Observability Analysis and Navigation Algorithm Design for Mars Aerocapture

This study addresses the challenge of navigating Mars aerocapture under parameter uncertainty. Dynamic and measurement models for the probe during Mars aerocapture were established, and observability analysis was conducted to ensure navigation estimator convergence. Leveraging a Gaussian Process, Mars atmospheric density was modeled, considering inherent uncertainties. A navigation algorithm for Mars aerocapture was proposed using the Unscented Schmidt-Kalman Filter, augmenting uncertain parameters into the system state and considering their impact through augmented state and covariance matrix. Simulation results validated the efficacy of the proposed navigation algorithm.