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This paper deals with the problem of spaceborne pose determination of uncooperative targets, e.g. space debris. An optimized template matching approach is adopted for pose initialization, while different variants of the Iterative Closest Point (ICP) algorithm are considered for pose tracking. The algorithms process 3D point clouds generated by a scanning LIDAR. Algorithm performance is investigated within a numerical simulation environment reproducing realistic conditions in terms of target configuration and sensor operation. Results demonstrate that the proposed algorithms provide a pose estimate with 0.1° accuracy in attitude and sub-centimeter accuracy in relative position, operating with sparse point clouds.

SAR4BAT project (SAR data fusion for bathymetric data retrieval of sea bottom in coastal areas) is funded by Italian Space Agency with Kell srl as prime contractor and University of Naples as technical consultant. Its goal is the development of SAR-based bathymetric products for coastal area by processing SAR data from COSMOSkyMed and ALOS satellites. In the present paper the results of SAR4BAT project are reported with special attention to the application of wave-based techniques, which rely on the ability of local bathymetry to modify the characteristics of sea surface (swell or gravity) waves.

The Department of Aerospace Engineering of the University of Naples “Federico II” has recently carried out several experiments in the field of forest fire monitoring, based on a mini Unmanned Aerial Vehicle (UAV) prototype for both airborne remote sensing and autonomous navigation research activities. The first goal of the research was to demonstrate the feasibility of using a compact platform, capable of autonomous operation, as tactical system in missions of fire risk monitoring. To this aim, several flight campaigns were successfully carried out to test integration of avionics, electro optical payload, and telemetry and communications equipments onboard the available mini UAV prototype. Recently, ant experiment was arranged to gather image data over a controlled, real fire. This flight test represented a demonstration of the suitability of a mini UAV platform, equipped with an electro optical payload system, for missions of wildfire monitoring and mapping, as well as for fire fighting activities management.

This paper presents activities being carried out at the Department of Aerospace Engineering of the University of Naples “Federico II”, in the field of airborne remote sensing for natural disaster monitoring and of autonomous navigation, from system design to realization and test. Results of a flight test campaign for experiments of fire recognition are discussed in detail in the paper.

This paper presents activities being carried out at the Department of Aerospace Engineering of the University of Naples “Federico II” and dealing with applications of airborne remote sensing to natural disaster monitoring and of autonomous GNC, from system design to realization and test. Concurrent projects and cooperation with external research teams constitute the scenario of these activities. The reference platform adopted for system implementation and operation is the mini-UAV named 1st. The main focus of this paper is on the integrated, multi-band, hyper-spectral electro-optical sensor that has been studied for applications of forest fire risk management based on compact aeronautical platforms. The system is completed by an onboard computer for operation control and data management, and a radio transceiver for real-time data download and command upload. Additional onboard equipment, such as the GNC subsystem, is relevant to the UAV platform. Activities in progress are discussed in detail: laboratory calibration of the electro-optical sensors in use, development and implementation of algorithms to exploit the collected data for the application of interest, and flight test campaigns. Procedures and results for laboratory calibration and characterization of the electro-optical sensors are described along with the facilities that have been set up to this purpose. In the end, flight test results for both remote sensing and GNC sub-systems are presented, describing also system functionality. Specialized flight campaigns are planned for the future to acquire data over test beds arranged to simulate fire-risk-concerned areas.

This paper presents the mini-UAV named 1st (autonomous Flyer for Integration of Remote Sensing Technologies and guidance, navigation, and control aimed at monitoring environmental risk) that is under development at Department of Space Science and Engineering of University of Naples “Federico II”. The project aims at developing an autonomous system capable of performing airborne surveillance and autonomous flight. Its airframe is based on a RC-model, a reproduction of the Dornier™ DO27™ by VMAR™. The main issue of the system is the integration of Remote Sensing and Autonomous Navigation hardware. Its architecture requires the development of both hardware and software. The core of the flight control system is based on a miniature, low-cost robotic vehicle sensor suite and a low-power, small-size, Linux single board computer, both produced by Crossbow Technology™. In addition, a radio modem RM is adopted to connect the onboard computer to GCS that is installed on a PC laptop. System navigation and control logic is fully reported in the paper. Several operating modes are implemented and can be selected online by ground staff. The remote sensing payload is based on an integrated, multi-band sensor that includes a thermal imager and a hyperspectral sensor in VNIR band. It is aimed at applications of natural disasters monitoring, in particular forest fires. Auxiliary units are envisaged: on-board CPU for instrument operation control, payload data acquisition, storage, and processing, as well as data exchange with GNC units; radio-transceiver for real-time payload data/telemetry downlink and command uplink. These activities are being carried out within concurrent, coordinated projects that are contributing to different sections of the system. A campaign of flight tests will support the development of the system.

This paper describes a modern electro-optical payload system for remote sensing from aeronautical platforms that is being developed at the Department of Space Science and Engineering of the University of Naples Federico II. It is aimed at applications of natural disasters monitoring, in particular forest fires, in missions of compact platforms, also Unmanned Aerial Vehicles. These activities are being carried out within concurrent, coordinated projects that are contributing to different sections of the system. Here the selected sensors are described along with on-board subsystems dedicated to payload operation and control, activities in progress, and test campaigns being prepared.

This paper describes the research activities undertaken at the University of Naples for the development and test of advanced attitude sensors for microsatellites and nanosatellites applications. In particular, a stellar-inertial sensor and a miniature digital sun sensor are described in the paper. Both sensors are being developed for autonomous attitude determination with high accuracy. The stellar-inertial sensor is obtained by the fusion of MEMS inertial rate sensors with an advanced star sensor based on Kalman filtering. The miniature sun sensor relies on a CMOS Photodetector covered by a MEMS mask with one or more tiny holes. The paper describes sensors’ operation principle as well as their prototype development and numerical and laboratory test preliminary results.