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This paper presents an innovative approach to design relative trajectories suitable for close-proximity operations in orbit, by assigning high-level constraints regarding their stability, shape and orientation. Specifically, this work is relevant to space mission scenarios, e.g. formation flying, on-orbit servicing, and active debris removal, which involve either the presence of two spacecraft carrying out coordinated maneuvers, or a servicing/recovery spacecraft (chaser) performing monitoring, rendezvous and docking with respect to another space object (target). In the above-mentioned scenarios, an important aspect is the capability of reducing collision risks and of providing robust and accurate relative navigation solutions. To this aim, the proposed approach exploits a relative motion model relevant to two-satellite formations, and developed in mean orbit parameters, which takes the perturbation effect due to secular Earth oblateness, as well as the motion of the target along a small-eccentricity orbit, into account. This model is used to design trajectories which ensure safe relative motion, to minimize collision risks and relax control requirements, providing at the same time favorable conditions, in terms of target-chaser relative observation geometry for pose determination and relative navigation with passive or active electro-optical sensors on board the chaser. Specifically, three design strategies are proposed in the context of a space target monitoring scenario, considering as design cases both operational spacecraft and debris, characterized by highly variable shape, size and absolute rotational dynamics. The effectiveness of the proposed design approach in providing favorable observation conditions for target-chaser relative pose estimation is demonstrated within a simulation environment which reproduces the designed target-chaser relative trajectory, the operation of an active LIDAR installed on board the chaser, and pose estimation algorithms.

As well known, micro and nanosatellites are being proposed for a variety of space missions, due to the advantages offered in terms of flexibility, cost and development time-scales. They also allow the development of space missions based on distributed architectures, composed of a number of small platforms in coordinated flight. However, technological advancements are still needed to make micro and nanosatellite competitive with respect to larger platforms. In this paper, we explore the potentiality offered by hyper hemispheric lens for the development of miniaturized and multi-function sensors for use on board of micro satellites. Hyper hemispheric lens belong to the ultra-wide field-of-view optical objectives. Here a novel optics of this category is presented. Its field of view is 360° in azimuth (panoramic capabilities) and 135° for the off-boresight angle (hyper-hemispheric field). With such capabilities the lens may be exploited as a very-large field-of-view optics where moving parts can be avoided. This is of interest to space applications, in which devices with any moving part, representing a possible point of failure, shall be avoided or reduced to the minimum. A hyper hemispheric lens may, then, be adopted for electro optical devices in space satellite subsystems, such as star-, Sun- and Earth-sensors, or for monitoring the environment surrounding the satellite in the case of on-orbit servicing or active debris removal operations. Weight and cost budgets for small and micro satellites are also important parameters to determine their success. Hyper hemispheric lens may be kept quite compact in dimension and the need of a single imaging detector, for a so large field of view, strongly reduces costs. In this paper, we explore possible applications of a multi-purpose space device based on a hyper hemispheric lens on board of micro and nanosatellites.

This paper aims at investigating the performance of a LIDAR-based system for pose determination of uncooperative targets. This problem is relevant to both debris removal and on-orbit servicing missions, and requires the adoption of suitable electro-optical sensors on board of a chaser platform, as well as model-based techniques for target detection and pose estimation. In this paper, a three dimensional approach is pursued in which the point cloud generated by a LIDAR is exploited for pose estimation. Specifically, the condition of close proximity flight to a large debris is considered, in which the relative motion determines a large variation of debris appearance and coverage in the sensor field of view, thus producing challenging conditions for pose estimation. A customized three dimensional Template Matching approach is proposed for fast and reliable pose initial acquisition, while pose tracking is carried out with an Iterative Closest Point algorithm exploiting different measurement-model matching techniques. Specific solutions are envisaged to speed algorithm convergence and limit the size of the point clouds used for pose initial acquisition and tracking to allow autonomous on-board operation. To investigate proposed approach effectiveness and achievable pose accuracy, a numerical simulation environment is developed implementing realistic debris geometry, debris-chaser close-proximity flight, and sensor operation. Results demonstrate algorithm capability of operating with sparse point clouds and large pose variations, while achieving sub-degree and sub-centimeter accuracy in relative attitude and position, respectively.

In this paper an original, easy to reproduce, semi-analytic calibration approach is developed for hardware-in-the-loop performance assessment of pose determination algorithms processing point cloud data, collected by imaging a non-cooperative target with LIDARs. The laboratory setup includes a scanning LIDAR, a monocular camera, a scaled-replica of a satellite-like target, and a set of calibration tools. The point clouds are processed by uncooperative model-based algorithms to estimate the target relative position and attitude with respect to the LIDAR. Target images, acquired by a monocular camera operated simultaneously with the LIDAR, are processed applying standard solutions to the Perspective-n-Points problem to get high-accuracy pose estimates which can be used as a benchmark to evaluate the accuracy attained by the LIDAR-based techniques. To this aim, a precise knowledge of the extrinsic relative calibration between the camera and the LIDAR is essential, and it is obtained by implementing an original calibration approach which does not need ad-hoc homologous targets (e.g., retro-reflectors) easily recognizable by the two sensors. The pose determination techniques investigated by this work are of interest to space applications involving close-proximity maneuvers between non-cooperative platforms, e.g., on-orbit servicing and active debris removal.

The search for undiscovered planets outside the solar system is a scientific topic that is rapidly spreading into the astrophysical and engineering communities. In this framework, the design of an innovative payload to detect exoplanets from a nano-sized space platform, like a 3U cubesat, is presented. The selected detection method is photometric transit, and the payload aims to detect flux decrements down to ~0.01% with a precision of 12 ppm. The payload design is also aimed at false positive recognition. The solution consists of a four-facets pyramid on the top of the payload, to allow for measurement redundancy and low-resolution spectral dispersion of the star images. The innovative concept is the use of a small and cheap platform for a relevant astronomical mission. The faintest observable target star has V-magnitude equal to 3.38. Despite missions aimed at ultra-precise photometry from microsatellites (e.g., MOST, BRITE), the transit of exoplanets orbiting very bright stars has not yet been surveyed photometrically from space, since any observation from a small/medium sized (30 cm optical aperture) telescope would saturate the detector. This cubesat mission can provide these missing measurements. This work is set up as a demonstrative project to verify the feasibility of the payload concept.

This paper presents an innovative algorithm developed for attitude determination of a space platform. The algorithm exploits images taken from a multi-purpose panoramic camera equipped with hyper-hemispheric lens and used as star tracker. The sensor architecture is also original since state-of-the-art star trackers accurately image as many stars as possible within a narrow- or medium-size field-of-view, while the considered sensor observes an extremely large portion of the celestial sphere but its observation capabilities are limited by the features of the optical system. The proposed original approach combines algorithmic concepts, like template matching and point cloud registration, inherited from the computer vision and robotic research fields, to carry out star identification. The final aim is to provide a robust and reliable initial attitude solution (lost-in-space mode), with a satisfactory accuracy level in view of the multi-purpose functionality of the sensor and considering its limitations in terms of resolution and sensitivity. Performance evaluation is carried out within a simulation environment in which the panoramic camera operation is realistically reproduced, including perturbations in the imaged star pattern. Results show that the presented algorithm is able to estimate attitude with accuracy better than 1° with a success rate around 98% evaluated by densely covering the entire space of the parameters representing the camera pointing in the inertial space.

The paper focuses on a navigation facility, relying on commercial-off-the-shelf (COTS) technology, developed to generate high-accuracy attitude and trajectory measurements in postprocessing. Target performance is cm-level positioning with tenth of degree attitude accuracy. The facility is based on the concept of GPS-aided inertial navigation but comprises carrier-phase differential GPS (CDGPS) processing and attitude estimation based on multiantenna GPS configurations. Expected applications of the system include: (a) performance assessment of integrated navigation systems, developed for general aviation aircraft and medium size unmanned aircraft systems (UAS); (b) generation of reference measurements to evaluate the flight performance of airborne sensors (e.g., radar or laser); and (c) generation of reference trajectory and attitude for improving imaging quality of airborne remote sensing data. The paper describes system architecture, selected algorithms for data processing and integration, and theoretical performance evaluation. Experimental results are also presented confirming the effectiveness of the implemented approach.

The present paper focuses on the development of an algorithm for safely and optimally managing the routing of aircraft on an airport surface in future airport operations. This tool is intended to support air traffic controllers’ decision-making in selecting the paths of all aircraft and the engine startup approval time for departing ones. Optimal routes are sought for minimizing the time both arriving and departing aircraft spend on an airport surface with engines on, with benefits in terms of safety, efficiency and costs. The proposed algorithm first computes a standalone, shortest path solution from runway to apron or vice versa, depending on the aircraft being inbound or outbound, respectively. For taking into account the constraints due to other traffic on an airport surface, this solution is amended by a conflict detection and resolution task that attempts to reduce and possibly nullify the number of conflicts generated in the first phase. An example application on a simple Italian airport exemplifies how the algorithm can be applied to true-world applications. Emphasis is given on how to model an airport surface as a weighted and directed graph with non-negative weights, as required for the input to the algorithm.

A new algorithm for ship wake detection is developed with the aim of ship heading and velocity estimation. It exploits the Radon transform and utilizes merit indexes in the intensity domain to validate the detected linear features as real components of the ship wake. Finally, ship velocity is estimated by state-of-the-art techniques of azimuth shift and Kelvin arm wavelength. The algorithm is applied to 13 X-band SAR images from the TerraSAR-X and COSMO/SkyMed missions with different polarization and incidence angles. Results show that the vast majority of wake features are correctly detected and validated also in critical situations, i.e., when multiple wake appearances or dark areas not related to wake features are imaged. The ship route estimations are validated with truth-at-sea in seven cases. Finally, it is also verified that the algorithm does not detect wakes in the surroundings of 10 ships without wake appearances.

The operation and test of a multi-spot digital sun sensor for precise sun-line determination is described. The image forming system consists of an opaque mask with multiple pinhole apertures producing multiple, simultaneous, spot-like images of the sun on the focal plane. The sun-line precision can be improved by averaging multiple simultaneous measures. Nevertheless, the sensor operation on a wide field of view requires acquiring and processing images in which the number of sun spots and the related intensity level are largely variable. To this end, a reliable and robust image acquisition procedure based on a variable shutter time has been considered as well as a calibration function exploiting also the knowledge of the sun-spot array size. Main focus of the present paper is the experimental validation of the wide field of view operation of the sensor by using a sensor prototype and a laboratory test facility. Results demonstrate that it is possible to keep high measurement precision also for large off-boresight angles.

This paper describes the high precision digital sun sensor under development at the University of Naples. The sensor determines the sun line orientation in the sensor frame from the measurement of the sun position on the focal plane. It exploits CMOS technology and an original optical head design with multiple apertures. This allows simultaneous multiple acquisitions of the sun as spots on the focal plane. The sensor can be operated either with a fixed or a variable number of sun spots, depending on the required field of view and sun-line measurement precision. Multiple acquisitions are averaged by using techniques which minimize the computational load to extract the sun line orientation with high precision. Accuracy and computational efficiency are also improved thanks to an original design of the calibration function relying on neural networks. Extensive test campaigns are carried out using a laboratory test facility reproducing sun spectrum, apparent size and distance, and variable illumination directions. Test results validate the sensor concept, confirming the precision improvement achievable with multiple apertures, and sensor operation with a variable number of sun spots. Specifically, the sensor provides accuracy and precision in the order of 1 arcmin and 1 arcsec, respectively.

This paper presents a customized three-dimensional template matching technique for autonomous pose determination of uncooperative targets. This topic is relevant to advanced space applications, like active debris removal and on-orbit servicing. The proposed technique is model-based and produces estimates of the target pose without any prior pose information, by processing three-dimensional point clouds provided by a LIDAR. These estimates are then used to initialize a pose tracking algorithm. Peculiar features of the proposed approach are the use of a reduced number of templates and the idea of building the database of templates on-line, thus significantly reducing the amount of on-board stored data with respect to traditional techniques. An algorithm variant is also introduced aimed at further accelerating the pose acquisition time and reducing the computational cost. Technique performance is investigated within a realistic numerical simulation environment comprising a target model, LIDAR operation and various target-chaser relative dynamics scenarios, relevant to close-proximity flight operations. Specifically, the capability of the proposed techniques to provide a pose solution suitable to initialize the tracking algorithm is demonstrated, as well as their robustness against highly variable pose conditions determined by the relative dynamics. Finally, a criterion for autonomous failure detection of the presented techniques is presented.

Long gravity waves or swell dominating the sea surface is known to be very useful to estimate seabed morphology in coastal areas. The paper reviews the main phenomena related to swell waves propagation that allow seabed morphology to be sensed. The linear dispersion is analysed and an error budget model is developed to assess the achievable depth accuracy when Synthetic Aperture Radar (SAR) data are used. The relevant issues and potentials of swell-based bathymetry by SAR are identified and discussed. This technique is of particular interest for characteristic regions of the Mediterranean Sea, such as in gulfs and relatively close areas, where traditional SAR-based bathymetric techniques, relying on strong tidal currents, are of limited practical utility.

This paper reports on a model developed for evaluating major system performance of a spaceborne bistatic synthetic aperture radar (SAR) for remote sensing applications. The procedure accounts for formation flying aspects. It is particularly aimed at comparison of monostatic and bistatic cases, and, as a test case, it is applied to study a novel configuration, based on a small satellite equipped with a receiving-only antenna orbiting in tandem with a large, noncooperative transmitting spacecraft, the Italian COSMO-SkyMed mission. Numerical results and plots show the effectiveness of the procedure as a mission design tool and put in evidence key issues and characteristics of the proposed spaceborne bistatic formation.

The application of the hyperacuity technique to image processing of star trackers is analysed. An analytical study of the error introduced by the centroiding algorithm is presented and it is shown that a systematic contribution and a random one exist. They result from image processing assumptions and photometric measure uncertainty, respectively. Their behaviour is characterised by means of numerical simulations that are based on optics theoretical point spread functions. The latter ones take into account both defocus and diffraction effects. First, measured star position uncertainty is evaluated as a function of defocus. As a result, a criterion for optimal defocus is presented. Subsequently, an original procedure for systematic centroiding error correction by means of a backpropagation neural network is described. It is also suitable for real hardware calibration. When applied to one of the considered numerical models, the position computation accuracy is improved from 0.01 to 0.005 pixels.

Surface current variations generated by underwater bottom topography produce intensity modulations in SAR images. The direct inversion from image intensity to bathymetry is difficult, in general, because of the theoretical complexity of the involved physical mechanisms and the practical consideration that most of the required parameters cannot be derived from SAR data. The conventional approach for SAR bathymetry relies on the forward mechanism, i.e. the simulation of SAR images from (partially) known bottom topography and, then, the adjustment of the bathymetry through iterative comparison between simulated and collected images. The present paper deals with the development of a bathymetric SAR algorithm able to perform the direct inversion limiting the need for a-priori information or in-situ measurements, and for human intervention in the processing chain. The proposed approach is tested on COSMO-SkyMed data collected over coastal regions in the Gulf of Naples, showing that dense coverage and metric accuracy can be achieved even when the current is not enough strong to dominate SAR response.

A system study of a spaceborne along-track synthetic aperture radar (SAR) interferometer is presented. This sensor has been successfully experienced for detecting moving targets by using only airborne installations. Several key issues must be addressed when spaceborne configurations are envisaged. To this end, a quantitative evaluation of system performance and measurement accuracy has been conducted. First, the identification of possible space configurations has been accomplished. In particular, the two antennas can operate on a single satellite or they can be carried along appropriate trajectories by two spacecrafts. Then, an error budget of radial velocity measurement accuracy has been performed. Finally, two possible mission scenarios are dealt in details, and numerical results are reported.

An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components.

This paper deals with star tracker algorithms validation based on star field scene simulation and hardware-in-the-loop test configuration. A laboratory facility for indoor tests, based on the simulation of star field scenes, is presented. Attainable performance is analyzed theoretically for both static and dynamic simulations. Also, a test campaign is presented, in which a star sensor prototype with real-time, fully autonomous capability is exploited. Results that assess star field scene simulation performance and show the achievable validation for the sensor algorithms and performance in different operating modes (autonomous attitude acquisition, attitude tracking, and angular rate-only) and different aspects (coverage, reliability, and measurement performance) are discussed.

This paper focuses on a hardware-in-the-loop facility aimed at real-time testing of architectures and algorithms of multisensor sense and avoid systems. It was developed within a research project aimed at flight demonstration of autonomous non-cooperative collision avoidance for Unmanned Aircraft Systems. In this framework, an optionally piloted Very Light Aircraft was used as experimental platform. The flight system is based on multiple-sensor data integration and it includes a Ka-band radar, four electro-optical sensors, and two dedicated processing units. The laboratory test system was developed with the primary aim of prototype validation before multi-sensor tracking and collision avoidance flight tests. System concept, hardware/software components, and operating modes are described in the paper. The facility has been built with a modular approach including both flight hardware and simulated systems and can work on the basis of experimentally tested or synthetically generated scenarios. Indeed, hybrid operating modes are also foreseen which enable performance assessment also in the case of alternative sensing architectures and flight scenarios that are hardly reproducible during flight tests. Real-time multisensor tracking results based on flight data are reported, which demonstrate reliability of the laboratory simulation while also showing the effectiveness of radar/electro-optical fusion in a non-cooperative collision avoidance architecture.

This paper presents the preliminary results obtained within a research project aimed at the development of a remote sensing system for forest fires monitoring in missions of compact airborne platforms. The core of the system is an integrated, multi-/hyper-spectral suite of electro-optical sensors. They were selected to get enhanced ability in forest fire detection and monitoring. The system is completed by a dedicated on-board computer for sensor control. It is capable of autonomous operation and it is also in charge of data exchange with the on-board navigation and flight control system. Two different configurations are described, relevant to different aircrafts: a mini UAV and a certified, two-seat light aircraft. Results of the first flight experiments are presented, that highlight performance achievable by the system.

This paper deals with design and prototype development of an Active Pixel Sensor — based miniature sun sensor and a laboratory facility for its indoor test and calibration. The miniature sun sensor is described and the laboratory test facility is presented in detail. The major focus of the paper is on tests and calibration of the sensor. Two different calibration functions have been adopted. They are based, respectively, on a geometrical model, which has required least-squares optimisation of system physical parameters estimates, and on neural networks. Calibration results are presented for the above solutions, showing that accuracy in the order of 0.01° has been achieved. Neural calibration functions have attained better performance thanks to their intrinsic auto-adaptive structure.