This study applies the AKF as the core estimator of a tightly-coupled INS/GPS integration scheme by tuning the measurement noise matrix R adaptively. The innovation sequence is used to derive the measurement weights through the covariance matrices R, which is known as innovation-based adaptive estimation. In the innovation-based adaptive estimation method implemented in study, the covariance matrix R are adapted when measurement update become available with time. A window based approach is implemented to reflect the quality of GPS pseudorange measurements by adaptively replace the measurement weights through the latest estimated covariance matrix R. To validate the performance of proposed AKF based tightly coupled INS/GPS integration scheme, a simulation scenario and a field test was conducted in the downtown area of Tainan city, respectively. The IMUs applied includes SPAN-CPT (1 deg/hr in run gyro bias) from NovAtel, which was used as the reference system, and one low end tactical grade IMU was applied as the test system. The preliminary results indicate the proposed algorithm is able to improve the accuracies of positional and orientation components of EKF based tightly coupled integration scheme by 70% and 70% in average respectively with the use of simulated measurements. In addition, the improvement ratio of proposed algorithm reaches 25% in positional components with the use of field test measurements. Consequently, the proposed AKF based tightly coupled INS/GPS integration scheme can provide the most consistent navigation solutions with sufficient sustainability in urban area.