目前全球衛星定位系統 (GPS) 已被廣泛應用在車輛導航上。但是GPS訊號容易被遮蔽使得導航發生困難，為了克服這個限制，慣性量測元件(Inertial Measurement Unit)與導航演算法將與GPS接收機整合。現行的GPS/INS整合導航演算法中，一般的做法是使用擴展型卡爾曼濾波器(Extended Kalman Filter)根據GPS及IMU的量測量估算載具的位置及速度。當GPS中斷時，使用INS估算正確的位置、速度及姿態，然而長時間失去GPS訊號時，導航解有可能發散，因此本論文研究的目標為即時估算加速規偏置量(Accelerometer Bias)及陀螺儀漂移量(Gyro Drift)以減緩發散的議題，以確保定位的精準度。

Nowadays, GPS has been applied to vehicle navigation extensively. But the GPS signal is easy to be obstructed, which may make the navigation difficult. In order to overcome this limitation, inertial measurement units with navigation algorithm have been used to integrate with GPS receivers. Existing GPS/INS integration navigation algorithm typically use the Extended Kalman Filter (EKF) to estimate vehicle position and velocity based on GPS and IMU measurements. When GPS is outage, the corrected position, velocity, and attitude estimated from INS can be used. However, the navigation solution may be subject to divergence after GPS signal is lost for a significant period of time. The objective of the thesis is to estimate the accelerometer bias and gyro drift in real time so as to mitigate the divergence issue and guarantee the accuracy of positioning.

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