MIMO fingerprinting-based particle filter for mobile positioning systems

2013 ◽  
Author(s):  
Mu-Hsuan Chuang ◽  
Yi-Hao Lo ◽  
Bo-Yi Wu ◽  
Yuan-Hao Huang
Keyword(s):  
Particle Filter ◽  
Positioning Systems ◽  
Mobile Positioning

scholarly journals Positioning Techniques in Indoor Environments Based on Stochastic Modeling of UWB Round Trip Time Measurements

2021 ◽  
Author(s):  
Paolo Carbone
Keyword(s):  
Particle Filter ◽  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Least Square ◽  
Indoor Environments ◽  
Round Trip Time ◽  
Round Trip ◽  
Positioning Systems ◽  
Trip Time ◽  
Non Gaussian

<div><div><div><p>In this paper, a technique for modeling propagation of Ultra Wide Band (UWB) signals in indoor or outdoor environments is proposed, supporting the design of a positioning systems based on Round Trip Time (RTT) measurements and on a particle filter. By assuming that nonlinear pulses are transmitted in an Additive White Gaussian Noise Channel, and detected using a threshold based receiver, it is shown that RTT measurements may be affected by a non-Gaussian noise. RTT noise properties are analyzed, and the effects of non-Gaussian noise on the performance of a RTT based positioning system are investigated. To this aim, a classical Least Square, an extended Kalman Filter and a Particle Filter are compared when used to detect a slowly moving target in presence of the modeled noise. It is shown that, in a realistic indoor environment, the Particle Filter solution may be a competitive solution, at a price of increased computational complexity. Experimental verifications validate the presented approach.</p></div></div></div>

scholarly journals Mobile Positioning Techniques and Systems: A Comprehensive Review

2020 ◽  
Vol 2020 ◽  
pp. 1-18 ◽  
Author(s):  
Arvind Ramtohul ◽  
Kavi Kumar Khedo
Keyword(s):  
Single Type ◽  
Core Element ◽  
Position Information ◽  
Research Issues ◽  
Comprehensive Review ◽  
Positioning Systems ◽  
Hybrid Techniques ◽  
Systems Research ◽  
Mobile Positioning ◽  
Positioning Technique

The recent developments in mobile positioning technologies and the increasing demands of ubiquitous computing have significantly contributed to sophisticated positioning applications and services. Position information represents a core element in the human-centred activities, assisting in visualising complex environments effectively and providing a representational coordinate for localisation, tracking, and navigation purposes. The emergence of smartphones has accelerated the development of cutting-edge positioning-based systems since they are contained to have more processing, memory, and battery power. Similarly, mobile devices are now equipped with new sensory capabilities, wireless communications, and localisation technologies. This has quadrupled towards new advances on positioning techniques, enhancing the existing ones and brought more value to positioning-based systems. Research studies in positioning techniques have progressed in different directions, and no work has categorised and assessed the various advancements in this area. Accuracy and precision are the two challenging aspects that are crucial to the proper functioning of a positioning system. In practice, there is not a single positioning technique that could be appropriate for different situations. Most of the survey papers have focussed on carrying out their review on conventional positioning techniques. The common positioning technique uses simple technologies and is applied to a single type of environment. Hybrid techniques are the next generation of positioning technique that is supporting the real and com plex environment. This paper presents a comprehensive review on the mobile positioning techniques and systems. A total of 21 positioning systems published between the years 2012 and 2018 in the top 5 most popular indexed databases are reviewed. The positioning techniques are identified and streamlined through a methodical process, and the selected ones are reviewed using derived parameters. This paper provides a significant review of the current state of the mobile positioning techniques and outlines the research issues that require more investigation.

scholarly journals Smartphone-Based 3D Indoor Pedestrian Positioning through Multi-Modal Data Fusion

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4554 ◽  
Author(s):  
Hongyu Zhao ◽  
Wanli Cheng ◽  
Ning Yang ◽  
Sen Qiu ◽  
Zhelong Wang ◽  
...  
Keyword(s):  
Particle Filter ◽  
Inertial Sensors ◽  
Dead Reckoning ◽  
Vertical Displacement ◽  
Location Based Services ◽  
Map Matching ◽  
Matching Algorithm ◽  
Positioning Systems ◽  
Indoor Location ◽  
Wall Crossing

Combining research areas of biomechanics and pedestrian dead reckoning (PDR) provides a very promising way for pedestrian positioning in environments where Global Positioning System (GPS) signals are degraded or unavailable. In recent years, the PDR systems based on a smartphone’s built-in inertial sensors have attracted much attention in such environments. However, smartphone-based PDR systems are facing various challenges, especially the heading drift, which leads to the phenomenon of estimated walking path passing through walls. In this paper, the 2D PDR system is implemented by using a pocket-worn smartphone, and then enhanced by introducing a map-matching algorithm that employs a particle filter to prevent the wall-crossing problem. In addition, to extend the PDR system for 3D applications, the smartphone’s built-in barometer is used to measure the pressure variation associated to the pedestrian’s vertical displacement. Experimental results show that the map-matching algorithm based on a particle filter can effectively solve the wall-crossing problem and improve the accuracy of indoor PDR. By fusing the barometer readings, the vertical displacement can be calculated to derive the floor transition information. Despite the inherent sensor noises and complex pedestrian movements, smartphone-based 3D pedestrian positioning systems have considerable potential for indoor location-based services (LBS).

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