Mobile Positioning System Based on Virtual Base Station Transform and Convex Optimization

Huang, Li-Hong; Tsai, Sheng-Yu; Huang, Yuan-Hao

doi:10.1109/sips.2012.24

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…whered i is the particle filtered result in the i-th BS. Our previous study [10] extends the map factor β between 0 and 1 for optimization so that the corresponding curve lies between the arc curve and the straight line as shown in Fig. 2(a).…”

Section: (C)mentioning

confidence: 92%

“…The research in [9] proposed to weight the NLOS and LOS contributions in the convex optimization process. Based on this concept, our previous study [10] presents a virtual base-station transform technique and a Manhattan/Euclidean mixed norm as a mapping factor of weight. The database of map factors is much smaller than that of fingerprinting because the map factors are only stored at the crossroads.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Design and implementation of a convex-optimized positioning system on wireless RF/FPGA platform

Huang¹,

Shr²,

Lin³

et al. 2014

2014 IEEE Workshop on Signal Processing Systems (SiPS)

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This paper presents the design and implementation of a positioning system based on particle filters and a convex optimization processor. The positioning system uses a virtual base-station transform (VBST) and convex optimization algorithm to deal with the none-light-of-sight (NLOS) problem in wireless communication systems. This study designs a modified resampling particle filter to reduce the processing latency with little performance loss. The proposed system uses four modified particle filters to adopt RSS signals from at most four base stations to 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.

show abstract

Section: (C)mentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Design and implementation of a convex-optimized positioning system on wireless RF/FPGA platform

Huang¹,

Shr²,

Lin³

et al. 2014

2014 IEEE Workshop on Signal Processing Systems (SiPS)

Self Cite

View full text Add to dashboard Cite

show abstract

“…The research in [9] proposed to weight the NLOS and LOS contributions in the convex optimization process. Based on this concept, our previous study [10] presented a virtual base-station transform technique and a Manhattan/Euclidean mixed norm as a mapping factor of weight. The database of map factors is much smaller than that of fingerprinting because the map factors are only stored at the crossroads.…”

Section: Introductionmentioning

confidence: 99%

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

Huang

Shr

Lin

et al. 2015

J Sign Process Syst

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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 basestation 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.

show abstract

Mobile Positioning System Based on Virtual Base Station Transform and Convex Optimization

Cited by 2 publications

References 7 publications

Design and implementation of a convex-optimized positioning system on wireless RF/FPGA platform

Design and implementation of a convex-optimized positioning system on wireless RF/FPGA platform

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

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