Positioning systems are one of the key elements required by location-based services (LBS). As global positioning system (GPS) was never intended for indoor environments, indoor positioning systems based on wireless local area networks (WLAN) have been proposed as a viable solution. RADAR algorithm is one of the famous indoor positioning techniques. It uses a database of predetermined fingerprints for selected locations to estimate the location of a mobile user in the signal space. Another new proposed algorithm named the Enhanced Fingerprint (EFP) uses the same principle as RADAR algorithm but with more than one fingerprint per location. In this paper we investigated the location fingerprint based algorithms by taking RADAR and EFP with more details. We evaluated these two algorithms in terms of accuracy, reliability and computation time. Experiment results show that the EFP algorithm gains 1.82 m of accuracy over RADAR algorithm, while the last one saves 75% of computation time. We found that EFP algorithm is more consistent with varying number of training samples.