Real time localization solution for land vehicle application using low-cost integrated sensors with GPS
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| Format: | Artículo científico |
| Langue: | en |
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Universidad Nacional Autónoma de México
2020
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| _version_ | 1876423816520925184 |
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| author | Abdalla Eldesoky |
| author_facet | Abdalla Eldesoky |
| contents | Real time localization solution for land vehicle application using low-cost integrated sensors with GPS Abdalla Eldesoky Ahmed M. Kamel M. Elhabiby Hadia Elhennawy Ingeniería GPS UKF MEMS Multi land vehicle The technique proposed in this research demonstrates a real time nonlinear data fusion solution based on extremely low-cost and grade inertial sensors for land vehicle navigation. Here, the utilized nonlinear multi-sensor data fusion (MSDF) is based on the combination between extremely low-cost micro electrical mechanical systems (MEMS) inertial, heading, pressure, and speed sensors in addition to satellite-based navigation system. The integrated navigation system fuses position and velocity states from the Global Positioning System (GPS), the velocity measurements from an odometer, heading angle observation from a magnetometer and navigation states from an inertial navigation system (INS). The implemented system performance is assessed through the post-processing of collected raw measurements and real time experimental work. The system that runs the real-time experiments is established on three connected platforms, two of them are based on a 32-bit ARMTM core and the third one is based 16-bit AVR ATMEL microcontroller. This microcontroller is connected to an on-board diagnostics (OBD) shield to collect the vehicle speed measurements. The raw data obtained from the integrated sensors is saved and post processed in MATLAB®. In normal conditions, the estimated position errors are reduced through the usage of INS/GPS integration with heading observation angle from a magnetometer. In GPS-denied environments, the integrated system uses the observations from INS, magnetometer in addition to the velocity from odometer to ensure a continuous and accurate navigation solution. A complementary filter (CF) is implemented to estimate and improve the pitch and roll angles calculations. In addition to that, an unscented Kalman filter (UKF) is used cascaded with the designed CF to complete the designed sensors fusion algorithm. Experimental results show that the designed MSDF can achieve a good level of accuracy and a continuous localization solution of a land vehicle in different GPS availability cases and can be implemented on the available in the market processors to be run in real time. 2020 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47471673007 https://www.redalyc.org/journal/474/47471673007/ https://www.redalyc.org/journal/474/47471673007/html/ https://www.redalyc.org/journal/474/47471673007/47471673007.epub https://www.redalyc.org/journal/474/47471673007/movil 10.14482/INDES.30.1.303.661 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.4 Vol.18 |
| format | Artículo científico |
| id | redalyc_47471673007 |
| institution | Redalyc |
| language | en |
| publishDate | 2020 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Real time localization solution for land vehicle application using low-cost integrated sensors with GPS Abdalla Eldesoky Ingeniería GPS UKF MEMS Multi land vehicle Real time localization solution for land vehicle application using low-cost integrated sensors with GPS Abdalla Eldesoky Ahmed M. Kamel M. Elhabiby Hadia Elhennawy Ingeniería GPS UKF MEMS Multi land vehicle The technique proposed in this research demonstrates a real time nonlinear data fusion solution based on extremely low-cost and grade inertial sensors for land vehicle navigation. Here, the utilized nonlinear multi-sensor data fusion (MSDF) is based on the combination between extremely low-cost micro electrical mechanical systems (MEMS) inertial, heading, pressure, and speed sensors in addition to satellite-based navigation system. The integrated navigation system fuses position and velocity states from the Global Positioning System (GPS), the velocity measurements from an odometer, heading angle observation from a magnetometer and navigation states from an inertial navigation system (INS). The implemented system performance is assessed through the post-processing of collected raw measurements and real time experimental work. The system that runs the real-time experiments is established on three connected platforms, two of them are based on a 32-bit ARMTM core and the third one is based 16-bit AVR ATMEL microcontroller. This microcontroller is connected to an on-board diagnostics (OBD) shield to collect the vehicle speed measurements. The raw data obtained from the integrated sensors is saved and post processed in MATLAB®. In normal conditions, the estimated position errors are reduced through the usage of INS/GPS integration with heading observation angle from a magnetometer. In GPS-denied environments, the integrated system uses the observations from INS, magnetometer in addition to the velocity from odometer to ensure a continuous and accurate navigation solution. A complementary filter (CF) is implemented to estimate and improve the pitch and roll angles calculations. In addition to that, an unscented Kalman filter (UKF) is used cascaded with the designed CF to complete the designed sensors fusion algorithm. Experimental results show that the designed MSDF can achieve a good level of accuracy and a continuous localization solution of a land vehicle in different GPS availability cases and can be implemented on the available in the market processors to be run in real time. 2020 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47471673007 https://www.redalyc.org/journal/474/47471673007/ https://www.redalyc.org/journal/474/47471673007/html/ https://www.redalyc.org/journal/474/47471673007/47471673007.epub https://www.redalyc.org/journal/474/47471673007/movil 10.14482/INDES.30.1.303.661 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.4 Vol.18 |
| title | Real time localization solution for land vehicle application using low-cost integrated sensors with GPS |
| topic | Ingeniería GPS UKF MEMS Multi land vehicle |
| url | https://www.redalyc.org/articulo.oa?id=47471673007 https://www.redalyc.org/journal/474/47471673007/ https://www.redalyc.org/journal/474/47471673007/html/ https://www.redalyc.org/journal/474/47471673007/47471673007.epub https://www.redalyc.org/journal/474/47471673007/movil |