This paper proposes a vision-integrated navigation system to guide an aircraft on the final glide path. It makes use of onboard vision systems which track runway features and estimate a 6D aircraft pose with respect to a runway to land. The proposed vision-integrated navigation system will allow an aircraft to continue the final approach procedure by maintaining the navigation precision in case of possible degradation or failure of ILS or GNSS/SBAS sensors. In order to handle a non-negligible delay of such vision-based measurements due to the image processing time, an error-sate Kalman filter (ESKF) framework incooporating time-delayed measurements is established. The proposed delayed-measurement ESKF framework uses a fact that camera image acquisitions are triggered by a system and hence can be notified without delay. This enables the navigation filter to perform back-propagation of the estimated state forward in time to prepare for the future correction step at the time the measurement becomes available. The vision-integrated navigation system based on this framework was developed and its functionality is validated in simulations. Its estimation performance will be flight-evaluated with two different vision systems onboard a fixed-wing UAV experimental platform.