An adaptive weighting based on modified DOP for collaborative indoor positioning
Indoor localisation has always been a challenging problem due to poor Global Navigation Satellite System (GNSS) availability in such environments. While inertial measurement sensors have become popular solutions for indoor positioning, they suffer large drifts after initialisation. Collaborative pos...
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| Format: | Article |
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Cambridge University Press
2016
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| Online Access: | https://eprints.nottingham.ac.uk/33123/ |
| _version_ | 1848794562339799040 |
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| author | Jing, Hao Pinchin, James Hill, Chris Moore, Terry |
| author_facet | Jing, Hao Pinchin, James Hill, Chris Moore, Terry |
| author_sort | Jing, Hao |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Indoor localisation has always been a challenging problem due to poor Global Navigation Satellite System (GNSS) availability in such environments. While inertial measurement sensors have become popular solutions for indoor positioning, they suffer large drifts after initialisation. Collaborative positioning enhances positioning robustness by integrating multiple localisation information, especially relative ranging measurements between local users and transmitters. However, not all ranging measurements are useful throughout the whole positioning process and integrating too much data will increase the computation cost. To enable a more reliable positioning system, an adaptive collaborative positioning algorithm is proposed which selects units for the collaborative network and integrates ranging measurement to constrain inertial measurement errors. The algorithm selects the network adaptively from three perspectives: the network geometry, the network size and the accuracy level of the ranging measurements between the units. The collaborative relative constraint is then defined according to the selected network geometry and anticipated measurement quality. In the case of trials with real data, the positioning accuracy is improved by 60% by adjusting the range constraint adaptively according to the selected network situation, while also improving the system robustness. |
| first_indexed | 2025-11-14T19:18:10Z |
| format | Article |
| id | nottingham-33123 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:18:10Z |
| publishDate | 2016 |
| publisher | Cambridge University Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-331232020-05-04T17:34:24Z https://eprints.nottingham.ac.uk/33123/ An adaptive weighting based on modified DOP for collaborative indoor positioning Jing, Hao Pinchin, James Hill, Chris Moore, Terry Indoor localisation has always been a challenging problem due to poor Global Navigation Satellite System (GNSS) availability in such environments. While inertial measurement sensors have become popular solutions for indoor positioning, they suffer large drifts after initialisation. Collaborative positioning enhances positioning robustness by integrating multiple localisation information, especially relative ranging measurements between local users and transmitters. However, not all ranging measurements are useful throughout the whole positioning process and integrating too much data will increase the computation cost. To enable a more reliable positioning system, an adaptive collaborative positioning algorithm is proposed which selects units for the collaborative network and integrates ranging measurement to constrain inertial measurement errors. The algorithm selects the network adaptively from three perspectives: the network geometry, the network size and the accuracy level of the ranging measurements between the units. The collaborative relative constraint is then defined according to the selected network geometry and anticipated measurement quality. In the case of trials with real data, the positioning accuracy is improved by 60% by adjusting the range constraint adaptively according to the selected network situation, while also improving the system robustness. Cambridge University Press 2016-03-01 Article PeerReviewed Jing, Hao, Pinchin, James, Hill, Chris and Moore, Terry (2016) An adaptive weighting based on modified DOP for collaborative indoor positioning. Journal of Navigation, 69 (02). pp. 225-245. ISSN 0373-4633 Indoor positioning; adaptive weighting; modified DOP http://dx.doi.org/10.1017/S037346331500065X doi:10.1017/S037346331500065X doi:10.1017/S037346331500065X |
| spellingShingle | Indoor positioning; adaptive weighting; modified DOP Jing, Hao Pinchin, James Hill, Chris Moore, Terry An adaptive weighting based on modified DOP for collaborative indoor positioning |
| title | An adaptive weighting based on modified DOP for collaborative indoor positioning |
| title_full | An adaptive weighting based on modified DOP for collaborative indoor positioning |
| title_fullStr | An adaptive weighting based on modified DOP for collaborative indoor positioning |
| title_full_unstemmed | An adaptive weighting based on modified DOP for collaborative indoor positioning |
| title_short | An adaptive weighting based on modified DOP for collaborative indoor positioning |
| title_sort | adaptive weighting based on modified dop for collaborative indoor positioning |
| topic | Indoor positioning; adaptive weighting; modified DOP |
| url | https://eprints.nottingham.ac.uk/33123/ https://eprints.nottingham.ac.uk/33123/ https://eprints.nottingham.ac.uk/33123/ |