What is mobile mapping?
Mobile mapping is the method of collecting geospatial information from a moving vehicle. Applied to a variety of platforms ranging from cars to trucks, trains to recreational vehicles; mobile mapping provides a means to efficiently and dynamically map the environment. Mobile mapping vehicles collect data to map features along the route using a range of imaging sensors that include digital photographic cameras, video or laser scanners. The features that are being mapped might include slopes or contours alongside the vehicles’ route, the position and type of road side assets such as signage and noise barriers, the height and structure of surrounding vegetation, or condition of the road surface itself. The accuracy, precision and frequency of measurements that are required to map these features will vary dramatically, so cameras may be taking multiple images per second or laser scanners could be collected a million individual data points per second.
A mobile mapping system therefore needs to be able to collect data in such a way that users are able to locate and position features of interest in data collected by the mobile mapping vehicle, while it is in motion. Positioning these data not only requires knowledge of where the vehicle is located, but also the orientation and onward velocity of the vehicle. Due to the frequency at which data is captured, this is information that needs to be understood continuously throughout the passage of the mobile mapping vehicle. Survey technologies such as global positioning systems (GPS) are well known and widely used, but relying only upon GPS will lead to incomplete mobile mapping results. This is where it is important that an inertial navigation system is used to deliver a complete mobile mapping solution.
Figure 1: Mobile mapping vehicles in operation. Images courtesy of WSP Sweden.
Why not just use GPS to position mobile mapping vehicles?
The use of GPS by surveyors to create and update maps has been commonplace for over 20 years. These systems calculate a position on the earth’s surface by way of timing information received from a network of global navigation satellite systems (GNSS) that continually orbit the earth. The satellite constellations accessed by the GNSS systems might include the original US-led Global Positioning System (GPS) project, the Russian GLONASS constellation, or one of the other constellations under development such as the European -led GALILEO, or China -based BeiDou projects. For the purpose of these descriptions, the generic terms of GPS and GNSS will be used respectively.
When undertaking mobile mapping, there are challenges associated with relying upon GPS data alone. Issues related to the use of GPS include those associated with the GPS receiver needing to have a clean line of sight to at least four GNSS at any one time to obtain longitude, latitude and altitude coordinates. In addition, the overall distribution of GNSS satellites above a particular portion of the earth at any one time may not lead to a clear line of sight. The extent to which location coordinates can be acquired will also depend upon whether structures in the environment occlude the receiver from clearly seeing the sky, and so tall buildings or overhanging trees can cause outages in the extent to which a GPS can calculate its position. This problem can be even more acute when undertaking mobile mapping, as vehicles often travel through GPS deprived areas such as urban centers or forests. In addition, even if the required number of satellites can be seen, the frequency at which location measurements are recorded from a GPS is likely to be different to the frequency at which images are being acquired by the sensors on the vehicle. As a result, there is a need to understand what the location of the vehicle is at times where GPS is unavailable, and be able to measure, or predict where the vehicle has travelled in between GPS readings that are received.
Figure 2: Illustration of GPS outage when mobile mapping in urban environment
Finally, a mobile mapping system must continuously calculate the exterior orientation of the sensors on the mobile mapping vehicle. As the vehicle is traveling, in addition to measuring a straight line distance between data points, its movement also needs to be described in terms of the roll, pitch and yaw of the vehicle. While GPS can provide information on the geographic coordinates of the vehicle at a particular time, in addition to an understanding of heading; the system does not know about parameters such as whether the vehicle is pointing up a slope or how fast it is moving towards (or past) features in the landscape.
Complete mobile mapping using an inertial navigation system
In practice, mobile mapping is best undertaken when a range of sensors are being used to locate the position, direction and orientation of the vehicle, while it is moving. These additional sensors help fill in the gaps when a location is unknown, and usually include:
- GPS receivers, for calculating latitude, longitude and elevation
- An odometer, for measuring distance travelled
- An inertial measurement unit (IMU), for measuring roll, pitch and heading of the vehicle and the sensors upon it.
- A computer processing unit containing various statistical algorithms for predicting the position of the mobile mapping vehicle, based upon the accumulated readings from the sensors described above.
The inertial navigation system (INS) is the computational system that includes an IMU, and takes input from the GPS and odometer systems (when available) to calculate the overall most likely position of the vehicle.
Figure 3: Components of a mobile mapping vehicle
The hardware component that provides much of the information related to the dynamics of the mobile mapping vehicle’s motion is the IMU. Comprised of an assembly of gyroscopes and accelerometers, the IMU will provide a continuous stream of data related to the linear acceleration of the vehicle on three axes, together with the three sets of rotation parameters. To provide additional measurements related to distance travelled by the mobile mapping vehicle and to reduce drift in challenging GNSS environments, most land-based vehicles will be fitted with a mechanical or laser-based wheel sensor (odometer) to measure wheel revolutions.
Finally, either integrated as a processing unit on the INS or as separate on-board computer; algorithms will be applied that check and analyse the input data from the sensors connected to the GPS. Using a range of statistical algorithms such as Kalman filters, absolute positions and orientations of the mobile mapping vehicle and its survey sensors will be calculated based upon all of the information available at each instance in time. The statistical element of these algorithms provides a means to collate the information from the sensors that feed into the INS, and is able to calculate a trajectory over which the vehicle has been moving. Through a processes known as dead reckoning, this enables a statistically most-likely position of the vehicle to be calculated at times when GPS data is not available.
The INS system enables the mobile mapping system to continuously collect spatially referenced information with a high degree of confidence across a range of environments as the vehicle travels. By understanding the dynamics of the moving vehicle platform better, operators of mobile mapping systems are able to locate and position the data captured by the imaging sensors mounted upon it.