# OBU for Accurate Navigation through Sensor Fusion in the Framework of the EMERGE Project
## 3 Sensor Fusion: Loosely Coupled Algorithm Implementation
### The Initialisation Loop
Figure 8: Scenario 1. Figure 10: Scenario 3. Figure 9: Scenario 2. Figure 12: Scenario 5. Figure 13-17 compare, on one side, the graphs of latitude, longitude, and altitude, and on the other side, the error on the same calculated as the distance from the ground truth. The gray line corresponds to GNSS-only, the blue line represents the result of IMU/GNSS

integration, and the dashed line represents the ground truth. Here, it becomes even more evident how the algorithm reduces disturbances introduced by GNSS and minimizes error. This observation is also numerically confirmed in Table 2 which presents the Root Mean Square Error data calculated with respect to the ground truth for the position obtained with GNSS-only and for the position estimated by the SF algorithm. Figure 16: Scenario 4. Figure 17: Scenario 5. Figure 15: Scenario 3. These results indicate a substantial discrepancy between the positions estimated via GNSS and the actual positions measured in the field, and demonstrate that the combined use of IMU and GNSS significantly improved the accuracy of position estimation. The velocity plots in Figures 18-22 confirm the previous analyses for the same scenarios, with a perfect overlap of the velocity estimates on all three axes for the ground truth, GNSS-only, and the result of data fusion. On the other side, the error on the three axes fluctuates slightly around zero, confirming the algorithm's good performance. Figure 6:0 Scenario 4. Figure 6:1 Scenario 5. Figure 6:2 Scenario 3. ## 6 Conclusions

This paper presents the OBU architecture for the EMERGE project, and the implementation of the navigation system, based on a multi-sensor approach. The proposal of a concrete architecture for OBU development provides a starting point in the automotive field for other application areas and services. Although in the test-bed used for this work most of the processing has been performed locally, the presented architecture can be applied to systems that foresee a microservice approach, cloud computing [36], and/or edge computing. This transformation entails moving some elements (mainly from the core layer of the onboard system architecture, i.e., layer 4 in Figure 1) out of the OBU and enhancing elements dedicated to communication, according to specific performance requirements. The modular architecture has helped in using the agile methodology for developing the product, facilitating the selection process of HW components and technologies, and error debugging. Experimental tests conducted on inertial and GNSS sensors have demonstrated their accuracy, that satisfies performance requirements of the EMERGE project and justifies their use in real automotive scenarios. The GNSS receiver provides excellent performance when integrated with the u-blox augmentation system, i.e., PointPerfect, that enhances the accuracy of the satellite navigation system from metres to centimetres. This work uses the u-blox commercial IP plan, which provides corrections through an MQTT broker. The subscription to the root topic provides to the experiment all the set of corrections--i.e., orbits, bias, atmosphere, and clock--whenever they are available. The effectiveness of the multi-sensor approach has also been validated in challenging scenarios like urban contexts. In fact, tests documented in Section 5.1.1 show that merging inertial and satellite data provides a more accurate estimate of the trajectory, particularly when the GNSS is degraded. Implementing an OBU in the automotive context also involves the power analysis of the system. The Power Management and UPS systems guarantee the operating autonomy needed by the OBU to conclude and store the states of the active processes. Conceptualisation, all authors; methodology, all authors; software, A.L.Z.S., V.I., M.B. and M.P. ; validation, A.L.Z.S., V.I., M.P., M.B., F.V. and E.C. ; formal analysis, all authors; investigation, all authors; resources, all authors; data curation, A.L.Z.S., V.I., M.P., M.B., F.V. and E.C. ; writing--original draft preparation, A.L.Z.S., V.I., M.P., F.V. and E.C.