Research On Terrain Matching Algorithm Based On Altitude-Entropy

Terrain aided navigation is an important method of integrated navigation at present.Terrain matching algorithm is the basis of terrain aided navigation. Terrain matchingalgorithm based on altitude-entropy is a hot research issues. Traditional altitude-entropyalgorithm has the shortcomings of bad stability, divergent error and poor anti-noiseability. Therefore, how to improve the real-time and accuracy of terrain matchingremains to be furtherly studied. This paper centers on process optimization ofaltitude-entropy terrain matching.Firstly, terrain matching algorithm based on weighted LTS Hausdorff distance isproposed. Weight value formula is constructed. LTS Hausdorff distance weighted isdefined. Because Terrain matching algorithm based on LTS Hausdorff distance hasdisadvantages of low matching efficiency and poor anti-noise ability. Secondly, BeeEvolutionary Genetic Algorithm is improved and Bee Evolutionary Genetic Algorithmbased on tabu search algorithm is proposed. Finally, the combination of BeeEvolutionary Genetic Algorithm improved and LTS Hausdorff distance Weightedoptimize the search process of terrain matching.The results show that LTS Hausdorff distance weighted reduces the noise andisolated points on the matching accuracy of terrain. And the improved Bee EvolutionaryGenetic Algorithm increases convergence rate. It has better global search capability.Terrain matching algorithm designed in this paper has ideal accuracy and robustness.For the improved Bee Evolutionary Genetic Algorithm, the key of the algorithmcapability is how to choose and control parameters. The set of control parameters isbased on other literatures and simulation test in this paper. Thus, it would affect theresult of terrain matching. In the follow-up research work, how to set the properparameters in the algorithm will be studied furtherly.