Based on wireless sensor networks, device-free indoor localization technique has received much attenation in the field of indoor localization system. Due to different indoor environmental parameters, multipath fading, human presences and different systems configurations, the WiFi-based RSSI (Received Signal Strength Indicator) values are effected. This problem leads the researchers to choose any filter or smoothing algorithm to get proper values of received signal strength in the indoor environment. The aim of using the filter or smoothing algorithm is to get a signal values which can clearly identify the changes in the signal values due to interferences caused by the various factors in the indoor environment. WiFi-based device-free indoor localization technique has become more attractive because of its simplicity, as well as it does not require extra hardware. However, the implenation of this technique in the indoor environment becomes complex sometimes, due to inaccurate and variable readings produced by the multipath fading in the RSSI values. In order to mitigate the varaiance in the received signal strength, various filters have been designed and tested. However none of the filter can completely mitigate the changes in received signal strength values cause by multipath fading. In this paper alpha trimmed filter is used for smoothing the raw data of received signal strength indicator values and also improving the strength of these values by mitigating multipath fading effects in an indoor environment.