The Global Positioning System (GPS) is widely used in most of the military and civilian applications because of its precision navigation capability. Unfortunately, GPS is not available in all environments (e.g., indoors, under sea, under ground, or jamming environment). The motivation of this research is to address the limitations of GPS by using star trackers as an attitude update to an inertial navigation systems (INS). Commercial, tactical, and navigation grade INS are modeled and simulated with measurements from GPS, star tracker, and barometer. GPS measurements are used to update the INS position and velocity for a small duration in the beginning of the vehicle?s flight time. Star tracker and barometer measurements are used to update the INS attitude and altitude, respectively. This research uses a Linear Kalman Filter as a recursive estimation system, to estimate the INS errors (i.e. position, velocity, tilts, accelerometer bias, gyroscope bias, and barometer bias) using the three types of measurement updates. The simulation results show that the star tracker was able to improve the performance of the commercial and tactical grades INS, for any duration of the vehicle's flight time. Also, the improvement in the performance of the navigation grade INS was not significant until the vehicle?s flight time was more than approximately 1000 seconds. Also, the research shows the performance impact on the three INS grades when using different star tracker accuracies.