A dense reference network for mass-market centimeter-accurate positioning

Murrian, Matthew J.; Gonzalez, Collin W.; Humphreys, Todd E.; Novlan, Thomas

doi:10.1109/plans.2016.7479708

Cited by 11 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One disadvantage of CDGNSS is that it requires observations from a nearby base station to eliminate modeling errors (e.g., for atmospheric delays or satellite clocks and orbits) common to both the base station (the reference) and the vehicle (the rover). Short-baseline CDGNSS, which offers the greatest robustness against urban multipath (Murrian et al, 2016), is limited to reference-rover baseline lengths below approximately 10 km (Odijk, 2002). To avoid the requirement for a nearby base station, attention has recently focused on extending precise point positioning (PPP), which is based on precise orbit, clock, and atmospheric corrections, to urban areas by tightly coupling with inertial sensors.…”

Section: Tightly Coupled Urban Pppmentioning

confidence: 99%

Low-Cost Inertial Aiding for Deep-Urban Tightly Coupled Multi-Antenna Precise GNSS

Yoder

Humphreys

2023

navi

Self Cite

View full text Add to dashboard Cite

The rise of connected and automated vehicles has created a need for robust globally referenced positioning with lane-level (e.g., sub-30-cm) accuracy (Reid et al., 2019). Much automated ground vehicle (AGV) research focuses on the use of lidar and cameras for navigation, but these sensing modalities often perform poorly in low-illumination conditions or during adverse weather such as heavy fog or snowy white-outs. By contrast, positioning techniques based on radio waves, such as automotive radar or GNSS, are robust to poor weather and lighting conditions (Narula et al., 2022). Recent work has found that fusing measurements from low-cost automotive radars with inertial sensing can provide lane-level accuracy in urban environments (Narula et al., 2022). But radar-based positioning in a global coordinate frame requires the production and maintenance of radar maps, which is a time-consuming and costly endeavor.

show abstract

Section: Tightly Coupled Urban Pppmentioning

confidence: 99%

Low-Cost Inertial Aiding for Deep-Urban Tightly Coupled Multi-Antenna Precise GNSS

Yoder

Humphreys

2023

navi

Self Cite

View full text Add to dashboard Cite

show abstract

“…3) Tightly-coupled urban PPP: One disadvantage of CDGNSS is that it requires observations from a nearby base station to eliminate modeling errors (e.g., for atmospheric delays or satellite clocks and orbits) common to both the base station (the reference) and the vehicle (the rover). Short-baseline CDGNSS, which offers the greatest robustness against urban multipath [12], is limited to reference-rover baseline lengths below approximately 10 km [13]. To avoid the requirement for a nearby base station, attention has recently focused on extending precise point positioning (PPP), which is based on precise orbit, clock, and atmospheric corrections, to urban areas by tightly coupling with inertial sensors.…”

Section: A Related Workmentioning

confidence: 99%

Low-Cost Inertial Aiding for Deep-Urban Tightly-Coupled Multi-Antenna Precise GNSS

Yoder¹,

Humphreys²

2022

Preprint

Self Cite

View full text Add to dashboard Cite

A vehicular pose estimation technique is presented that tightly couples multi-antenna carrier-phase differential GNSS (CDGNSS) with a low-cost MEMS inertial sensor and vehicle dynamics constraints. This work is the first to explore the use of consumer-grade inertial sensors for tightly-coupled urban CDGNSS, and first to explore the tightly-coupled combination of multi-antenna CDGNSS and inertial sensing (of any quality) for urban navigation. An unscented linearization permits ambiguity resolution using traditional integer least squares while both implicitly enforcing known-baseline-length constraints and exploiting the multi-baseline problem's inter-baseline correlations.A novel false fix detection and recovery technique is developed to mitigate the effect of conditioning the filter state on incorrect integers. When evaluated on the publicly-available TEX-CUP urban positioning dataset, the proposed technique achieves, with consumer-and industrial-grade inertial sensors, respectively, a 96.6% and 97.5% integer fix availability, and 12.0 cm and 10.1 cm overall (fix and float) 95th percentile horizontal positioning error.

show abstract

“…The development of plane tables and alidades increased the precision of measurements. With the invention of tachymeters that determine distances through traveling time or the phase shift of light and the differential global navigation satellite system (CDGNSS), measurement precision has become even more accurate to the order of centimetres [67]. With these technologies, digital data collection has also emerged in the field of mapping, reducing the amount of cumbersome and laborious work.…”

Section: Remote Sensing Techniques For Monitoring Geomorphology-terramentioning

confidence: 99%

Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

Lausch

Schaepman

Skidmore³

et al. 2020

Remote Sensing

View full text Add to dashboard Cite

The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and ecosystem management. Numerous remote sensing (RS) approaches and platforms have been used in the past to enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, and objective monitoring of geomorphological characteristics and their traits. This contribution provides a state-of-the-art review for the RS-based monitoring of these characteristics and traits, by presenting examples of aeolian, fluvial, and coastal landforms. Different examples for monitoring geomorphology as a crucial discipline of geodiversity using RS are provided, discussing the implementation of RS technologies such as LiDAR, RADAR, as well as multi-spectral and hyperspectral sensor technologies. Furthermore, data products and RS technologies that could be used in the future for monitoring geomorphology are introduced. The use of spectral traits (ST) and spectral trait variation (STV) approaches with RS enable the status, changes, and disturbances of geomorphic diversity to be monitored. We focus on the requirements for future geomorphology monitoring specifically aimed at overcoming some key limitations of ecological modeling, namely: the implementation and linking of in-situ, close-range, air- and spaceborne RS technologies, geomorphic traits, and data science approaches as crucial components for a better understanding of the geomorphic impacts on complex ecosystems. This paper aims to impart multidimensional geomorphic information obtained by RS for improved utilization in biodiversity monitoring.

show abstract

A dense reference network for mass-market centimeter-accurate positioning

Cited by 11 publications

References 8 publications

Low-Cost Inertial Aiding for Deep-Urban Tightly Coupled Multi-Antenna Precise GNSS

Low-Cost Inertial Aiding for Deep-Urban Tightly Coupled Multi-Antenna Precise GNSS

Low-Cost Inertial Aiding for Deep-Urban Tightly-Coupled Multi-Antenna Precise GNSS

Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

Contact Info

Product

Resources

About