The military depends on the Global Positioning System (GPS) for a wide array of advanced weaponry guidance and precision navigation systems. Lack of GPS access makes precision navigation very difficult. Inclusion of inertial sensors in existing navigation systems provides short-term precision navigation, but drifts significantly over long-term navigation. This thesis is motivated by the need for inertial sensor drift-constraint in degraded and denied GPS environments. The navigation system developed consists of inertial sensors, a simulated barometer, three Raytheon DH500 radios, and a stereo-camera image-aiding system. The Raytheon DH500 is a combat comm radio which also provides range measurements between radios. The measurements from each sensor are fused together with an extended Kalman filter to estimate the navigation trajectory. Residual monitoring and the Sage-Husa adaptive algorithm are individually tested in the Kalman filter range update algorithm to help improve the radio range positioning performance. The navigation system is shown to provide long-term inertial sensor drift-constraint with position errors as low as 3 meters.