Bayesian Terrain-aided Inertial Navigation Using Airborne Laser Scanner

When an aircraft with an inertial navigation system stays without an additional treatment (GPS-denied environment, covered area without terrain information) its errors grow during the time due to the sensors and the gravity field uncertainties. So as soon as possible the navigation filter has to reduce this uncertainty in the shortest possible time using other sensor. We take interest in using as other sensor a airborne laser scanner (ALS) with a digital terrain elevation data (value of the terrain elevation as a function of geodetic coordinates). ALS sensor advantage is that it extracts a lot of terrain information in a single time step : the output is multiple distance measurements to the terrain alongside different directions with a very good accuracy. This very nice property might improve the navigation filter precision and so reduce the time until the INS estimates uncertainty is below a certain level. But basic filters diverge when for a more or less long duration in function of INS quality the uncertainty becomes too large. Therefore we studied new filter developed in the Bayesian framework. The objective considered here is the design of a navigation filter in the Bayesian framework to decrease a significantly large uncertainty on INS location estimates in the shortest possible time by combining INS output with an ALS and a digital reference map