Inomhuspositionering med bredbandig radio

Sammanfattning: In this report it is evaluated whether a higher dimensional fingerprint vector increases accuracy of an algorithm for indoor localisation. Many solutions use a Received Signal Strength Indicator (RSSI) to estimate a position. It was studied if the use of the Channel State Information (CSI), i.e. the channel’s frequency response, is beneficial for the accuracy.The localisation algorithm estimates the position of a new measurement by comparing it to previous measurements using k-Nearest Neighbour (k-NN) regression. The mean power was used as RSSI and 100 samples of the frequency response as CSI. Reduction of the dimension of the CSI vector with statistical moments and Principal Component Analysis (PCA) was tested. An improvement in accuracy could not be observed by using a higher dimensional fingerprint vector than RSSI. A standardised Euclidean or Mahalanobis distance measure in the k-NN algorithm seemed to perform better than Euclidean distance. Taking the logarithm of the frequency response samples before doing any calculation also seemed to improve accuracy.