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We consider constrained multiple-spacecraft reconfigurations outside of a gravity well in deep space. As opposed to the single-spacecraft scenario, such reconfigurations involve collision avoidance constraints that can be formalized and embedded in a nonconvex.
A control strategy for sensor-based collision avoidance and the supporting.
The Program to Optimize Simulated Trajectories II (POST2) is used as a basis for an end-to-end descent and landing trajectory simulation that is essential in determining the design and performance capability of lunar descent and landing system models and lunar environment models for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project. This POST2-based ALHAT simulation provides descent and landing simulation capability by integrating lunar environment and lander system models (including terrain, sensor, guidance, navigation, and control models), along with the data necessary to design and operate a landing system for robotic, human, and cargo lunar-landing success. This paper presents the current and planned development and model validation of the POST2-based end-to-end trajectory simulation used for the testing, performance and evaluation of ALHAT project system and models.
In the fall of 2004, the Earth Science Mission Operations Project tasked the Goddard Space Flight Center (GSPC) Flight Dynamics Analysis Branch with establishment of a process to protect the high-value Earth Observing System (EOS) missions (Terra, Aqua, and Aura) from close approaches with space debris and other orbiting objects. An agreement between GSFC and the United States Strategic Command was put in place so that close approach predictions would be routinely generated. This paper describes the ESMO conjunction assessment process for the EOS satellites. Process details, including tools and algorithms developed, are discussed. Particular details for a predicted close approach between Terra and a piece of space debris that resulted in the execution of a debris avoidance maneuver are included. This close approach example is described in detail fiom the first screening identification through execution of the mitigation maneuver to illustrate both the process and lessons learned fiom its implementation.
The Human Factors Implementation Team (HFIT) process has been used to verify human factors requirements for NASA International Space Station (ISS) payloads since 2003, resulting in $2.4 million in avoided costs. This cost benefit has been realized by greatly reducing the need to process time-consuming formal waivers (exceptions) for individual requirements violations. The HFIT team, which includes astronauts and their technical staff, acts as the single source for human factors requirements integration of payloads. HFIT has the authority to provide inputs during early design phases, thus eliminating many potential requirements violations in a cost-effective manner. In those instances where it is not economically or technically feasible to meet the precise metric of a given requirement, HFIT can work with the payload engineers to develop common sense solutions and formally document that the resulting payload design does not materially affect the astronaut s ability to operate and interact with the payload. The HFIT process is fully ISO 9000 compliant and works concurrently with NASA s formal systems engineering work flow. Due to its success with payloads, the HFIT process is being adapted and extended to ISS systems hardware. Key aspects of this process are also being considered for NASA's Space Shuttle replacement, the Crew Exploration Vehicle.
The Mars Reconnaissance Orbiter reached Mars on March 10, 2006 and performed a Mars orbit insertion maneuver of 1 km/s to enter into a large elliptical orbit. Three weeks later, aerobraking operations began and lasted about five months. Aerobraking utilized the atmospheric drag to reduce the large elliptical orbit into a smaller, near circular orbit. At the time of MRO aerobraking, there were three other operational spacecraft orbiting Mars and the navigation team had to minimize the possibility of a collision. This paper describes the daily operations of the MRO navigation team during this time as well as the collision avoidance strategy development and implementation.
This study develops evaluation criteria for systems and technologies against the Cooperative Conflict Avoidance (CCA) requirements for unmanned flight at and above FL430 as part of Step 1 of the Access-5 program. These evaluation criteria are then applied to both current and future technologies to identify those which might be used to provide an Equivalent Level of Safety (ELOS) for CCA. This document provides the results of this analysis of various systems and technologies intended for evaluation as part of the CCA work package.
This document describes a method to demonstrate that a UAS, operating in the NAS, can avoid collisions with an equivalent level of safety compared to a manned aircraft. The method is based on the calculation of a collision probability for a UAS , the calculation of a collision probability for a base line manned aircraft, and the calculation of a risk ratio given by: Risk Ratio = P(collision_UAS)/P(collision_manned). A UAS will achieve an equivalent level of safety for collision risk if the Risk Ratio is less than or equal to one. Calculation of the probability of collision for UAS and manned aircraft is accomplished through event/fault trees.
An initial Collision Avoidance for Airport Traffic (CAAT) concept for the Terminal Maneuvering Area (TMA) was evaluated in a simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. CAAT is being designed to enhance surface situation awareness and provide cockpit alerts of potential conflicts during runway, taxi, and low altitude air-to-air operations. The purpose of the study was to evaluate the initial concept for an aircraft-based method of conflict detection and resolution (CD&R) in the TMA focusing on conflict detection algorithms and alerting display concepts. This paper gives an overview of the CD&R concept, simulation study, and test results.
NASA has successfully used debris avoidance maneuvers to protect our spacecraft for more than 20 . years. This process which started out using parametric data and maneuver boxes has seen considerable evolution and now allows us to continue nominal operations for all but the most threatening objects. This has greatly reduced the interruptions to the critical mission objectives being pursued by NASA s Space Station, Space Shuttle, and robotic satellites.
When facing a conjunction between space objects, decision makers must chose whether to maneuver for collision avoidance or not. We apply a well-known decision procedure, the sequential probability ratio test, to this problem. We propose two approaches to the problem solution, one based on a frequentist method, and the other on a Bayesian method. The frequentist method does not require any prior knowledge concerning the conjunction, while the Bayesian method assumes knowledge of prior probability densities. Our results show that both methods achieve desired missed detection rates, but the frequentist method's false alarm performance is inferior to the Bayesian method's
This paper describes some of the environmental challenges associated with landing a crewed or robotic vehicle at any certified location on the lunar surface (i.e. not a mountain peak, permanently dark crater floor or overly steep terrain), with a specific focus on how hazard detection technology may be incorporated to mitigate these challenges. For this discussion, the vehicle of interest is the Altair Lunar Lander, being the vehicle element of the NASA Constellation Program aimed at returning humans to the moon. Lunar environmental challenges for such global lunar access primarily involve terrain and lighting. These would include sizable rocks and slopes, which are more concentrated in highland areas; small craters, which are essentially everywhere independent of terrain type; and for polar regions, low-angle sunlight, which leaves significant terrain in shadow. To address these issues, as well as to provide for precision landing, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) Project was charted by NASA Headquarters, and has since been making significant progress. The ALHAT team considered several sensors for real-time hazard detection, settling on the use of a Flash Lidar mounted to a high-speed gimbal, with computationally intense image processing and elevation interpretation software. The Altair Project has been working with the ALHAT team to understand the capabilities and limitations of their concept, and has incorporated much of the ALHAT hazard detection system into the Altair baseline design. This integration, along with open issues relating to computational performance, the need for system redundancy, and potential pilot interaction, will be explored further in this paper.
A Collision Avoidance for Airport Traffic (CAAT) concept for the airport Terminal Maneuvering Area (TMA) was evaluated in a simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. CAAT is being designed to enhance surface situation awareness and provide cockpit alerts of potential conflicts during runway, taxi, and low altitude air-to-air operations. The purpose of the study was to evaluate pilot reaction to conflict events in the TMA near the airport, different alert timings for various scenarios, alerting display concepts, and directive alerting concepts. This paper gives an overview of the conflict detection and resolution (CD&R) concept, simulation study, and test results
Creating and implementing a process for the mitigation of the impact hazards due to cornets and asteroids will prove to be a complex and involved process. The closest similar program is the collision avoidance process currently used for protection of the International Space Station (ISS). This process, in operation for over three years, has many similarities to the NEG risk problem. By reviewing the ISS program, a broader perspective on the complications of and requirements for a NEO risk mitigation program might be obtained. Specifically, any lessons learned and continuing issues of concern might prove useful in the development of a NEO risk assessment and mitigation program.
Automatic Ground Collision Avoidance Systems (Auto-GCAS) utilizes Digital Terrain Elevation Data (DTED) stored onboard a plane to determine potential recovery maneuvers. Because of the current limitations of computer hardware on military airplanes such as the F-22 and F-35, the DTED must be compressed through a lossy technique called binary-tree tip-tilt. The purpose of this study is to determine the accuracy of the compressed data with respect to the original DTED. This study is mainly interested in the magnitude of the error between the two as well as the overall distribution of the errors throughout the DTED. By understanding how the errors of the compression technique are affected by various factors (topography, density of sampling points, sub-sampling techniques, etc.), modifications can be made to the compression technique resulting in better accuracy. This, in turn, would minimize unnecessary activation of A-GCAS during flight as well as maximizing its contribution to fighter safety.
NASA Langley Research Center (LaRC) and The MITRE Corporation (MITRE) have developed, and successfully demonstrated, an integrated simulation-to-flight capability for evaluating sense and avoid (SAA) system elements. This integrated capability consists of a MITRE developed fast-time computer simulation for evaluating SAA algorithms, and a NASA LaRC surrogate unmanned aircraft system (UAS) equipped to support hardware and software in-the-loop evaluation of SAA system elements (e.g., algorithms, sensors, architecture, communications, autonomous systems), concepts, and procedures. The fast-time computer simulation subjects algorithms to simulated flight encounters/ conditions and generates a fitness report that records strengths, weaknesses, and overall performance. Reviewed algorithms (and their fitness report) are then transferred to NASA LaRC where additional (joint) airworthiness evaluations are performed on the candidate SAA system-element configurations, concepts, and/or procedures of interest; software and hardware components are integrated into the Surrogate UAS research systems; and flight safety and mission planning activities are completed. Onboard the Surrogate UAS, candidate SAA system element configurations, concepts, and/or procedures are subjected to flight evaluations and in-flight performance is monitored. The Surrogate UAS, which can be controlled remotely via generic Ground Station uplink or automatically via onboard systems, operates with a NASA Safety Pilot/Pilot in Command onboard to permit safe operations in mixed airspace with manned aircraft. An end-to-end demonstration of a typical application of the capability was performed in non-exclusionary airspace in October 2011; additional research, development, flight testing, and evaluation efforts using this integrated capability are planned throughout fiscal year 2012 and 2013.
A document discusses sequential probability ratio tests that explicitly allow decision-makers to incorporate false alarm and missed detection risks, and are potentially less sensitive to modeling errors than a procedure that relies solely on a probability of collision threshold. Recent work on constrained Kalman filtering has suggested an approach to formulating such a test for collision avoidance maneuver decisions: a filter bank with two norm-inequality-constrained epoch-state extended Kalman filters. One filter models the null hypotheses that the miss distance is inside the combined hard body radius at the predicted time of closest approach, and one filter models the alternative hypothesis. The epoch-state filter developed for this method explicitly accounts for any process noise present in the system. The method appears to work well using a realistic example based on an upcoming, highly elliptical orbit formation flying mission.
Lidar technology will play an important role in enabling highly ambitious missions being envisioned for exploration of solar system bodies. Currently, NASA is developing a set of advanced lidar sensors, under the Autonomous Landing and Hazard Avoidance (ALHAT) project, aimed at safe landing of robotic and manned vehicles at designated sites with a high degree of precision. These lidar sensors are an Imaging Flash Lidar capable of generating high resolution three-dimensional elevation maps of the terrain, a Doppler Lidar for providing precision vehicle velocity and altitude, and a Laser Altimeter for measuring distance to the ground and ground contours from high altitudes. The capabilities of these lidar sensors have been demonstrated through four helicopter and one fixed-wing aircraft flight test campaigns conducted from 2008 through 2012 during different phases of their development. Recently, prototype versions of these landing lidars have been completed for integration into a rocket-powered terrestrial free-flyer vehicle (Morpheus) being built by NASA Johnson Space Center. Operating in closed-loop with other ALHAT avionics, the viability of the lidars for future landing missions will be demonstrated. This paper describes the ALHAT lidar sensors and assesses their capabilities and impacts on future landing missions.