Integration of radar altimeter, precision navigation, and digital terrain data for low-altitude flight

Avionic systems that depend on digitized terrain elevation data for guidance generation or navigational reference require accurate absolute and relative distance measurements to the terrain, especially as they approach lower altitudes. This is particularly exacting in low-altitude helicopter missions, where aggressive terrain hugging maneuvers create minimal horizontal and vertical clearances and demand precise terrain positioning. Sole reliance on airborne precision navigation and stored terrain elevation data for above-ground-level (AGL) positioning severely limits the operational altitude of such systems. A Kalman filter is presented which blends radar altimeter returns, precision navigation, and stored terrain elevation data for AGL positioning. The filter is evaluated using low-altitude helicopter flight test data acquired over moderately rugged terrain. The proposed Kalman filter is found to remove large disparities in predicted AGL altitude (i.e., from airborne navigation and terrain elevation data) in the presence of measurement anomalies and dropouts. Previous work suggested a minimum clearance altitude of 220 ft AGL for a near-terrain guidance system; integration of a radar altimeter allows for operation of that system below 50 ft, subject to obstacle-avoidance limitations