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A Noise-Robust Convex-Optimized Positioning System Based on Code-Aided RSS Estimation and Virtual Base Station Transform

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Abstract

This paper presents a noise-robust mobile positioning system based on received signal strength (RSS) estimators, particle filters and a convex optimization processor. The positioning system uses a code-aided noise cancellation technique to refine the (RSS) signals and improve the positioning accuracy. This study also presents a virtual base-station transform (VBST) and convex optimization algorithm to deal with the none-light-of-sight (NLOS) travelling problem of the microwave transmission. The proposed positioning processor consists of four code-aided SNR/RSS estimators and four latency-reduced particle filters to refine the RSS signals from four base stations and estimate their distances to the mobile station. Then, the estimated distances are delivered to a convex optimization processor with the VBST algorithm to locate the mobile station. This work implemented the positioning algorithm on Xilinx Virtex-4 FPGA and RF modules to verify the positioning performance. The measurement and analysis results show that the proposed convex-optimized positioning system reduces 20 % RMSE in the mixed NLOS/LOS environment compared to the sole particle filtering approach. The RSS estimator can further improve the positioning performance in the noisy environments.

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Acknowledgements

This work was supported by the National Science Council (NSC), Taiwan, under Grant Number NSC 101-2221-E-007-127-MY2.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Tsing Hua University, Taiwan, 30013, Republic of China

    Li-Hong Huang, Kai-Ting Shr, Ming-Hung Lin & Yuan-Hao Huang

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  1. Li-Hong Huang
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Correspondence to Yuan-Hao Huang.

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Huang, LH., Shr, KT., Lin, MH. et al. A Noise-Robust Convex-Optimized Positioning System Based on Code-Aided RSS Estimation and Virtual Base Station Transform. J Sign Process Syst 84, 309–323 (2016). https://doi.org/10.1007/s11265-015-1082-5

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