A new measurement model of interferometric radar altimeter for terrain referenced navigation using particle filter

This paper proposes a novel method of grafting one of the measurements of interferometric radar altimeter (IRA) onto particle filter that uses sequential importance resampling (SIR) to enhance the performance of terrain referenced navigation (TRN). IRA which is a terrain sensor that measures slant range, slant angle and look angle to the closest terrain point from the aircraft is introduced. The procedure of numerically replicating the measurements of IRA when the position, velocity, and attitude of aircraft, and the terrain database is given is provided herein this paper. Although the degree of accuracy of IRA measurements is higher than radar altimeter (RA), performance of TRN that utilizes IRA stays in a similar level with RA-aided TRN or becomes even worse because the way of utilizing IRA measurements remains unchanged. Proposed method estimates the slant range from each of the particles to their closest terrain point to update the position of an aircraft. Numerical simulations that use actual terrain database is presented to observe the performance of proposed method in comparison with typical TRN that utilizes RA and another that makes use of IRA measurements in a conventional manner. Performance of TRN with proposed method gets improved in terms of root mean square error of aircraft's 2D position and initial position error correction.