GPS World, June 2017

SENSOR FUSION Though position accuracy between IMUs is less apparent in this condition attitude results remain separated by IMU quality which is a major consideration for some mapping applications such as those using lidar or other sensors where a distance bearing calculation must be done for distant targets Test data for this scenario was collected in downtown Calgary Canada The trajectory FIGURE 2 includes several overhead bridges for brief total outages and some very dense urban conditions TABLE 2 shows the RMS error results of the three systems running both the default and land profiles The first thing to notice is that the errors are differentiated by IMU category though the differences are fairly small in the position domain thanks to the tightly coupled architecture However because GNSS information is partially available the differences seen in activating the land profile are fairly modest especially as the IMU performance rises As the clearest benefits of the land profile are seen on the entry level MEMS IMU UUT1 these will be explored graphically in FIGURES 3 and 4 Figure 3 shows the position domain and the RMS differences can be seen in a few cases where the default mode errors increased faster than Urban Canyon RMS Errors Profile IMU 2D Pos m Height m TABLE 2 RTK RMS errors for urban canyon the land profile An example of this divergence is most obvious around the 1500 second mark of the test during periods GNSS is most heavily blocked Low Dynamics Test The low dynamics test is designed to emulate conditions experienced by machine control agriculture and mining applications In this situation GNSS availability is generally not the limiting factor and can be used to control the low frequency position and velocity errors of the INS system The difficulty is managing the attitude especially azimuth errors because attitude parameters are very hard to observe without significant rotations or accelerations FIGURES 5 and 6 The low dynamics test was collected in an open sky environment and consisted of traveling in a straight line on a rural road for roughly 2 km at an average speed of 10 15 km h 16 GPS WORLD WWW GPSWORLD COM JUNE 2017 Up Vel m s Roll deg As this type of scenario provides 2D Vel m s little physical impetus the azimuth and gyroscope biases are not observable The reason for this is due to the use of the first order differential equations to estimate the navigation system errors Essentially the differential equations define how the position velocity and attitude errors change grow over time based on each other and the IMU errors The observability of a particular update is tied to additional states through the off diagonal elements of the derived transition matrix with the accelerations and rotations experienced by the system The overall RMS solution errors for RTK are provided in TABLE 3 As evident by the results presented the position and velocity errors are clearly constrained by the continuous RTKlevel GNSS position regardless of whether the land profile is enabled FIGURE 3 UUT1 position error std vs land FIGURE 4 UUT 1 attitude error std vs land Pitch deg Yaw deg DEFAULT UUT1 244 098 004 001 002 002 014 UUT2 079 076 002 001 001 001 005 UUT3 049 023 0002 001 001 002 003 LAND UUT1 170 055 005 001 002 002 012 UUT2 078 002 001 001 001 001 005 UUT3 047 023 002 001 001 002 003