Mapping & Surveying
Professional-grade GNSS/IMU post-processing for mobile mapping systems, UAV photogrammetry, terrestrial LiDAR, and geodetic surveys. High-accuracy trajectories for survey-grade point cloud georeferencing in corridor and urban mapping projects.
Why AlgoNav for Mapping?
Survey-grade accuracy and workflow automation for professional surveying applications.
Mobile Mapping
Precise trajectory computation for vehicle-mounted and backpack LiDAR systems. Tightly-coupled GNSS/IMU sensor fusion supports reliable point cloud georeferencing through urban canyons, partial GNSS outages, and other GNSS-challenged environments.
Geodetic Surveys
High-accuracy static and kinematic processing for geodetic control network establishment, cadastral boundary surveys, and deformation monitoring with full ambiguity resolution.
UAV / Drone Mapping
PPK processing for aerial photogrammetry and LiDAR surveys with direct georeferencing, reducing ground control point requirements while maintaining project-level accuracy targets.
No GCPs Required
With AlgoNav's high-accuracy GNSS/IMU sensor fusion, Ground Control Points become optional for UAV and drone mapping projects. The precise positioning solution already delivers survey-grade coordinates directly from the onboard GNSS receiver and IMU — no additional field work needed.
Works with Your Existing Survey Hardware
Survey and mapping professionals use diverse GNSS receivers and IMUs across mobile mapping systems, UAVs, and terrestrial platforms. AlgoNav works with any sensor providing an open or documented format — no hardware replacement, no lock-in to a proprietary ecosystem.
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RTK vs PPK in Mapping & Surveying
Survey-grade projects demand the highest trajectory quality. Why is post-processing essential?
Real-Time (RTK)
Corrections streamed during data capture
- Requires continuous NTRIP or radio link throughout every survey mission
- Urban canyons, tree canopy, and bridge underpasses cause frequent RTK drops and re-initializations
- Base station handover between reference stations can introduce position jumps on long corridors
- Real-time sensor fusion requires all data links between GNSS, IMU, and other sensors to work continuously and reliably — operationally demanding to set up and maintain
- IMU alignment requires 10–20 minutes of static idle time before each mission — costly field downtime with crews waiting
Post-Processed (PPK / PPP)
Process after capture with optimal products
- No real-time link needed — record raw GNSS/IMU data and process back in the office
- Iterative optimal smoothing bridges GNSS outages under bridges, canopy, and in urban canyons
- Multi-base processing with automatic station weighting (Moving VRS) for consistent corridor trajectories
- PPP for remote areas: Final precise orbit products deliver higher accuracy than real-time broadcast ephemerides
- Each sensor simply logs data independently — no inter-sensor data links required in the field, much simpler to deploy and operate
- No static IMU alignment needed — orientation is computed automatically from the logged data during processing
- Traceable QC reports per mission prove accuracy to clients before deliverable handoff
When to Use Which?
Use RTK only for tasks requiring immediate on-site coordinates.
Use PPK for all mobile mapping, drone survey, and LiDAR georeferencing projects where trajectory quality determines point cloud accuracy. Post-processing consistently outperforms real-time solutions.
Best practice: Professional survey teams record raw data regardless of RTK status — PPK serves as both primary processing mode and quality safety net for every mission.
Challenges We Solve
Real-world surveying is rarely ideal. AlgoNav is engineered for the conditions you actually encounter.
Urban Canyon GNSS Shadowing
In urban canyons, under tree canopy, and beneath bridges, multipath and signal masking can force RTK-fixed solutions to drop. Post-processing uses the entire dataset — including future observations — to bridge outages and resolve ambiguities, delivering significantly more robust solutions than any real-time filter that only sees past data.
No GCPs Required
High-accuracy GNSS/IMU post-processing delivers survey-grade georeferencing directly — eliminating the need to place and measure Ground Control Points in the field. This saves significant time and cost, especially for UAV photogrammetry and LiDAR projects where GCP deployment is often the biggest operational bottleneck.
No IMU Alignment Needed
Real-time systems typically require 10–20 minutes of static warmup for IMU alignment before each mission — often ineffective with low- and mid-cost sensors anyway. AlgoNav's iterative post-processing computes initial orientation directly from the logged data, eliminating idle field time entirely.
No Live GNSS Link & Automatic PPP
No real-time correction stream required — unlike RTK, a dropped data link never degrades your solution. In remote areas without base station coverage, PPP delivers accurate results using final precise orbit and clock products. AlgoNav fetches these products automatically for the best possible solution.
Gimbal-Mounted Sensors & Multi-IMU
On many professional UAVs, payload sensors such as cameras, LiDAR scanners, or even ground-penetrating radar are mounted on stabilized gimbal platforms to ensure smooth, vibration-free data capture. In these setups, a dedicated IMU is often rigidly attached to the gimbal alongside the sensor — rather than to the airframe. This creates a fundamental challenge: the lever arm between the GNSS antenna (on the body) and the payload IMU (on the gimbal) changes continuously as the gimbal rotates, breaking the constant lever-arm assumption that standard GNSS/INS processing relies on. AlgoNav supports these multi-IMU configurations natively, fusing both the body-fixed IMU and the gimbal-mounted IMU to accurately determine sensor position and orientation at every point in time — a capability that most standard post-processing packages do not offer.
Let's Talk
Discover how AlgoNav can enhance your surveying workflows with survey-grade trajectory accuracy, automated batch processing, and seamless integration into your existing mobile mapping pipeline.