The tilt angles (roll in 6d and pitch in 6e) converge when the vehicle is static, however the heading (6f) remains on the initial value with slight drift during the static period. The heading becomes observable when the vehicle moves and the GPS-derived velocity vector is then used to initialise the heading. From Figure 6f it is easy to see that the heading quickly changes from the initial value to the correct value when the vehicle starts to move. In the last section of the heading curve in Figure 6f, the heading has a jump of about 126deg in comparison with the initial value. In comparison with the compass data collected in the test, the angle at the end reflects the correct heading direction. Because the vehicle starts and stops at the same site and heads in the same direction the correct heading angle at the end demonstrates that the integration Kalman filtering works properly, at least in a qualitative sense.

Performance in tunnels
One test was performed in the Jenolan Caves area near Bathurst. The road goes through a tunnel near the Jenolan Caves township. The tunnel has a length of 197.7m in east, and 32.8m in north. It took 45sec to drive through the tunnel, including the time waiting due to traffic. Figure 7a shows the entrance to the tunnel, and Figure 7b depicts the trajectory from GPS and GPS/INS solutions. During the 45-second GPS outage in the tunnel, the INS solution correctly outlines the shape of the tunnel. This result demonstrates that the integration system is working satisfactorily – once an accurate navigation solution and the inertial sensor biases have been estimated before the vehicle enters the tunnel.

The second test was performed in the Sydney Airport tunnel, as depicted in Figure 8. There are two successive GPS outages. The first 17-second GPS outage occurred under a bridge just 12 seconds before the car entered the tunnel, and then a 44-second GPS outage in the tunnel itself.

Figure 9 illustrates the integrated solution (in blue) and the GPS-only solution (in red). It can be seen that the two GPS outages are bridged smoothly.

An FPGA-based real-time GPS/INS integrated system has been developed. A time-sync UART is designed to connect with the Nios II processor system to enable communication between the Nios II and the GPS and INS devices, as well as timesynchronise the GPS and INS data streams.

The embedded software has been developed using eCos – an open source embedded operating system. The software is programmed to implement multiple tasks; decoding the GPS and INS data streams, time synchronisation, strapdown inertial computation, and the integration Kalman filtering. With eCos support, the software implements the FAT32 filing system for CF card I/O, operation status display on the LCD, and button controls. The real-time solution is sent out via two additional UARTs and can be displayed on a GoogleEarth viewer. Long-term tests have demonstrated the functionality and operational robustness of the embedded software.

The GPS/INS integrated algorithm has been developed and tested in the laboratory and in the field. The results have demonstrated that the integration Kalman filter estimates the inertial errors correctly, to compensate for the drift in the inertial solution. The results of the tests in several tunnels have shown that the corrected INS solution can bridge the GPS outages with reasonable accuracy.

The project is funded under the Australian Cooperative Research Centre for Spatial Information (CRCSI). The authors would like to acknowledge the support from the CRC-SI.