RuAviation

Engineers at the Moscow Aviation Institute (MAI) have developed a methodology aimed at improving the accuracy and reliability of navigation systems in civil aircraft, according to the institute’s press service.

The core of this solution is a set of digital algorithms that analyze onboard sensor data, detect system faults, and provide pilots with real-time situational awareness. This approach enables rapid identification of navigation equipment malfunctions and minimizes the risk of cumulative errors.

Modern airliners primarily rely on satellite navigation as their main source of positional data. However, in environments with significant interference—such as over major metropolitan areas—satellite signals may become degraded or completely unavailable. To ensure redundancy, aircraft are equipped with autonomous inertial navigation systems (INS) based on accelerometers and gyroscopes. Typically, three identical INS units are installed onboard to provide fault tolerance in case one system fails. Nevertheless, even with this architecture, error accumulation and the need for regular calibration remain persistent challenges.

The MAI-developed solution integrates data from multiple sources, including ground-based radio navigation systems. The algorithms process all incoming parameters, identify anomalies, and compute weighted average values for pilot display, thereby maintaining navigational accuracy even in the event of partial equipment failure or external interference.

MAI specialists have placed particular emphasis on cybersecurity. The algorithms are designed to withstand deliberate attacks on navigation systems, in line with current aviation industry standards.

“At present, the project is undergoing bench testing in a virtual environment, simulating various failure and disruption scenarios. The work is expected to be completed within two years,” MAI representatives stated.

The methodology is universal and can be adapted for other modes of transport, including unmanned aerial vehicles (UAVs), underwater vehicles, and ground-based robotic systems. Currently, there are no certified solutions on the market offering comparable functionality, which distinguishes the MAI project from both domestic and international developments.