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Terrain-Referenced Navigation Using the IGMAP Data Fusion Algorithm

Runnalls, Andrew R., Groves, Paul D., Handley, Robin J. (2005) Terrain-Referenced Navigation Using the IGMAP Data Fusion Algorithm. In: Proceedings of the 61st Annual Meeting of the Institute of Navigation. . pp. 976-986. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:14318)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)


Accuracy and robustness are vital to present and future air navigation, both in the military and civil spheres. The strengths of INS and GPS are well known; integrated INS/GPS systems combine their advantages. However, the knowledge required to jam GPS is becoming public, and it can be carried out with basic hardware. When GPS data are unavailable, and a low grade INS is used, navigation accuracy quickly degrades to an unacceptable level. Terrain-referenced navigation (TRN) techniques - for example, terrain contour navigation based on radio altimeter measurements over undulating terrain - provide a complementary technology: when integrated with INS and GPS, TRN can allow the system to establish and maintain high accuracy even in sustained GPS outages. In a previous paper, the authors explored different techniques for performing the triple integration of TRN, INS and GPS, and found that there were performance advantages if TRN data were processed using a novel data fusion algorithm known as IGMAP; in particular, IGMAP was found to provide more accurate and robust performance over low roughness terrain, which can prove challenging to conventional TRN algorithms. The present paper explores the IGMAP algorithm and its performance in more detail. IGMAP (Iterative Gaussian Mixture Approximation of the Posterior) is an advanced data fusion algorithm for handling non-linear measurements, particularly ambiguous measurements (i.e. measurements for which the likelihood function may be multimodal), in conjunction with a linear or linearisable system model. It is particularly well suited to system models of high dimensionality, and applications where it is desired to interoperate with existing approaches using a Kalman Filter or multi-hypothesis Kalman Filter. Although devised with integrated TRN/INS or TRN/INS/GPS systems in mind, the algorithm has potential applications to other data fusion problems, for example in target tracking. The paper outlines the mathematical foundations of the algorithm, and illustrates its operation using recorded flight data based on the use of an inertial system aided by terrain height information from a radio altimeter.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: terrain-referenced navigation, data fusion, Kalman filter
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:03 UTC
Last Modified: 16 Feb 2021 12:25 UTC
Resource URI: (The current URI for this page, for reference purposes)
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