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The term mobile mapping can mean many different things to many different people. It covers a wide range of disciplines and can reference both air and land-based activities. However, it doesn’t matter whether you’re using a drone to map infrastructure, or a land-based vehicle to locate assets, one thing remains constant – the need for uninterrupted trajectory data.
Engineers tend to use GNSS-aided inertial navigation systems (INS) to provide them with this information. An INS device combines position data from GNSS, with orientation data from an IMU, to output an estimate of its position on earth. The data can then be used for a range of georeferencing activities.
In an open-sky environment, an INS will generally output trajectory data to centimetre-level accuracy, which is comfortably precise enough for most georeferencing use cases. But, by its very nature, mobile mapping doesn’t always take place exclusively in open-sky conditions. In fact, it takes place over long baselines that incorporate multiple environmental conditions, and regular GNSS interruptions. Therefore, much of the value in mobile mapping today, comes from the ability to collect accurate, uninterrupted trajectory data across a range of different environments, with and without GNSS position updates.
Uninterrupted trajectory data in urban canyons
For tasks such as infrastructure monitoring and asset management – two of the most widely publicised mobile mapping applications – having the ability to provide uninterrupted trajectory data in environments such as urban canyons isn’t just a ‘nice to have’ it’s essential, and can be the difference between winning and losing a project to a competitor.
To open the door to consistent, accurate data collection in built up areas, mapping fleets need to be resilient to GNSS-signal interruption or blackout, which can cause significant position drift errors and render data useless.
The best solution for ensuring globally-accurate, uninterrupted trajectory data will always be a combination of GNSS and INS data, and this combination should always be utilised whenever possible. But when GNSS isn’t available, additional redundancy needs to be integrated into the system.
Using sensor fusion for redundancy
When GNSS is unreliable, aiding data from additional sensors, like LiDAR or cameras should be used in its absence – though this can be fraught with its own set of integration challenges.
Data from these systems, when fused with IMU data correctly, can help to replace missing or erroneous GNSS data, stabilising position drift and ensuring accurate trajectory data without GNSS.
This is particularly useful for any project that takes place in an urban canyon, where GNSS signal is continuously reflected or interrupted by tall buildings, bridges and tunnels. For example, in this use case, it is possible that missing GNSS updates can be supplemented with velocity updates from a LIDAR sensor (LiDAR Inertial Odometry or LIO), whenever GNSS signal is lost. LIO data can be added in post-process, or in real-time (for active navigation) with the WayFinder navigation system.
Where there is high concentration of assets, there is usually also a high concentration of GNSS interruptions. For projects like large scale asset mapping, that generally take place over vast areas and in built up environments, it is crucial to obtain uninterrupted trajectory data. Without it, asset identification and location can become inaccurate causing problems further down the line. Generating and fusing navigation updates from other sensors adds resilience to your trajectory output meaning more accurate localisation data for longer periods.
Like we mentioned earlier in this blog, for any project GNSS and INS data should be used where possible as this should give you the most accurate data, however in more challenging environments, like urban canyons, fusing additional sensor modalities can be a cost-effective way to keep your trajectory accurate. Additionally, having the ability to intelligenty switch between GNSS and non-GNSS methods of localisation can increase productivity and speed up project delivery.
The challenge for many mobile mappers can be in the time and skills required to generate and fuse navigation updates from those additional sensor modalities. That’s where WayFinder comes in. As a ready-to-deploy, multi-sensor fusion device, the integration and sensor fusion of GNSS, IMU, LiDAR and camera data is done for you. With wide support for georeferenced data from a range of survey-grade laser scanners, and the ability to switch between using GNSS and LiDAR/camera for localisation, you can confidently reallocate the time and money spent on deployment to growth, confident in the knowledge that your data collection system is capable of collecting accurate, uninterrupted trajectory data.
Download the WayFinder Datasheet
Learn more about the position accuracy specifications you can expect from WayFinder both with and without GNSS signal
