| Various methods of implementing Differential Global Positioning Systems (DGPS) are frequently used to correct the ranging errors common to two GPS receivers. One stationary receiver which is referred to as the base. The other stationary or mobile receivers which are commonly called the rovers. These techniques are solved by estimation methods, such as Kalman filtering. The central problem for the GPS receiver is precisely estimating position, velocity, and time based on noisy observations of the satellite signals. Using DGPS techniques reduces the spherical position error deviation to approximately one meter. However, a time delay (latency) in receiving the corrections from the base station can be problematic for real-time implementations. These corrections can be predicted for relatively short period of time at the rover.;This thesis has two main objectives. First, we evaluate a methodology for predicting the corrections which compensates the GPS data in real-time. This methodology is being compared with a standard DGPS method. Second, we estimate the vehicle states (position, velocity, acceleration, and attitude) for real-time navigation and control. |
