes has been replaced today by the use of electromagnetic waveforms emitted from reference sources [3]. There is a large variety of radio-navigation systems, ranging from legacy ones dating from the middle of the last century, such as Decca or Loran, to the ones relying on the transmissions from wireless local area network (WLAN) base stations or from the devices found in wireless sensor networks. However, the systems based on satellite transmissions are the ones that play a prominent role today. They are gathered under global navigation satellite systems (GNSS). This term refers to all systems (some of them operational, and others under development) that provide users with positioning information
Technical Limitations of GNSS Receivers in Indoor Positioning
2007 17th International Conference Radioelektronika, 2007
This paper presents an overview of aspects that have to be taken into account in use of GNSS receivers for positioning in the difficult environment, for example indoors. The performing position determination and navigation tasks in such environments come nowadays more and more in the focus of the GNSS community. The GNSS signal indoor reception is affected by strong attenuation and due to the nature of the environment by strong multipath. The paper discusses both of them and their possible impact to the navigation tasks. The effect of the user movement is discussed and the experimental measurements are presented. The measurements were realized with use of experimental GNSS software receiver, described in the paper as well.
Signal Propagation Analysis and Signature Extraction for GNSS Indoor Positioning
Position Location and Navigation IEEE Symposium, 2006
The large popularization of GNSS (based on GPS, Glonass and forthcoming Galileo) receivers and the increased market interest for Location Based Services (LBS) have motivated interesting studies in modelling the radio channel propagation for dense urban and indoor geolocation, where two key problems need to be addressed: weak signal operation and multipath, both leading to receiver range errors and consequently position being calculated with large biases.
A test-bed implementation of an acquisition system for indoor positioning
Gps Solutions, 2009
Indoor GNSS signals are typically received with poor signal-to-noise ratio, which impairs the acquisition stage of common global positioning system (GPS) receivers. Extending the coherent integration time increases the acquisition sensitivity, but the data-bit-rate limits the maximum achievable performance. Non-coherent processing also improves the detection performance, but indoor signals require a large amount of accumulations resulting in significant squaring loss. Moreover, both strategies have high computational complexity which fixes demanding requirements for stand alone mass-market terminals operating in real time. A sensitivity-complexity trade-off is therefore mandatory. Assisted-GPS, which is included in 3GPP specifications, reduces the overall acquisition complexity and enhances sensitivity. In this paper we describe a low-complexity-assisted data-wipe-off technique that enables the high-sensitivity acquisition of GPS signals. The method is based on the acquisition of the strongest signal in order to obtain information that eases the acquisition of the weaker ones. The analysis also addresses sources of sensitivity loss, such as Doppler effects and local oscillator inaccuracies. A test campaign with real signals and integration times up to 2 s validates the method, demonstrating the effectiveness of the proposed technique in indoor environments.
7Th Geomatic Week, 2007
The main objective of the project 'SARHA-Sensor-Augmented EGNOS/Galileo Receiver for Handheld Applications in Urban and Indoor Environments' is the development of a modern satellite navigation receiver with autonomous sensor augmentation. Additionally, the hybrid navigation system will be enhanced by a transponder capable of receiving absolute position updates from transmitters installed inside buildings. The transponder will allow the SARHA system to significantly increase reliability and accuracy of the positioning solutions indoors. The hybrid navigation software is split up into two parts. The first one will be implemented directly on the GPS receiver, whereas the second part will run on a microcontroller. Thus, a small, low-performance microcontroller can be used, representing the first step towards the reduction of size, weight and power consumption of the mobile system. This paper provides an overview on personal mobility and typical applications related to the system, describes the system architecture and the hybrid navigation software in detail. Furthermore, emphasis is laid on a comparison of different step detection algorithms, showing their advantages and disadvantages. Based on the Galileo signal definition, additional analysis set up to explore the signal characteristics in comparison to the GPS signals, are provided. Improvements due to the Galileo signal availability in urban and indoor environments are assessed and will later ensure seamless integration of enhanced technologies into the continuous developments.
Wireless Personal Communications, 2018
In order to support indoor and outdoor seamless location-based services (LBS), this paper proposes a smart fusion architecture for combing the ubiquitous signals of the mobile device integrated multi-modal sensors based on deep learning, which can fuse the vision/wireless/inertial information. The core of the fusion architecture is an improved four-layers deep neural network that integrating a convolutional neural network (CNN) and an improved particle filter. In the first place, inspired by creating the RGB-D image, we change the image gray by using a normalized magnetic strength and scale the image intensity by using a normalized WiFi signal strength, which results in a new image named RGB-WM image. Then, homogeneous features are extracted from the RGB-WM image based on the improved CNN for achieving context-awareness. Based on combing the context information, we introduce a new particle filter for fusing different information from multi-modal sensors. In order to evaluate our proposed positioning architecture, we have conducted extensive experiments in four different scenarios including our laboratory, and the campus of our university. Experimental results demonstrate the precision and recall of the RGB-WM image feature is 95.6 and 4.1% respectively. Furthermore, the proposed infrastructure-free fusion architecture reduced the root mean square error (RMSE) of locations in the range of 13.3-55.2% in walking experiments with two smartphones, under two motion conditions, which indicates a superior performance of our proposed image/ WiFi/magnetic/inertial fusion architecture over the state-of-the-art with these four localization scenarios. The ubiquitous positioning accuracy of our proposed algorithm is less than 1.23 m, which can meet the requirement of the complex GNSS-denied regions.
IEEE Access
During the last decade, the number of applications for land transportation that depend on systems for accurate positioning has significantly increased. Unfortunately, systems based on low-cost global navigation satellite system (GNSS) components harshly suffer signal impairments due to the environment surrounding the antenna, but new designs based on deeper data fusion and on the combination of different signal processing techniques can overcome limitations without the introduction of expensive components. Supported by a complete mathematical model, this paper presents the design of a real-time positioning system that is based on the tight integration of extremely low-cost sensors and a consumer-grade global positioning system receiver. The design has been validated experimentally through a series of tests carried out in real scenarios. The performance of the new system is compared against a standalone GNSS receiver and surveygrade professional equipment. The results show that a carefully designed and constrained integration of low-cost sensors can have performance comparable to that of an expensive professional equipment. INDEX TERMS Global positioning system (GPS), inertial navigation system (INS), position accuracy, tight architecture.
Performance Evaluation of High Sensitivity GNSS Techniques in Indoor, Urban and Space Environments
Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016), 2016
BIOGRAPHY Enrique Domínguez received a M.Sc. degree in Telecommunications Engineering in 2000 and a Master in Space Technologies in 2009, both from the Polytechnic University of Madrid. He joined GMV in 2000 working first in the development of EGNOS and Galileo and since 2009 in GNSS software receivers, multi-sensor fusion algorithms and integrity algorithms.