A low-cost IMU/GPS position accuracy experimental study using extended kalman filter data fusion in real environments

Fatimi, Aziz El; Addaim, Adnane; Guennoun, Zouhair

doi:10.1051/e3sconf/202129701040

Cited by 3 publications

(3 citation statements)

References 16 publications

(22 reference statements)

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“…The three basic noise terms are angle random walk (N), bias instability (B), and rate random walk (K). Assuming that manufacturing uncertainties such as scale factor and misalignment uncertainties are neglected (stationary state W ideal t ( ) = 0), the gyroscope output measurement can be modeled by the formula as follow [11,18,19].…”

Section: Gyroscope Stochastic Modelmentioning

confidence: 99%

Development of a hardware emulator of a nanosatellite gyroscope

2023

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The gyroscope sensor has multiple applications in consumer electronics, aircraft navigation, and control systems. Significant errors that match the corresponding data are a typical disadvantage of this sensor. This needs to be done by making error models that can be used to get the right level of measurement accuracy. For high-precision space applications, the navigation design system should take into account the angle random walk (N), bias instability error (B), and rate random walk (K) of the BMG160 gyroscope. For this reason, this paper shows how to use Allan Variance (AVAR) and Power Spectral Density (PSD) for the experimental identification and modeling of the stochastic parameters of the Bosch BMG160 gyroscope embedded in a nanosatellite in order to get an accurate gyroscope model. This work also demonstrates the principle of operation of the equivalent electronic model intended to carry out advanced simulations without recourse to the real material in order to avoid the problem of bad manipulation and availability of the material in order to reduce the time and cost of development. The interpretation of the Allan curves and the PSD obtained from the measurements collected over a long period is presented, as well as a comparison between the real raw data of the BMG160 gyroscope and the designed hardware emulator in both the time and frequency domains. This is done to evaluate the accuracy of the gyroscope model emulating the real sensor in laboratory simulations. The experimental results show that the signals from the emulator and the BMG160 gyroscope are quite close. Therefore, the proposed prototype could be an optimal solution for laboratory calculations and simulations

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Section: Gyroscope Stochastic Modelmentioning

confidence: 99%

Development of a hardware emulator of a nanosatellite gyroscope

2023

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“…The authors of [9] proposed to collect such data, not solely within the roundabout, but also 100 m (including segmentation of this length) before entering and after exiting such road features. The authors of [10] developed a system for data collection on various types of infrastructure (this system requires a GPS receiver coupled with a threeaxis accelerometer, a three-axis gyroscope, and a three-axis magnetometer). According to the authors, this elaborate system worked promisingly in a city, on a designated section of highway at a speed of 120 km/h, and on a roundabout.…”

Section: Literature Reviewmentioning

confidence: 99%

Calculation of an Average Vehicle’s Sideways Acceleration on Small Roundabouts

Jagelčák

Gnap

Kostrzewski

et al. 2022

Sensors

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The calculation of the average sideways acceleration, based on speed and angular velocity on small roundabouts for a vehicle of up to 3.5 t gross vehicle mass, is described in this paper. Calculations of the turning radius are derived from angular velocity and an automatic selection of events, based on the lateral acceleration of the coefficient of variation within a defined time window. The calculation of the turning radius based on speed and angular velocity yields almost identical results to the calculation of the turning radius by the three-point method using GPS coordinates, as described in previous research. This means that the calculation of the turning radius, derived from the speed of GNSS/INS dual-antenna sensor and gyroscope data, yields similar results to those from the computation of the turning radius derived from the coordinates of a GNSS/INS dual-antenna sensor. The research results can be used in the development of sensors to improve road safety.

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“…In contrast, if it is positive, it suggests the vehicle is moving with an orientation to the east. Negative indicates the direction to the west (the speed value always reads positive, even though the y-axis has a negative value because the negative sign is used for readings heading orientation) [35], [38]. to 315th second until it is determined that the vehicle is moving northeast (opposite to the initial direction) at the velocity value indicated by the y-axis coordinate.…”

Section: Figure 6 Navigation Routes Based On Gnss Data In Meter Formatmentioning

confidence: 99%

The Impact of Telemetry Received Signal Strength of IMU/GNSS Data Transmission on Autonomous Vehicle Navigation

Khosyi’in

Prasetyowati

Suprapto

et al. 2022

IJEEI

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This paper presents the effect of received signal strength on IMU/GNSS sensor data transmission for autonomous vehicle navigation. A pixhawk 2.1 flight controller is used to build the navigation system. Straight lines with back-andforth routes were tested using two types of SiK telemetry: Holybro and RFD. The results of the tests show that when the RSSI value falls close to the receiver's sensitivity value, the readings of the gyro sensor data, accelerometer, magnetometer, and GNSS compass data are disturbed. When the RSSI signal collides with noise, the radio telemetry link is lost, affecting the accuracy of speed data and the orientation of autonomous vehicles. According to Cisco's conversion table, the highest RSSI on Holybro telemetry is -48 dBm, and the lowest is -103 dBm, with a receiver sensitivity of -117 and data reading at a distance of about 427 meters. While the highest RSSI value on RFD telemetry is -17 dBm and the lowest is -113 dBm, even the lowest value is above the receiver's sensitivity limit of -121 dBm with data readings at a distance of approximately 749.4 meters. RFD outperforms Holybro in terms of RSSI and sensitivity at low data rates. When reading distance data to reference distance data using Google Earth and ArcGIS, RFD telemetry has a higher accuracy, with an average accuracy of 98.8%.

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A low-cost IMU/GPS position accuracy experimental study using extended kalman filter data fusion in real environments

Cited by 3 publications

References 16 publications

Development of a hardware emulator of a nanosatellite gyroscope

Development of a hardware emulator of a nanosatellite gyroscope

Calculation of an Average Vehicle’s Sideways Acceleration on Small Roundabouts

The Impact of Telemetry Received Signal Strength of IMU/GNSS Data Transmission on Autonomous Vehicle Navigation

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