Indoor positioning using Bluetooth addressed a great concern. The properties of narrowband usage, low energy consumption and universality on devices attract numerous customers and promote researchers to investigate potential of Bluetooth in indoor positioning field. It has already supported Angle-of-Arrival (AoA) and Angle-of-Departure (AoD) in angle domain for indoor localization. In range domain, using Received Signal Strength (RSS) is practicable but it cannot provide enough resolution. It is needed to develop a technique that can improve resolution for range finding feature. The challenges of localization in indoor environments are mainly from the multipath propagation of signals. In this thesis, a subspace-based super-resolution algorithm for time delay dispersion estimate is developed. Range finding is realized by computing time-of-arrival (ToA) parameter of signal arriving at direct line-of-sight (DLoS). An essential procedure before the developed algorithm is applied is that to correctly separate subspace into signal space and noise space. Techniques for subspace separation are investigated in this thesis. In this thesis, we want to explore the potential of indoor localization using Bluetooth narrowband radios. To start with, a data model according to the property of the conducted measurement data is developed. The conducted measurement data is radio channel measurements based on channel sounding technique. Then the data model is developed as channel impulse response model and multipath signals are indicated by different time delays. Since an accurate covariance matrix of measurement data is required for super-resolution algorithm, smoothing techniques is employed. The smoothing techniques considered are forward smoothing technique and forward-backward smoothing technique. For the purpose of obtaining an accurate subspace separation, two techniques are investigated in this thesis, namely MDL criteria algorithm and the threshold method. in order to investigate the performance and reliability of those two techniques, experiments are taken out using different parameter values. Comparison is made between the results of these two techniques. Afterwards, subspace-based super-resolution algorithm is taken into consideration. In this thesis, the super-resolution algorithm implemented is MUSIC algorithm. The functionality of MUSIC algorithm on narrowband radios measurements is tested and evaluated firstly by simulation experiments, which demonstrates the practicability of applying MUSIC algorithm on narrowband radios measurements. Then experiments are extended to the measurement data that conducted from real indoor environments, for the purpose of indoor localization realization using narrowband radios.