ROBUST NAVIGATION SYSTEM FOR PLANETARY LANDERS - EXPRO+

ObjectivesTo implement and test navigation reinitialisation logics that maximise the likelihood of safe recovery from navigation filter divergence during descent and landing.DescriptionA lander's navigation system faces extreme challenges in an environment that is poorly modeled and highly variable, leading to complex sensor stimulations and interactions across a wide range flight paramteres (e.g. altritude, attitude, etc.). Vehicle dynamics demand rapid deceleration from high velocity to a complete stop. During descent and landingan irreversible phase in most missionsaborts or retries are impossible due totrajectory physics. Landing failures can often be traced back to a navigation failure driven by these effects. Recovery from an uncontained navigation failure is exceptionally unlikely. However, a failure in the navigation system should not automatically lead to total loss of navigation capability. A well-designed system includes multiple health monitors and acceptance conditions, from low-level sensor electronics to high-level navigation filter updates. Monitors are periodically checked to enable the fastest possible recovery action,which may involve reconfiguration, switching to backup units, or discarding faulty measurements. Despite these safeguards, some failures propagate into the estimatedstate vector, often causing fatal consequences and loss of navigation function. This typically results in an inability to safely contact the surface. But before reaching this critical failure, a robust navigation design should incorporate an ultimate fallback: an on-the-flyreinitialization procedure. This activity broadly addresses the implementation and testing of reinitialization procedures, starting with the detection of navigation system failures. The following tasksshall be conducted:1. Implement or adapt ageneric precision navigation solution to be tested in Enceladuslanding scenarios. The navigation design shall build on establishedcompany orconsortium heritage and use performance models for image or terrain-relative processing.2. Develop a stochastic failureinjector, preceded by thorough research into critical failuresthrough detailed sensor and pseudo-sensor analysis, navigation system review, andhistorical mishap investigations.3. Perform trade-offs and implement navigation filter reinitialization logics along with theirtriggering conditions.4. Conduct performance and robustness simulation campaigns.5. Port and validate the selected reinitialization procedure on a Processor-in-the-Loop(PIL) setup integrated with the navigation flight software, verifying result reproducibility andembeddability.