: Indoor positioning methods based on wireless local area network (WLAN) signal measurements have gained
popularity because of high localisation accuracy. These methods use radio-maps obtained from wireless signal measurement
surveys on location grids. Measurement sets from various WLAN access points are called fingerprints and they can be used
to identify locations where the measurements are collected. WLAN positioning methods face unexpected changes in signal
patterns because of attenuation changes or transient faults in WLAN cards or access points that often make signal strength
readings unavailable. This study studies the effect of faulty measurements on the performance of popular state-of-the-art
WLAN indoor positioning methods. Additionally, an integrity monitoring preprocessing algorithm is provided that
demonstrates a possibility of faulty measurements mitigation for conventional methods such as K-nearest-neighbour. This is
achieved by detecting and excluding faulty measurements prior to classification. Performance figures are provided for both
simulated and empirical environments