Fuzzy logic for robust detection in wireless communications

This work addresses the problem of spatial reference estimation in mobile scenarios. Novel techniques based on fuzzy logic are introduced to enhance the performance of a tracking system. Specifically, the model-free function approximation capability of fuzzy logic is used to obtain high resolution angle estimates from the spatial spectral density. These estimates are used to improve the resolution of the tracker. To the authors knowledge it is the first time that fuzzy logic is introduced in array spectral estimation. This work also develops a fuzzy controller for acting as an interpolative supervisor of different trackers that apply in different operating conditions of the dynamic nonlinear system. The result is a localization and tracking system that attains a resolution comparable to that of high resolution techniques as the minimum variance or Capon estimator. One of the main features of the proposed technique is its low computational burden. In summary, the presented system supports the expectation of adaptive arrays for obtaining a communication front-end of affordable complexity, developing cost and good performance.