Alex Moschevikin

A localization system using inertial measurement units from wireless commercial hand-held devices

This paper describes a newly developed technology for the calculation of trajectories of mobile objects, which is based on commercially available sensors being integrated into modern mobile phones and other gadgets. First, a step counting technique was implemented. Second, a novel step length estimator is proposed. These two algorithms utilize the data from accelerometer sensor only. Third, the heading information was obtained using a gyroscope with complementary filter in quaternion form. The combined algorithm was implemented on a low-power ARM processor to provide the trajectory points relative to an initial point. The proposed technique was tested by 10 subjects, in different shoes with different paces. The dependence of the performance of the technology on the attaching point of the mobile device is weak. The proposed algorithms have better balance and estimation accuracy and depend in less degree on the variety in physical parameters of people in comparison with the existing techniques. In experiments inertial measurement units were mounted in different places, i.e. in the hand, in trousers or in T-shirt pockets. The return position error did not exceed 5% of the total travelled distance for all performed tests.

RealTrac Technology Overview

This paper presents the overview of the RealTracTMtechnology developed by the RTL-Service ltd. It is based on the nanoLOC (IEEE 802.15.4a) radio standard. The RealTracTMtechnology features the local positioning system including the possibility of data transfer and voice communication. Radio access is provided by gateway units connected by wired network to a system server. Repeater units are used to increase the radio coverage area. Both gateway and repeater units serve as access points in a system. Channels for voice communication are supported by the Asterisk PBX software installed at the system server. Mobile handheld units periodically enter into active state and initiate the time-of-flight (ToF) ranging. Access points measure received signal strength (RSS) of the incoming radio signal. ToF and RSS data is processed by the server using a particle filter within localization algorithms. The following information is taken into consideration: ToF, RSS, structure of the building, air pressure value and inertial measurement unit data. The developed protocols for the communication in the system are discussed as well.

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

The article describes three different types of Bayesian filtering methods (Kalman filter, particle filter, and grid-based filter) applied for indoor localization in NanoLOC (IEEE 802.15.4a) wireless sensors network. Received Signal Strength, Time-of-flight measurements and the building structure were used for position calculations. The comparison of the applied algorithms revealed conditions at which one algorithm is superior to others. The techniques described in this paper are not depending on the used RF technology.

The impact of NLOS components in Time-of-Flight networks for indoor positioning systems

Ranging errors are inevitable in all local positioning systems, including those based on Time-of-Flight (ToF) technique. Results of experiments show that the major cause for these errors is a signal degradation from multipath propagation. This effect is especially critical in case of Non-Light-of-Sight (NLOS) conditions. This paper describes causes that affects ranging errors for nanoLOC™-TOF-technology and presents estimations for the probability density functions of such errors under different NLOS conditions. The provided estimations allow the improvement of the accuracy of the localization through the subsequent mitigation of the ranging errors from the measurements. Additionally, it is proposed to increase the number of cases of NLOS-conditions for the improvement of the accuracy.

Simultaneous localization and mapping in indoor positioning systems based on round trip time-of-flight measurements and inertial navigation

This paper describes the algorithm for positioning of both indoor base stations and pedestrians in nanoLOC (IEEE 802.15.4a) wireless network. The algorithm uses three sources of information: time-of-flight ranging results between a mobile tag and base stations, the trajectory obtained from an embedded inertial measurement unit, and the map of the building. The iterative algorithm consists of two consequent interconnected stages. The particle filter is used to localize the mobile object on the map, whereas the discrete Bayes filter (grid filter) is applied for estimating the positions of base stations. Time-of-flight non-line-of-sight error distribution function was used as a likelihood in the discrete Bayes filter. Simulation shows that the described SLAM algorithm can be effectively used for setting the initial positions of base stations on the predefined map to save the installation time without significant decrease of localization accuracy. The proposed technique was applied in RealTrac local positioning technology.

Hardware and software architecture of multi mems sensor inertial module

The paper describes the hardware and software architecture of the developed multi MEMS sensor prototype module, consisting of ARM Cortex M4 STM32F446 microcontroller unit, five 9-axis inertial measurement units MPU9255 (3D accelerometer, 3D gyroscope, 3D magnetometer and temperature sensor) and a BMP280 barometer. The module is also equipped with WiFi wireless interface (Espressif ESP8266 chip). The module is constructed in the form of a truncated pyramid. Inertial sensors are mounted on a special basement at different angles to each other to eliminate hardware sensors drifts and to provide the capability for self-calibration. The module fuses information obtained from all types of inertial sensors (acceleration, rotation rate, magnetic field and air pressure) in order to calculate orientation and trajectory. It might be used as an Inertial Measurement Unit, Vertical Reference Unit or Attitude and Heading Reference System.

Automatic signal strength map construction in indoor positioning system based on round trip time of flight measurements and inertial navigation

The accuracy of round trip time-of-flight indoor positioning system can be improved taking into account the measurements of received signal strength. This method requires prior knowledge about received signals strength statistics inside the building. In this paper we propose a method of automatic received signal strength map creation in time-of-flight based indoor positioning system with the help of odometry measurements. The proposed method is based on particle filter and uses distance and signal strength measurements together with the data from an embedded inertial measurement unit and the map of the building. The RSS coverage map consists on the set of discrete bins. When a particle visits a bin the RSS statistics in this bin is sequentially updated using Bayesian inference.

Using radiating cable for time-of-flight CSS measurements indoors and outdoors

The application of leaky feeder (radiating) cables is a common solution for the implementation of reliable radio communication in huge industrial buildings, tunnels and mining environment. This paper explores the possibilities of leaky feeders for 1D and 2D localization in wireless systems based on time of flight chirp spread spectrum technologies. The main focus of this paper is to present and analyse the results of time of flight and received signal strength measurements with leaky feeders in indoor and outdoor conditions. The authors carried out experiments to compare ranging accuracy and radio coverage area for a point-like monopole antenna and for a leaky feeder acting as a distributed antenna. In all experiments RealTrac equipment based on nanoLOC radio standard was used. The estimation of the most probable path of a chirp signal going through a leaky feeder was calculated using the ray tracing approach. The typical non-line-of-sight errors profiles are presented. The results show the possibility to use radiating cables in real time location technologies based on time-of-flight method.

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

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 2D-localization. Theoretical analysis is verified with real-life measurements, which were performed using Chirp Spread Spectrum Technologies.

Using pressure sensors for floor identification in wireless sensors networks

Information on atmospheric pressure may be used in local positioning systems based on wireless sensors networks. This paper discusses the possibility of improving positioning accuracy in multistory buildings. Also pressure sensor data are used to save radio bandwidth and thus to decrease power consumption of radio modules. It is applicable especially in the systems with server-centric control of ranging schedule.