The Inertial Measurement Unit (IMU) is an integral component in a wide range of mobile mapping solutions. The device is typically a combination of three accelerometers and three gyroscopes with each triad set at right angles, used to measure linear and angular motion. 3D Laser Mapping have been working with and testing IMUs for years and fully understand how complex they can be. On this page we aim to clarify technical jargon, outline performance characteristics and help you find the system right for your needs.
Five things to look for when evaluating an IMU
- Roll, Pitch and Heading accuracy – Determines how accurate the measured values are compared to their true values. Impacts the positional accuracy of the pointcloud, positional error increases with range.
- Gyro Bias – The lower the Gyro-bias the less effort is required for initialising the system
- Gyro Random Walk – The noise of the sensor, which causes INS error to grow over time during GNSS outages. The lower the Gyro-RW the better the system will perform without GNSS
- Measurement Rate – The higher the measurement rate the less interpolation is required during laser scanner geo-encoding resulting in improved accuracy.
- Export Control – Can you easily move the IMU around the world or will you need an export license to do so?
Measures of Performance and Error
|Position||m||The absolute positional accuracy|
|Velocity||m/s||The velocity accuracy|
|Roll/Pitch||deg||The roll/pitch accuracy|
|True Heading||deg||The heading accuracy|
|Data Rates||Hz||The measurement speed of the IMU|
The performance of the INS (Inertial Navigation System) is also often quoted and takes into account the accuracy of the IMU and a GNSS (Global Navigation Satellite System) when combined by a Kalman Filter.
An INS filter, referred to as a Kalman Filter , combines the different measurements taking into account estimated errors to produce a trajectory including time, position, and attitude.
|Bias Repeatability||deg/hr or m/s²||The difference between the real value and the output, which can change from mission to mission and affects the time taken to initialise the INS|
|Bias Stability||deg/hr²||The bias can change over time and has an effect on the performance of the INS during GNSS outage|
|Scale Factor||ppm||The relation in scale between input and output|
|Random Walk||deg/√hr||The noise of the sensor, which causes INS error to grow over time during GNSS outage|
Data Rate: A high data rate is also important because scanners will generally be recording at a much higher rate than the IMU and so errors with interpolation will occur which will also grow with range.
Application: If the application requires driving with very little dynamics (low speed, very few turns) then an IMU with a low bias and low random walk will be beneficial. It should be noted that heading drift can be reduced during a low dynamic survey by using a dual GNSS antenna system.For surveying in areas of poor GNSS, such as city mapping, the most important factor will be the bias and random walk since these errors dictate how quickly and to what extent heading drift occurs. For example, if the INS has no GNSS for one minute, a low grade IMU could result in an error of over 2m, and a high grade IMU an error of less than 20cm.
Coupling: How the INS and GNSS interact with each other is referred to as coupling. A loosely coupled INS is where the position and velocity from the INS and GNSS are combined to form a trajectory. A tightly coupled INS goes a step further by also combining the GNSS raw measurements with the INS, therefore allowing GNSS position updates with fewer than four satellites (four satellites are usually the minimum requirement for a GNSS position fix). The deeply coupled approach is similar to the tightly coupled approach, except information is also passed from the INS filter to the GNSS filter, which enabled faster GNSS signal reacquisition. It is common for some INS systems to use a combination of these different coupling techniques and will generally be given different terminology to those described above, so it may be necessary to ask the supplier how the INS and GNSS interact with each other.
Type of Inertial Measurement Unit: There are many different types of IMU, the three most common types of IMU for mobile mapping applications are:
- Fibre Optic Gyro (FOG)
- Ring Laser Gyro (RLG)
- Micro Electro Mechanical Systems (MEMS)
Generally, FOG and RLG IMUs provide higher performance than a MEMS IMU, but this is not always the case. We highly recommend studying the specifications of each IMU carefully before deciding to ensure you get the right system.
If you’re interested in a mobile mapping systems, or would simply like to bend our ear – please get in touch! Drop us a line at firstname.lastname@example.org or dial 01949 838004.