Araç Parçalarının MEMS Manyetometre Sensör Çıktısına Etkisi

Year 2020, Volume: 35 Issue: 1, 11 - 18, 31.03.2020

Murat Bakırcı

https://doi.org/10.21605/cukurovaummfd.764331

Abstract

Birçok Akıllı Ulaşım Sistemi (AUS) için araçların yön bilgisinin hassasiyeti oldukça önemlidir. GPS- tabanlı konumlandırma ve yön tahmini neredeyse bütün ulaşım sistemlerinde yaygın olarak kullanılmaktadır. Fakat şehir merkezlerindeki çevresel etmenler nedeniyle GPS sinyali algılamasında tutarsızlıklar meydana gelmektedir. Mobil cihazlarda bulunan jiroskop, ivme ölçer, manyetometre gibi Mikroelektromekaniksel Sistem (MEMS) sensörleri, taşıt dinamiği ölçümlerinde oldukça güçlü bir potansiyele sahip olmak ile birlikte taşıtlarda yön tahmini ile ilgili çalışmalar yapabilmek için de oldukça elverişlidir. Akıllı mobil cihazlardaki manyetometre sensörleri, hassas yön tahmini yapabilmek için kullanışlı duruma getirilebilirler. Fakat manyetometre sensörü tarafından ölçülen manyetik alan verisi, taşıtın ferromanyetik parçaları nedeni ile ciddi şekilde deforme olmaktadır. Bu çalışmada, hata parametreleri saptanarak hassas olarak taşıt yön tahmininin nümerik olarak elde edilebileceği ortaya konmuştur. Hata parametreleri matematiksel bir modele dönüştürülerek etki eden hatalar ham sensör verisinden elimine edilmiştir. Simülasyon sonuçlarına göre modelin ürettiği maksimum hata %3.4’tür.

Keywords

Taşıt yön tahmini, Manyetometre, Ferromanyetik nesne, MEMS sensör, Akıllı ulaşım sistemleri

Effect of the Components of a Vehicle on a MEMS Magnetometer Sensor Output

Abstract

Precise vehicle heading information is of great importance for many Intelligent Transportation Systems (ITS) applications. GPS-based localization and heading estimation is widely used in almost every transportation systems. However, dense urban environment causes inconsistency in the reception of the GPS signals. Given the diverse sensors within mobile devices, i.e., Microelectromechanical System (MEMS) sensors such as gyroscope, accelerometer, magnetometer etc., they have a strong potential for sensing vehicle dynamics and can promote a broad range of applications associated with heading estimation. A magnetometer sensor of a smart mobile device can be utilized to obtain accurate vehicle heading estimation. However, ferromagnetic components of a vehicle significantly deforms the magnetic field measured by magnetometer sensor. In this study, it is demonstrated that an accurate vehicle heading estimation can numerically be achieved through identifying error parameters. These parameters were then transformed into a mathematical model and contributing errors were eliminated from raw sensor output.
Simulation results show that the model produces a maximum error of 3.4%.

Keywords

Vehicle heading estimation, Magnetometer, Ferromagnetic object, MEMS sensor, Intelligent transportation systems

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