As the basis of animalsâ?? natal homing behavior, path integration can continuously provide current position information relative to\nthe initial position. Some neurons in freely moving animalsâ?? brains can encode current positions and surrounding environments\nby special firing patterns. Research studies show that neurons such as grid cells (GCs) in the hippocampus of animalsâ?? brains are\nrelated to the path integration. They might encode the coordinate of the animalâ??s current position in the same way as the residue\nnumber system (RNS) which is based on the Chinese remainder theorem (CRT). Hence, in order to provide vehicles a bionic\nposition estimation method, we propose a model to decode the GCsâ?? encoding information based on the improved traditional selforganizing\nmap (SOM), and this model makes full use of GCsâ?? firing characteristics. The details of the model are discussed in this\npaper. Besides, the model is realized by computer simulation, and its performance is analyzed under different conditions.\nSimulation results indicate that the proposed position estimation model is effective and stable.
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