THE AUTOMATIC GENERATION OF AN ADAPTIVE NAVIGATION MODEL FOR INDOOR MAP MATCHING
Indoor map matching has been an important technique to improve the indoor localization accuracy because it takes the advantage of available indoor building data and effectively decreases the localization cost. One of the spatial model involved in the indoor map matching, adaptive navigation model, could balance the accuracy and complexity of the model representation required by map matching by combining the medial axes and fine-grained grids according to the movement characteristics of pedestrians in open and narrow areas. In order to reduce the manual effort of producting a large number of models and update them, we propose an algorithm to automatically generate this model. Futermore, we use this algorithm to generate this model for three lab architectures, and the evaluation of the results of the ANM generated by the algorithm proves that the algorithm meets the requirements.