DOAJ Open Access 2022

Multi-Epoch 3D-Mapping-Aided Positioning using Bayesian Filtering Techniques

Qiming Zhong Paul D. Groves

Abstrak

The performance of different filtering algorithms combined with 3D-mapping-aided (3DMA) techniques is investigated in this paper. Several single- and multi-epoch filtering algorithms were implemented and then tested on static pedestrian navigation data collected in the City of London using a u-blox EVK M8T GNSS receiver and vehicle navigation data collected in Canary Wharf, London, by a trial van with a Racelogic Labsat 3 GNSS front-end. The results show that filtering has a greater impact on mobile positioning than static positioning, while 3DMA GNSS brings more significant improvements to positioning accuracy in denser environments than in more open areas. Thus, multi-epoch 3DMA GNSS filtering should bring the maximum benefit to mobile positioning in dense environments. In vehicle tests at Canary Wharf, 3DMA GNSS filtering reduced the RMS horizontal position error by approximately 68% and 57% compared to the single-epoch 3DMA GNSS and filtered conventional GNSS, respectively.

Penulis (2)

Q

Qiming Zhong

P

Paul D. Groves

Format Sitasi

Zhong, Q., Groves, P.D. (2022). Multi-Epoch 3D-Mapping-Aided Positioning using Bayesian Filtering Techniques. https://doi.org/10.33012/navi.515

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Informasi Jurnal
Tahun Terbit
2022
Sumber Database
DOAJ
DOI
10.33012/navi.515
Akses
Open Access ✓