  Citation: Bassolillo, S.R.; D’Amato, E.; Notaro, I.; Ariante, G.; Del Core, G.; Mattei, M. Enhanced Attitude and Altitude Estimation for Indoor Autonomous UAVs. Drones 2022, 6, 18. https://doi.org/10.3390/ drones6010018 Academic Editor: Higinio González Jorge Received: 24 November 2021 Accepted: 10 January 2022 Published: 12 January 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). drones Article Enhanced Attitude and Altitude Estimation for Indoor Autonomous UAVs Salvatore Rosario Bassolillo 1 , Egidio D’Amato 2, * , Immacolata Notaro 1 , Gennaro Ariante 2 , Giuseppe Del Core 2 and Massimiliano Mattei 3 1 Department of Engineering, University of Campania Luigi Vanvitelli, 81031 Aversa, Italy; salvatorerosario.bassolillo@unicampania.it (S.R.B.); immacolata.notaro@unicampania.it (I.N.) 2 Department of Science and Technology, University of Naples Parthenope, 80143 Naples, Italy; gennaro.ariante@studenti.uniparthenope.it (G.A.); giuseppe.delcore@uniparthenope.it (G.D.C.) 3 Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80125 Naples, Italy; massimiliano.mattei@unina.it * Correspondence: egidio.damato@uniparthenope.it Abstract: In recent years the use of Unmanned Aerial Vehicles (UAVs) has considerably grown in the civil sectors, due to their high flexibility of use. Currently, two important key points are making them more and more successful in the civil field, namely the decrease of production costs and the increase in navigation accuracy. In this paper, we propose a Kalman filtering-based sensor fusion algorithm, using a low cost navigation platform that contains an inertial measurement unit (IMU), five ultrasonic ranging sensors and an optical flow camera. The aim is to improve navigation in indoor or GPS-denied environments. A multi-rate version of the Extended Kalman Filter is considered to deal with the use of heterogeneous sensors with different sampling rates, and the presence of non-linearities in the model. The effectiveness of the proposed sensor platform is evaluated by means of numerical tests on the dynamic flight simulator of a quadrotor. Results show high precision and robustness of the attitude estimation algorithm, with a reduced computational cost, being ready to be implemented on low-cost platforms. Keywords: sensor fusion; kalman filtering; attitude estimation; UAV navigation 1. Introduction In the last two decades, the use of small and micro-UAVs has considerably spread, with the increased level of autonomy and the development of low cost electronics devices, i.e., microcontrollers, sensors, etc. [1]. In particular, the possibility of multi-rotors (quad- copter, hexacopeter, etc.) to take off and land vertically, to move in any direction and hover over a fixed position gives them employment for reconnaissance missions in hostile and hazardous environment [2,3], where other aircraft and robots cannot be used. However, their use requires the solution of different technological problems, first of all the need of a robust and reliable attitude estimator, possibly executable on low-cost computational hardware and using only measurements from light-weight sensors. Nowadays the most widely used platforms for UAV navigation are based on the Global Positioning System (GPS) [4] and the Inertial Navigation System (INS) [5] including an IMU with magnetic, angular rate, and gravity sensors (MARG). However, GPS is able to provide data about position by receiving information from a network of several satellites, resulting unusable in indoor environment, due to the loss of signal. MARG sensors consists of Micro Electro-Mechanical Systems (MEMS) based on gyro- scopes, accelerometers and magnetometers which can provide the orientation of a rigid body with respect to a fixed reference system. Unlike GPS sensors, they can provide atti- tude information in indoor environment too, since they do not use signal from external sources. Moreover, the growing success of these sensors in many applications [6], is due to Drones 2022, 6, 18. https://doi.org/10.3390/drones6010018 https://www.mdpi.com/journal/drones