A novel RSSI (Received Signal Strength Indication) refinement algorithm is proposed to enhance the resolution for indoor and outdoor real-time location tracking system. The proposed refinement algorithm is implemented in two separate phases. During the first phase, called the pre-processing step, RSSI values at different static locations are collected and processed to build a calibrated model for each reference node. Different measurement campaigns pertinent to each parameter in the model are implemented to analyze the sensitivity of RSSI. The propagation models constructed for each reference nodes are needed by the second phase. During the next phase, called the runtime process, real-time tracking is performed. Smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the mobile target is moving. Filtered RSSI values are converted to distances using formula calibrated in the first phase. Finally, an iterative trilateration algorithm is used for position estimation. Experiments relevant to the optimization algorithm are carried out in both indoor and outdoor environments and the results validated the feasibility of proposed algorithm in reducing the dynamic fluctuation for more accurate position estimation.

A timing synchronization is required in the mobile station to determine the correct transmission timing of the mobile-to-base bursts. In this letter, a timing synchronization technique using the reliability check and smoothing algorithm is proposed for the GSM receiver. The reliability check scheme extends the usefulness of this algorithm into low SNR region. And also smoothing algorithm is carried out by a first-order filter with an asymmetric step size. Simulation results show that the proposed algorithm is adequate for timing recovery of GSM modem.

Because of non-negligible ISI due to the Gaussian filter and delay spread in the GSM system, an equalizer is required. In this letter, a joint sliding window channel estimation and timing adjustment method is proposed for maximum likelihood sequence equalizer. And also a smoothing algorithm is presented in order to improve the equalizer performance. This smoothing scheme utilizes a variant of LMS algorithm to tune the channel coefficient estimates. Simulation results show that the proposed scheme is adequate for channel estimation of the adaptive equalizer.