The Landmarc algorithm is the most common scheme to achieve the object location. However, Landmarc has been found with estimation errors due to the type of RSSI radio property. In the present study, we introduce an enhanced statistical approach in order to process RSSI data and estimate the tracking tag position in a room. We proposed herein two location estimate schemes, namely, the ESL_Average and ESL_Median schemes. Both schemes periodically collect RSSI data within a fixed time period and calculate final values to estimate location by using the Landmarc algorithm. For the ESL_Average scheme, the final RSSI value is the average of all RSSI values measured in the given time period. The ESL_Median scheme uses the median of RSSI values to estimate the tracking tag location. We also estimate the estimation accuracy of the two proposed schemes by experiment and comparison with the Landmarc algorithm. The result from performance evaluations reveals that the proposed schemes yield higher accuracy than the traditional Landmarc scheme.