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The navigation system is considered an essential component of any MMS since recorded navigation parameters are used to compute position and ori- entation parameters of real world objects in the global coordinate frame. Mapping sensors acquire spatial data in their local coordinate frame while the navigation sensors are used to record navigation parameters of the vehi- cle in the global coordinate frame. When these sensors are synchronised, the recorded navigation parameters can be employed to reference the mapping objects in the global coordinate frame. An example of navigation data from the XP-1 system along a road section is shown in Figure 2.7.

The georeferencing process of a MMS including a mapping sensor and GNSS/INS navigation sensors is shown in Figure2.8 [EES02,Tot09]. Let us

Figure 2.8: Georeferencing process of MMS.

consider that a mapping sensor is used to acquire spatial data point p in its s- frame which represents a local coordinate frame. α and β are polar coordinate angles which represent the mapping direction angles along XS and YS axis

of the s-frame respectively. The navigation sensors GNSS/INS are used to record the navigation parameters of the vehicle in m-frame which represents the global coordinate frame. The recorded parameters are used to measure navigation parameters of the mapping sensor which are then employed to reference the acquired data point p in the m-frame. The global coordinates of the mapping point p are computed in the m-frame with a georeferencing equation which can be described as [Tot09]

rm_p = rm_{GN SS}+ R_{IN S}m (Rs_X(α).R_Ys(β).RIN S_s .rs_p+ r_sIN S− r_{GN SS}IN S ) (2.3)

where r_pm is the coordinates of the point p in the m-frame and r_{GN SS}m is the coordinates of the GNSS in the m-frame determined using kinematic GNSS. Rm_{IN S} is the rotation matrix between the INS body and the m-frame determined using INS measurements, Rs

X and RsY are rotation matrices which

describe a rotation of the mapping direction around the X and Y-axis of the s-frame respectively and RIN S

s is the rotation matrix between the INS and the

s-frame determined through calibration. rs_p are the coordinates of the point p in the s-frame, rIN S

s are the coordinates of the mapping sensor in the INS

body frame determined through calibration and rIN S

GN SS are the coordinates

of the GNSS in the INS body frame determined through calibration.

GNSS has revolutionised conventional surveying and mapping by provid- ing reliable positioning services with an accuracy range up to few millimetres [KfBl03]. The GNSS sensor is used to determine translational and rotational parameters of a trajectory from range measurements between satellite and receiver. A roving GNSS sensor on a mobile mapping vehicle operates with respect to a local GNSS base station [Pet10]. The GNSS base station cal- culates its position based on a satellite signal and compares this position with its known position. This difference is then applied to correct the roving GNSS data in either Real time Kinematic (RTK) or Post Processing Kine- matic (PPK) mode. In RTK mode, the roving GNSS sensor directly receives corrections from the base station GNSS using a Ultra High Frequency (UHF) modem communication. In PPK mode, the roving GNSS data and the base station GNSS corrections are stored in a data logger and are combined in

post processing [IXS09]. Thus, the processed GNSS data provides an ac- curate estimation of the vehicle’s navigation parameters. The INS sensor consists of three gyroscopes and three accelerometers which determine the relative position and orientation parameters of the mobile mapping vehicle by sensing angular velocity and specific force [Es05].

In urban areas with high rise buildings or in areas with dense canopies, the GNSS sensor can output less accurate navigation due to satellite signal obstruction and distortion [Pet10]. However, the INS sensor can help com- pensate for this as it maintains reasonable level of position and orientation accuracy for short intervals of time. The combination of the GNSS and INS sensors provide an effective solution as both sensors can be used to update each other frequently and maintain high global positioning accuracy. Their integration is achieved using a Kalman filter algorithm which identifies and corrects navigation errors in both the GNSS and INS sensors [GWA07]. In the Kalman filter process, the navigation information from the GNSS and INS sensors is compared to estimate the errors [IXS09]. These errors are discriminated in the Kalman filter observation unit and are then fed back into the GNSS and INS error models for correction. Thus, drifts in the INS gyroscopes and accelerometers can be corrected with the GNSS derived trajectories while in areas of poor or absent GNSS signal coverage, the posi- tion and orientation parameters can be corrected with the INS observations [Es05]. Terrestrial MMSs are also supplemented with DMI’s to provide ad- ditional information for relative positioning. The DMI is attached to the mobile mapping vehicle’s wheel and provides a measure of distance travelled by the vehicle [GQS06]. The process for estimating navigation parameters of the mobile mapping vehicle using a GNSS base station and a navigation

system is shown in Figure 2.9. The measurements from a GNSS base station

Figure 2.9: Process for estimating navigation parameters of the mobile map- ping vehicle using a GNSS base station and a navigation system.

are used to make corrections to a roving GNSS data collected with the mobile mapping vehicle. The corrected GNSS data is then integrated with INS and DMI data in a Kalman filter process to provide more accurate estimation of the vehicle’s navigation parameters.