近年來由於微機電(MEMS)系統快速發展與技術的成熟，低價位的慣性導航裝置已經能應用於車輛的定位研究之上。利用車輛在平面道路之約束條件運動模式，一組二維的加速儀就可以進行導航定位。本論文則使用多個微型感測器的定位系統來適時修正單一組加速儀定位的不足。我們主要使用三個微型感測器：電子羅盤、加速儀與陀螺儀，利用單晶片微處理器(PIC16F88)為溝通介面，將三個感測器結合起來，組合成一個定位系統裝置。感測器的信號處理首先根據電子羅盤及加速儀之間雜訊特性的差異，運用較為簡易的互補濾波器進行信號整合；最後利用車輛在慣性座標下的位置路徑、體座標上的速度與加速度，以及二維平面車輛之約束條件運動下的運動方程式與感測器雜訊為系統狀態，運用擴展式卡爾曼濾波器來進行車輛的方位與路徑估測並抑制雜訊彼此的漂移。

Recent years progress in the field of micro-electro-mechanical system (MEMS) has made low cost inertial devices become a possible option for land vehicle. In the hardware implementation part of this thesis, we discussed characteristics and interface designs for various sensors. In the digital signal process theoretical, first we designed a complementary filter according to the sensors noise characteristic. Then we designed a Kalman filter to integrate the compass, accelerometer, and gyroscope sensors output. By using the relationship between the constrain motion of the vehicle positions, speeds, accelerations, and sensors noises, sensor noise and drifts are effectively removed.

[1] http://www.gpsworld.com

[2] http://www.nasa.gov

[3]http://www.hq.nasa.gov/office/pao/History/alsj/4gimb.jpg

[4]http://xenia.media.mit.edu/~verp/projects/smartpen/img3.gif

[5] Microchip, “PIC16F88 Data Sheet”, 2003.

[6] Michael J. Caruso, “Applications of Magnetoresistive Sensors in Navigation Systems”, Honeywell Inc., 2003.

[7] Robert Grover Brown, Patrick Y.C Hwang, “Introduction to Random Signals and Applied Kalman Filtering” , second edition, Wiley, 1992.

[8] Greg Welch, Gary Bishop, “An Introduction to the Kalman Filter”, Department of Computer Science University of North Carolina at Chapel Hill, NC 27599-3175, September 17, 1997.

[9] Mohinder S. Maybeck, Angus P. Andrews, “Kalman Filtering Theory and Practice ”, 1993.

[10] Xin Ma, Salah Sukkarieh, Jong-Hyuk Kim, “Vehicle Model Aided Inertial navigation”, IEEE, May 26 2003.

[11] Mohinder S. Grewal and Angus P. Andrews, “Klman Filtering Theory and Practice Using Matlab”, Prentice Hall, Inc, 2001.

[12] Young Soo Suh, “Attitude Estimation Using Low Cost Accelerometer and Gyroscope”, Proceeding of 7th Korea-Russia International Symposium, KORUS 2003.

[13] Masatoshi Hoshino, Yasuhiro Gunji, Shigeru Oho, Kenji Takano, “A Kalman Filter to Estimate Direction for Automotivr Navigation”, Proceedings of the IEEE, 1996.

[14] F. X. Cao, D. K. Yang, A. G. Xiao, C. L. Law, K. V. Ling, H. C. Chua, “Low caost SINS/GPS Integration for Land Vehicle Navigation”, IEEE 5th International Conference on Intelligent Transportation Systems 3-6, September 2002.

[15]高維文(1995)，地面車輛定位及導航系統，行政院國科會專題研究計劃，台灣工業技術學院機械系，台北。

[16]黃振文(1996)，全球定位系統與慣性導航系統整合之車輛導航系統設計，碩士論文，中華工學院航太工程研究所，新竹。

[17]郭侃誠(1996)，結合GPS與INS之實驗船定位系統研究，碩士論文，台灣科技大學機械工程研究所，台北。

[18]黃國興，慣性導航系統原理與應用，全華科技圖書，台北，1996。

[19]蘇茂舜(2001)，車輛導航用之微機電加速儀研究，碩士論文，中華大學機械與航太研究所，新竹。

[20]楊憲東，自動飛行控制原理與實務，全華科技圖書，ISBN 957-21-3354-3，台北，2002。

[21]莊智清、黃國興，e-navigation電子導航，全華科技圖書，ISBN 957-21-3154-0，台北，2003。