Performance Analysis of Multiple RF Based Advanced Filter for Indoor Localization

Indoor localization is a key feature for everyday life. Indoor environments often contain substantial amounts of metal and other such reflective materials that affect the propagation of radio frequency signals in non-trivial ways, causing severe multi-path effects, dead spots, noise, and interference. The focus of this experiment is to apply the various filtering algorithms to filter the noise from the accrued Radio Frequency (RF) signal and compare the performance of those filters. The experiment has performed in both indoor and outdoor locations. Then filters the outcome by applying different algorithms, e.g. SA-Landmarc algorithm, Cocktail algorithms, and Linear Quadratic Estimation (LQE) algorithm. The experiment has conducted in the indoor and outdoor environment with a distance from 0.5-20m; each time the distance increased by 1m until 20m. XCTU software has used to note down the readings and then convert the input to algorithm to reduce the noise. Learning outcomes help us to analyze the accuracy of the signal and the further approaches, which can help us to reduce the signal noise.

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