This work presents an innovative approach for tuning the Kalman filter in INS/GNSS integration, combining states from the inertial navigation system (INS) and data from the Global Navigation Satellite System (GNSS) to enhance navigation accuracy. The INS uses measurements from accelerometers and gyroscopes, which are subject to uncertainties in scale factor, misalignment, non-orthogonality, and bias, as well as temporal, thermal, and vibration variations. The GNSS receiver faces challenges such as multipath, temporary signal loss, and susceptibility to high-frequency noise. The novel approach for Kalman filter tuning involves previously performing Monte Carlo simulations using ideal data from a predetermined trajectory, applying the inertial sensor error model. For the indirect filter, errors from inertial sensors are used, while, for the direct filter, navigation errors in position, velocity, and attitude are also considered to obtain the process noise covariance matrix Q. This methodology is tested and validated with real data from Castro Leite Consultoria’s commercial platforms, PINA-F and PINA-M. The results demonstrate the efficiency and consistency of the estimation technique, highlighting its applicability in real scenarios.

This work presents the design, simulation, and validation of an embedded guidance, navigation, and control (GNC) system on a simulated onboard platform for the first stage of a microlauncher vehicle. The objective is to evaluate the performance and feasibility of an embedded control architecture throughout powered flight. The control strategy adopted is a proportional-integral-derivative (PID) controller with gain scheduling, employing gains that are tuned by a linear quadratic (LQ) approach to counteract vehicle dynamics changes. The guidance unit supplies reference attitude angles, and the navigation unit estimates vehicle orientation based on inertial measurements in rotation matrices and Euler angles. The validation process involves software-in-the-loop (SIL) and hardware-in-the-loop (HIL) simulations, with the GNC algorithms executed in real time on an embedded hardware platform. Results show excellent pitch stabilization, accurate tracking of the reference trajectory, and actuator commands within operational limits. The simulated vehicle response is well correlated with expected mission profiles. In addition, functional requirements and verification procedures for the GNC system are also formally stated. These findings justify the development of robust embedded avionics systems for microlaunchers and provide an experimentally verified methodological framework to be applied in the future in small satellite launch vehicles.