1. An on-board state estimation system for an aerial vehicle, the system comprising: a computer database that stores a pre-loaded digital elevation model (DEM) for a ground surface over which the aerial vehicle is to fly; a sensor suite comprising one or more sensors, wherein the one or more sensors comprise: an altitude sensor for sensing an above-ground altitude of the aerial vehicle; one or more downward-pointed cameras such that the one or more cameras are pointed at the ground when the aerial vehicle is in the air; and at least one downward-pointing laser scanner such that the at least one downward-pointing laser scanner is pointed at the ground surface when the aerial vehicle is in the air; means, responsive to the sensor suite, for determining local, relative, continuous state estimates of the aerial vehicle as it moves, wherein the means for determining the local, relative, continuous state estimates comprise: a visual odometry (VO) system that is in communication with the one or more downward-pointed cameras and the altitude sensor, wherein the VO system continuously computes updated local state estimates of the aerial vehicle by comparing time-stamped ground surface images taken at different points in time, using the sensed altitude of the aerial vehicle from the altitude sensor for scaling the time-stamped ground surface images; and an inertial measurement unit (IMU) that is in communication with the one or more motion sensors and continuously measures acceleration of the aerial vehicle in three dimensions and angular velocities for roll, pitch and yaw for the aerial vehicle based on input from motion sensors that detect motion of the vehicle; means, responsive to the sensor suite, for determining global, absolute, noncontinuous state estimates of the aerial vehicle as it moves, wherein the means for determining the global, absolute, noncontinuous state estimates comprise terrain referenced navigation means; and state estimation means for determining continuously updated state estimates for the aerial vehicle as it moves without a need for GNSS coordinates by combining the local, relative, continuous state estimates with the global, absolute, noncontinuous state estimates.