Understanding IMU Data Gaps: Causes and Mitigation Strategies

Introduction

Inertial Measurement Units (IMUs) serve as critical components in various systems, providing essential data for navigation, orientation, and motion tracking. Despite their reliability, IMUs may encounter data gaps, disrupting the continuity and accuracy of information. Understanding the causes behind these interruptions and employing effective setup and post-processing strategies becomes pivotal in ensuring the integrity of collected data.

Causes of IMU Data Gaps

IMU data gaps can stem from various sources, including:

1. Connection Issues:
   
   Unstable physical connections or disruptions in communication channels between the IMU and the processing unit can lead to intermittent data loss.
   
   External factors like electromagnetic interference can interfere with signal transmission, causing temporary gaps in data recording.
2. Power Source Instability:
   
   Fluctuations in power supply, voltage drops, or sudden interruptions can disrupt IMU operations, resulting in data gaps. This instability may occur due to inadequate power conditioning or issues within the power supply system.
3. Receiver Error/INS Reset:
   
   Errors within the receiver or an Inertial Navigation System (INS) reset can also contribute to data gaps.
4. Data Link Bandwidth Limitations:
   
   Bandwidth limitations within the data link can result in numerous small gaps in data recording. If a customer uses NovAtel Application Suite, this software uses approximately 20 – 30 output logs solely for data display, things like this contribute to IMU data loss.

Mitigation Strategies and Recommendations

Addressing IMU data gaps requires a multifaceted approach involving several strategies:

1. Post Processing:
   
   Refining post-processing techniques is crucial as errors during this phase can exacerbate issues stemming from IMU data gaps. Employing interpolation to estimate missing data mitigates these gaps, but caution is necessary to prevent significant error propagation, especially when double integrating interpolated data. Thus, ensuring precision in post-processing becomes pivotal in minimizing the impact of IMU data gaps rather than worsen them.
2. Data Logging:
   
   Logging data into the receiver's internal memory can be advisable. For example, recording the BESTPOS message into the receiver's internal memory requires specific commands like:
   
   FILECONFIG OPEN
LOG FILE BESTPOSB ONTIME 1
SAVECONFIG
3. Enhancing Data Link Efficiency:
   
   To reduce bandwidth consumption, using a terminal like TeraTerm for receiver communication is recommended. Further guidance can be found on the NovAtel OEM7 Receiver User Documentation Portal.
   
   Consider employing NovAtel Application Suite (NAS) for data collection and real-time monitoring. Pay particular attention to the IMU status on Field 6 using LOG RAWIMUSA for comprehensive insights.
4. Monitoring and Prevention:
   
   Establish a robust monitoring system to identify potential issues during data collection. Regular checks for cable integrity, power stability, and buffer capacity can help prevent data gaps from occurring.
5. Improving Hardware Reliability:
   
   Address hardware-related issues by upgrading connectors, ensuring stable power supplies, and optimizing buffer capacities to significantly reduce the occurrence of gaps.

Conclusion

IMU data gaps present challenges in maintaining data accuracy and continuity. Understanding the root causes, implementing effective post-processing strategies like interpolation within limitations, and addressing hardware issues are vital in managing and minimizing the impact of these interruptions. By proactively identifying and rectifying potential causes, researchers and operators can maintain the reliability and precision of IMU data, enhancing the overall performance of the system.