Position fix in terrain referenced navigation using statistical verification

In this study, a method for retaining the uniqueness of terrain shape and updating using a t-test is proposed using a batch processing algorithm. Using a correlation algorithm, the batch processing algorithm provides a position fix which is then utilised as input to a Kalman filter to compensate for navigation error in a terrain referenced navigation (TRN) system. However, a positional false fix can occur over flat or repetitive terrain, which then causes the navigation solution to diverge. The aim of this study is to prevent the batch processing algorithm from providing a positional false fix by extending the profile length to allow it to incorporate a uniqueness of terrain. A method for reducing computation time is also proposed using an error covariance of measurement. In addition, the use of a t-test is proposed to help provide a stable navigation solution. Numerical simulations are performed to evaluate the performance of the proposed method, and the results show that the proposed method performs better than a general batch processing TRN.