Bayesian filters for ToF and RSS measurements for indoor positioning of a mobile object

Galov, Aleksandr; Moschevikin, Alex

doi:10.1109/ipin.2013.6817845

Cited by 15 publications

(6 citation statements)

References 9 publications

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“…They are now capable to provide a reasonable accuracy also under harsh indoor environments, as could be shown in [1], [2] and many others. [3], [4] show that applications can even include safety-related underground longwall mining infrastructure.…”

Section: Introductionmentioning

confidence: 83%

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On the possibility to use leaky feeders for positioning in chirp spread spectrum technologies

Moschevikin

Serezhina

Sikora

2014

2014 2nd International Symposium on Wireless Systems Within the Conferences on Intelligent Data Acquisition and Advanced Comput

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Real Time Localization Systems using electromagnetic waves have significantly evolved during the last years. They also might be used in industrial and in mining environments. Here, topologies might include tunnels, where it might be difficult to ensure the field coverage. Leaky feeder cables are a common solution in case of normal radio communication.In this paper, we study the possibilities to use leaky feeders also for Time-of-Flight based real time localization in such linear topologies, like tunnels, but possibly also for 2Dlocalization. Theoretical analysis is verified with real-life measurements, which were performed using Chirp Spread Spectrum Technologies.

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Section: Introductionmentioning

confidence: 83%

“…According to (2) it was assumed that the slope of this line s = −0.25 dB/m would correspond to the longitudinal losses α = 0.14 dB/m of the RMC 12-HLFR leaky feeder (see Table II). As occured, s is significantly higher than α.…”

Section: A Experiments 1 Velocity Factormentioning

confidence: 99%

On the possibility to use leaky feeders for positioning in chirp spread spectrum technologies

Moschevikin

Serezhina

Sikora

2014

2014 2nd International Symposium on Wireless Systems Within the Conferences on Intelligent Data Acquisition and Advanced Comput

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“…The Bluetooth-based indoor navigation with ToF range sensor fusion could show an efficient performance in real-time embedded implementations. Furthermore, Ultrasonic and Time-of-Flight sensors could present the precision of 1–5 m in harsh environments with more involved geometry [ 13 , 14 , 15 ]. Although these systems used wireless sensor networks and different accurate measurements, their performances are partially dependent on the building’s complexity, fusion method and, somewhat for Ultrasonic methods, the system cannot locate the pedestrian without the anchors and tags.…”

Section: Related Workmentioning

confidence: 99%

Applying a ToF/IMU-Based Multi-Sensor Fusion Architecture in Pedestrian Indoor Navigation Methods

Farhangian

Sefidgar

Landry

2021

Sensors

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The advancement of indoor Inertial Navigation Systems (INS) based on the low-cost Inertial Measurement Units (IMU) has been long reviewed in the field of pedestrian localization. There are various sources of error in these systems which lead to unstable and unreliable positioning results, especially in long term performances. These inaccuracies are usually caused by imperfect system modeling, inappropriate sensor fusion models, heading drift, biases of IMUs, and calibration methods. This article addresses the issues surrounding unreliability of the low-cost Micro-Electro-Mechanical System (MEMS)-based pedestrian INS. We designed a novel multi-sensor fusion method based on a Time of Flight (ToF) distance sensor and dual chest- and foot-mounted IMUs, aided by an online calibration technique. An Extended Kalman Filter (EKF) is accounted for estimating the attitude, position, and velocity errors, as well as estimation of IMU biases. A fusion architecture is derived to provide a consistent velocity measurement by operative contribution of ToF distance sensor and foot mounted IMU. In this method, the measurements of the ToF distance sensor are used for the time-steps in which the Zero Velocity Update (ZUPT) measurements are not active. In parallel, the chest mounted IMU is accounted for attitude estimation of the pedestrian’s chest. As well, by designing a novel corridor detection filter, the heading drift is restricted in each straightway. Compared to the common INS method, developed system proves promising and resilient results in two-dimensional corridor spaces for durations of up to 11 min. Finally, the results of our experiments showed the position RMS error of less than 3 m and final-point error of less than 5 m.

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“…As a rule, zones do not contain walls and partitions. During the installation of the location system signal strength map of access points is built [5,6]. Typically, the signal strength of the access point map is formed from the average values of its signal strength in each zone ("fingerprinting").…”

Section: задача оптимального размещения точек доступа системы позициоmentioning

confidence: 99%

The problem of optimal placement of access points for the indoor positioning system

Voronov¹

2017

Vestnik SPbSU. Applied Mathematics. Computer Science. Control P

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This paper deals with an indoor positioning system. The system is based on the use of wireless local area network access points. A location calculation engine is based on Bayesian algorithms. Location accuracy depends on the number and placement of access points. This paper considers the mathematical model and the method of solving the problem of optimal access point placement for indoor positioning system. The criteria for evaluating the quality of the access points placement is the mathematical expectation of the localization error. We consider two strategies for localization of a mobile object. It is demonstrated that, for some strategies, the addition of access points can possibly increases the expectation errors, for example, the strategy selecting the most probable zone. A strategy, guaranteeing that the addition of access points does not lead to an increase in the expectation errors is proposed. An algorithm for solving the optimization problem is developed. We present the result of testing the algorithm on real data. Refs 16. Fig. 1.

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Bayesian filters for ToF and RSS measurements for indoor positioning of a mobile object

Cited by 15 publications

References 9 publications

On the possibility to use leaky feeders for positioning in chirp spread spectrum technologies

On the possibility to use leaky feeders for positioning in chirp spread spectrum technologies

Applying a ToF/IMU-Based Multi-Sensor Fusion Architecture in Pedestrian Indoor Navigation Methods

The problem of optimal placement of access points for the indoor positioning system

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