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LiDAR Boost Post Process
- 0.218 m Position 2D (60s GNSS outage)
- 0.05° Heading (60s GNSS outage)
- 0.02° Roll / Pitch (60s GNSS outage)
OXTS Inertial Navigation Systems and LiDAR Boost Post Process
GNSS has its limits. Tunnels, urban canyons, underground environments – anywhere signal is weak or blocked is a gap in your localisation data. LiDAR Boost closes that gap.
What is LiDAR Boost Post-Process?
LiDAR Boost Post Process is a powerful Windows-based application designed to deliver high-accuracy navigation through advanced sensor fusion. By processing synchronised INS and LiDAR data logs, the software applies our innovative LiDAR Boost algorithms to generate additional navigation aiding directly from LiDAR measurements.
This LiDAR-derived aiding is seamlessly combined with GNSS and IMU data from the INS to produce a robust, precision navigation solution. Even in challenging or GNSS-denied environments, LiDAR Boost bridges gaps in satellite coverage, constraining IMU error growth and maintaining reliable positioning performance.
With support for both an intuitive graphical user interface and a flexible command-line interface, LiDAR Boost Post Process fits easily into a wide range of workflows. Automatic quality reports also provide at-a-glance performance analysis and simplify debugging.
As the offline counterpart to the real-time LiDAR Boost capability in our WayFinder Prime and WayFinder Hub systems, it enables detailed post-mission processing, validation, and performance optimisation of your INS, ensuring maximum insight and accuracy from your data.
How it works
LiDAR Boost post process contains two complementary techniques to maintain accuracy wherever you are:
LiDAR Inertial Odometry (LIO) analyses point cloud data from your LiDAR scanner. It detects planes and objects and tracks movement between frames to calculate real-time velocity updates. It’s ideal for areas where GNSS signal is patchy, for temporary outages like tunnels, or to protect against multipath errors that are common when navigating through cities.
LiDAR Map Matching (LMM) takes things one step further – if you have a pre-existing point cloud of a space, LMM can compare live LiDAR data against it to deliver accurate, fully repeatable performance every time you navigate through that environment.
The Problem: Position Drift
Position drift is rarely an issue in open-sky conditions. However, in environments with poor GNSS visibility, such as urban canyons, keeping drift to a minimum is critical to maintaining dataset integrity.
The graph opposite shows how the LiDAR inertial odometry feature effectively constrains position drift.
The data shown was collected in Oxford, UK, a representative example of an urban-canyon environment.
Who is it for?
LiDAR Boost has potential to add value to any land-based activity that requires accurate localisation data in challenging environments. Automotive testers can use it to gather consistently accurate data for open-road testing or create an indoor testing solution that doesn’t rely on infrastructure, while surveyors can use it to collect accurate trajectory data in cities, indoors, or underground for subsequent use in georeferencing activities.
Compatible Devices
LiDAR Boost Post Process is compatible with all OXTS GNSS/INS devices. The software, including the LiDAR inertial odometry and map-matching feature codes can be added on to any OXTS GNSS/INS device.
It is also built into WayFinder Prime – an advanced sensor fusion platform that enables you to accurately navigate in any environment, even when GNSS signals are intermittent or completely blocked. Simply mount it, configure it, initialise, and you’re ready to go. No integration headaches. No custom algorithm development.
LiDAR Inertial Odometry Technical Paper
Download the LiDAR Inertial Odometry technical paper and learn more about how the feature works alongside OXTS GNSS/INS devices.
Compatibility
Compatible LiDAR sensors include many 360° field-of-view devices from:
Specification
Odometry accuracy 0.03 – 0.05 m/s measurement rate 5-20 Hz
The specification values here have been obtained statistically using a Hesai XT32 LiDAR device and an OXTS INS.
The data was collected in the city of Oxford using an RTK Integer reference dataset. Oxford was chosen as it closely resembles other urban areas. Please note that these values may vary depending on your LiDAR set-up and the environment.
| Measurement | GNSS Outage | RMSE |
|---|---|---|
| Position 2D | 60 s | 0.218 m |
| Heading | 60 s | 0.050° |
| Roll/Pitch | 60 s | 0.020° |
| Velocity 3D | 60 s | 0.037 m/s |
| Altitude | 60 s | 0.128 m |
LiDAR Boost Post Process features
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Windows OS supported.
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Feature code on the INS to enable.
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Software running in post-process.
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Ability to run from the command line or GUI.
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Automatic quality report will generate after processing is complete to give debug outputs and performance metrics.
Test data
01
Point cloud – Multi-storey car park
Bicester, UK – Point cloud – Multi-storey car park
- GNSS/INS – RT3000 v4
- LiDAR – Hesai XT32
- Software: NAVsuite, LiDAR Boost Post Process
Environment: In this example LiDAR Boost Post Process was tested inside a multi-storey car park. Upon entering the car park the OXTS device, an RT3000 v4 GNSS/INS, naturally did not have any access to GNSS updates. To overcome this, updates from a Hesai XT32 LiDAR sensor were used to aid the navigation engine.
The outcome is more accurate data for longer.
02
KML Trail – Urban Canyon
London, UK – KML Trail – Urban Canyon
- GNSS/INS – RT3000 v4
- LiDAR – Hesai XT32
- Software: NAVsuite, LiDAR Boost Post Process
Environment: In this example LiDAR Boost was tested in one of the most difficult areas for a GNSS/INS to operate, the ‘Sky Garden Quarter’ urban canyon in London, UK. During the data collection, there were regular GNSS signal interruptions and severe multi-path disruptions. LiDAR Boost Post Process was used to improve position drift making the data both accurate and repeatable throughout each lap of the data collection.
03
Pointcloud – Tunnel
San Francisco, USA – Point cloud – Tunnel
- GNSS/INS – RT3000 v4
- LiDAR – Hesai XT32
- Software: NAVsuite, LiDAR Boost Post Process
Environment: Even a short tunnel can present a major test for a GNSS/INS. The longer a GNSS/INS is without GNSS signal updates, the more pronounced position drift becomes. In this example, LiDAR Boost was used to keep the navigation solution on track throughout its journey through the tunnel. Not only did this lead to improved navigation data but also a clearer point cloud, as can be seen by viewing the pillars in the example below.
04
KML Trail – Multi-storey Car Park
San Francisco, USA – KML Trail – Multi-storey Car Park
- GNSS/INS – RT3000 v4
- LiDAR – Hesai XT32
- Software: NAVsuite, LiDAR Boost
Environment: As mentioned previously, because GNSS signal updates are blocked in a multi-storey car park, a GNSS/INS device must use an additional aiding source to navigate accurately. In this example LiDAR Boost was used to improve the navigation output. This has led to a more consistent data set.
05
Point cloud – Urban Canyon
San Francisco, USA – Pointcloud – Urban Canyon
- GNSS/INS – RT3000 v4
- LiDAR – Hesai XT32
- Software: NAVsuite, LiDAR Boost
Environment: The Mission Street urban canyon in San Francisco, USA is a street surrounded by glass-fronted high-rise buildings. GNSS signal is continuously interrupted and there is a danger of multi-path errors. During testing the RT3000 v4 by itself was very accurate, however when coupled with LiDAR Boost Post Process it was almost seamless.The feature keeps the INS on a stable and consistent path through the city allowing it to filter out all multi-path signals.
Trial the beta version of LIO
Users of OXTS Inertial Navigation Systems can trial the beta version of LIO for free today!
Complete the form and one of our developers will be in touch to provide you with the software!
Alternatively, send us your data to [email protected] and we will process it for you!