Airborne vehicle nap-of-the-earth (NOE) flight requires precise pilot control to avoid obstacles and elevated terrain. While the pilot normally relies on good visibility to perform the NOE function, requirements exist for NOE flight during periods of less than good visibility (poor weather or night time conditions). Much practical work has been done on obstacle avoidance systems in which sensors automatically detect physical threats in the flight path--particularly wires; the remaining task necessary to effect NOE flight during periods of zero or poor visibility is navigation.
Airborne (e.g. helicopter) navigation systems are typically of the dead reckoning (DR) variety, usually based on doppler radar and compass systems, and while these systems offer excellent short term guidance capability, they exhibit unacceptable long term position error growth, so that some form of in-flight correction procedure, such as periodic position updating of the dead reckoning navigation system, is necessary. Unfortunately, currently available radio aids (even assuming their presence in the vehicle's operational area) are generally unsatisfactory to support NOE flight conditions where line of sight communications is not possible.
One proposal to solve this problem has been the concept of employing terrain correlation techniques whereby the aircraft's position as determined by its navigation system is updated as a function of overflown terrain and its elevation heights and height variations. Examples of such terrain correlation schemes include TERrain Contour Matching (TERCOM) and Sandia Inertial Terrain Aided Navigation (SITAN). (For a discussion of TERCOM and SITAN proposals that have been investigated, attention may be directed to articles entitled "Continuous Kalman Updating of an Inertial Navigation System Using Terrain Measurements" by R. D. Andreas et al., Sandia National Laboratories, pg. 1263-1270, 1978 IEEE; "An Alternative Approach for Terrain-Aided Navigation Using Parallel Extended Kalman Filters" by T. C. Sheives et al., Sandia National Laboratories, Albuquerque, N. Mex., Dec. 1979; and "Application of Multiple Model Estimation Techniques to a Recursive Terrain Height Correlation System" by W. Tang et al., pg. 757-764, IEEE 1981. Also, attention may be directed to the U.S. patents to Evans et al. U.S. Pat. No. 4,179,693; Webber U.S. Pat. No. 4,144,571; Thomas et al. U.S. Pat. No. 4,103,847; and Blatchford U.S. Pat. No. 3,992,613 for further background information that provides an illustration of conventional guidance and navigation systems that compare altimeter information with stored data for guidance.)
Unfortunately both of the TERCOM and SITAN approaches suffer from a number of drawbacks which limit their performance and accuracy. For example, in the TERCOM system, navigation accuracy is limited by the correlation distance S.sub.T, which is defined by using the covariance function in the spatial domain. It is usually a function of terrain characteristic and is typically on the order of several hundred meters. Such a long correlation distance limits the use of TERCOM for high-precision navigation systems (such as a helicopter-borne NOE system which requires an accuracy on the order of 100 m). In order to achieve good accuracy using TERCOM, a long integration path length, typically on the order of 10Km, must be used. Such a long integration distance requires that an extremely large quantity of terrain data be stored for the terrain correlation. The TERCOM correlation algorithms that are currently being employed are incapable of providing good accuracy in a high noise environment, such as a highly inaccurate inertial navigation system (INS) that contains large velocity, altitude, acceleration and gyro, etc. errors. Finally, existing TERCOM systems store non-compressed terrain data for terrain correlation, which limits the practical ground coverage of the navigation system.
In the SITAN system, terrain linearization is required such that a linearized terrain measurement model can be incorporated into Kalman filter of the navigation system. As a result of the linearization process, the filter has a small region of convergence, and thus diverges when the navigation system is required to operate with a large uncertainty region (e.g. after a period of over-water navigation, or at the start of the navigation process). Usually, the SITAN system diverges when the uncertainty region is larger than several hundred meters. In addition, the SITAN system stores data for terrain correlation in a non-compressed format, so that for long missions, data storage becomes a problem.