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High degree complete orthogonal polynomials to improve distance prediction based on RSSI

Abstract:

An indoor positioning system allows to determine the location of a person or device, when using the GPS is not possible. The use of radiofrequency and RSSI techniques presents advantages regarding cost and infrastructure; however, the signal is very unstable and must be preprocessed to use it successfully in the inference of distance; The more accurate the predicted distance between the receiver and the emitters, the more accurate the determination of the location will be. This work builds on previous studies of signal filtering, improving them by studying the application of non-linear regression techniques, more specifically high-degree polynomial regressions, which provide a better prediction of the pattern followed by the RSSI signal as distance between sender and receiver varies.