Integration of radar altimeter sensor into navigation systems for reusable launchers

In recent years, the growing interest in re-usable launch vehicles, driven by the demand for a reliable and cost-effective access to space, has translated in an increased interest of researchers to address unique challenges related to rocket boosters vertical landing on sea-borne barges. Among the most challenging aspects of this process is the need of a precise navigation system, capable of dealing with the fast dynamics to which a re-entry vehicle is subject. While conventional launcher navigation algorithms are capable of fusing GNSS and IMU measurements, their performance cannot guarantee to satisfy the stringent requirements needed to successfully perform a booster landing. For this reason, in the case of reusable rocket boosters the use for multi-sensor navigation algorithms to increase the estimate precision is essential. The purpose of this Master thesis, carried out at the company GMV, is to investigate about, implement and test a multi-sensor hybrid navigation algorithm capable of providing the adequate accuracy needed to perform the booster pinpoint landing. In particular, to fulfill the aim of this dissertation, an error-state extended Kalman filter-based, tight-coupled, closed-loop and indirect estimator architecture fusing GNSS, IMU and radar altimeter measurements is implemented in Matlab-Simulink environment. The navigation software devised is an alternative implementation with respect to the company-developed solution and is tested using the GMV's 3DoF open-loop navigation simulator. A progressive implementation approach is followed, fusing to the IMU measurement first the GNSS observation in a tightly coupled architecture and subsequently adding the radar altimeter measurements by means of an alternative measurement model. An improvement on the state estimate is expected as radar altimeter measurements are included in the estimation.