Experimental results of a terrain relative navigation algorithm using a simulated lunar scenario

This paper deals with the problem of the navigation of a lunar lander based on the Terrain Relative Navigation approach. An algorithm is developed and tested on a scaled simulated lunar scenario, over which a tri-axial moving frame has been built to reproduce the landing trajectories. At the tip of the tri-axial moving frame, a long-range and a short-range infrared distance sensor are mounted to measure the altitude. The calibration of the distance sensors is of crucial importance to obtain good measurements. For this purpose, the sensors are calibrated by optimizing a nonlinear transfer function and a bias function using a least squares method. As a consequence, the covariance of the sensors is approximated with a second order function of the distance. The two sensors have two different operation ranges that overlap in a small region. A switch strategy is developed in order to obtain the best performances in the overlapping range. As a result, a single error model function of the distance is found after the evaluation of the switch strategy. Because of different environmental factors, such as temperature, a bias drift is evaluated for both the sensors and properly taken into account in the algorithm. In order to reflect information of the surface in the navigation algorithm, a Digital Elevation Model of the simulated lunar surface has been considered. The navigation algorithm is designed as an Extended Kalman Filter which uses the altitude measurements, the Digital Elevation Model and the accelerations measurements coming from the moving frame. The objective of the navigation algorithm is to estimate the position of the simulated space vehicle during the landing from an altitude of 3 km to a landing site in the proximity of a crater rim. Because the algorithm needs to be updated during the landing, a crater peak detector is conceived in order to reset the navigation filter with a new state vector and new state covariance. Experimental results of the navigation algorithm are presented in the paper

A Search Algorithm for Stochastic Optimization in Initial Orbit Determination

Optical observations constitute a source of angular measurements of a satellite pass. Commonly, these observations have short durations with respect to the satellite orbit period. As a consequence, the use of classical orbit determination algorithms, as Laplace, Gauss or Escobal methods, give very poor results. This thesis faces with the problem of estimating the orbital parameters of an orbiting object using its optical streak acquired by a telescope or a high accuracy camera. In this thesis a new technique is developed for the Initial Orbit Determination from optical data by exploiting the genetic algorithms. The algorithm works without restrictions on the observer location. A recent challenging problem is the Initial Orbit Determination with space- based observations. This thesis focuses on the problem of determinating the orbital parameters of a satellite from an orbiting observer in LEO, using short time observations. We present the results based on a simulation with the observer on a sun-synchronous orbit with a single observation of just 60 s. Monte Carlo simulations are presented with di erent levels of sensor accuracy to show the reliability of the algorithm. The algorithm is able to yield a candidate solution for each observation. The coplanar case is analyzed and discussed as well. Several test show the reliability of the algorithm varying the number of the observations, the initialization method, the observation period and the noise seed

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Un algoritmo di ricerca per ottimizzazione stocastica nella Determinazionale Orbitale Iniziale

Optical observations constitute a source of angular measurements of a satellite pass. Commonly, these observations have short durations with respect to the satellite orbit period. As a consequence, the use of classical orbit determination algorithms, as Laplace, Gauss or Escobal methods, give very poor results. This thesis faces with the problem of estimating the orbital parameters of an orbiting object using its optical streak acquired by a telescope or a high accuracy camera. In this thesis a new technique is developed for the Initial Orbit Determination from optical data by exploiting the genetic algorithms. The algorithm works without restrictions on the observer location. A recent challenging problem is the Initial Orbit Determination with space- based observations. This thesis focuses on the problem of determinating the orbital parameters of a satellite from an orbiting observer in LEO, using short time observations. We present the results based on a simulation with the observer on a sun-synchronous orbit with a single observation of just 60 s. Monte Carlo simulations are presented with di erent levels of sensor accuracy to show the reliability of the algorithm. The algorithm is able to yield a candidate solution for each observation. The coplanar case is analyzed and discussed as well. Several test show the reliability of the algorithm varying the number of the observations, the initialization method, the observation period and the noise seed

A genetic algorithm for Initial Orbit Determination from a too short arc optical observation

Optical observations constitute a source of angular measurements of a satellite pass. Commonly, these observations have short durations with respect to the satellite orbit period. As a consequence, the use of classical orbit determination algorithms, as Laplace, Gauss or Escobal methods, give very poor results. The present work faces with the problem of estimating the orbital parameters of an orbiting object using its optical streak acquired by a telescope or a high accuracy camera. In the paper a new technique is developed for the Initial Orbit Determination from optical data by exploiting the genetic algorithms. The algorithm works without restrictions on the observer location. A recent challenging problem is the Initial Orbit Determination with space-based observations. This work focuses on the problem of determinating the orbital parameters of a satellite from an orbiting observer in LEO, using short time observations. We present the results based on a simulation with the observer on a sun-synchronous orbit with a single observation of just 60 s. Monte Carlo simulations are presented with different levels of sensor accuracy to show the reliability of the algorithm. The algorithm is able to yield a candidate solution for each observation. The coplanar case is analyzed and discussed as well

An heuristic approach to the problem of initial orbit determination: A test case with GEO observations

The orbit determination of a satellite in a geostationary orbit is usually based on optical observations. Telescopes all around the Earth are observing the geostationary ring to obtain periodically new measurements in order to update the estimation of the objects’ orbits. One critical aspect of the orbit determination process is the initial orbit determination because no a priori information are available. This paper proposes a new method based on search algorithms with heuristic principles aming to find the six independent orbital parameters that best fit the observations. A genetic algorithm makes the candidate solutions moving in a solution space of six dimensions. The problem is reduced into a two dimensional space with a Lambert’s solver using the initial and final angular observations. This paper presents the results using a single image acquired by a Earth-based telescope, the acquired streak is correlated to the objects of the NORAD database

Space debris orbit determination from an ISS onboard camera

An autonomous system for the orbit determination of space debris has been studied for a new payload on the ISS. Space based observations could be a very important source for optical observations. An ISS onboard camera could provide measurements for a large class of satellites on different orbits. The high chances of observations and the possibility of scanning large regions of the sky suggest that the camera should be in continuous activity with different modes. This article will present a possible site for the installation of the camera, the treatment of the images to obtain the angular measurements and a genetic algorithm to estimate the orbital parameters of the observed object. The genetic algorithm will use the time-tagged orbital angular observations and a very accurate estimation of the camera site in order to evaluate the target orbit. The algorithm will use only two variables to determine the output: the initial and the final relative distance between observer and target, these two values will identify uniquely the orbit of the observed object. The camera will be mounted on a pan-tilt system to obtain longer observations by tracking the object. The possible high angular velocities, the conditions of illumination and the relative positions force the orbit determination algorithm to be efficient and reliable also on very short arc passes. The camera system will be characterized by a very compact design, low power consumption and low mass. The electric system will be capable to operate continuously in the space environment. The system will downlink data from the angular observations, the on-board estimated orbital parameters and some images to allow the testing of the performances and the off-line processing to obtain a better estimation

Analysis and experimentation of an optical-flow-based navigation algorithm for a lander

This paper deals with the development and the testing of an algorithm for the landing phase of a space vehicle, based on the optical-flow technique to measure the trajectory’s velocity. The Optical-flow sensor is obtained through the processing of 2-D images captured by a camera by knowing the acquisition time for each frame. Image processing techniques have been used for the implementation of an algorithm capable of detecting complex structures. The algorithm can detect craters and the shadows created by the craters themselves. It is possible to obtain the direction of the light by simply connecting the center of the crater with the center of the shadowed zone. The information of the light direction is used to obtain a solar compass. Finally, an extended Kalman filter has been used to estimate the state. The navigation filter is tested on the Lunar Simulator Facility at the Automation, Robotics, and Control for Aerospace Laboratory (ARCAlab) of the Department of Astronautical, Electrical and Energy Engineering of Sapienza University of Rome