Noise-Resistant Mobile Positioning System Based on Code-Aided RSS Estimation

Abstract

In recent years, research on mobile positioning techniques in wireless communications systems attracts a lot of interest due to the growing use of location-based applications for smart phones. This research proposes a code-aided received signal strength (RSS) estimator for a network-based positioning system. The proposed RSS estimator derives the channel noise by accumulating the minimum path metrics of the Viterbi decoder and then refines the RSS value as the input to the particle filter at each base station. Afterwards, the calculated distances at base stations are processed by convex optimization to locate the mobile device. This work develops a system to verify the positioning performance in the urban area. The simulation results show that the proposed system with the code-aided RSS estimation has 20 to 60-meter better performance than the same system with raw RSS information when SNR is smaller than 4dB. Compared to other corresponding SNR estimation methods, the proposed RSS estimation technique also has better performance especially in the lower SNR conditions.