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Anzalone, Evan

Publications and source records attributed to Anzalone, Evan.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Guidance and Navigation Challenges for a Mars Ascent Vehicle

This work presents studies and analysis in support of a Mars Ascent Vehicle as part of a Martian Sample Return campaign. The vehicle design has been ongoing, with rapid development of a 6 Degree of Freedom simulation to capture full vehicle dispersions and integrated performance of vehicle, guidance, navigation and control. The maturation of this simulation is presented to provide an overview of its capabilities added over the past year of effort. The results describe in detail guidance algorithm development to increase the system’s robustness to thrust sensitivities. Navigation performance and sensitivity analysis are included to describe the capabilities of the current design as well as identify primary drivers of insertion performance. Lastly, integrated vehicle 6DOF statistical results are presented to provide insight into the nominal performance of the current vehicle and insight into system-level drivers. Future work is described to outline the continuing maturation and development of the MSR MAV ascent vehicle.

Anzalone, Evan↗
NASA NTRS2020

Use of Navigation Beacons to Support Lunar Vehicle Operations

To support a wide variety of lunar missions in a condensed regime, solutions are needed outside of the use of Earth-based orbit determination. This research presents an alternate approach to in-situ navigation through the use of beacons, similar to that used on Earth as well as under technology development efforts. An overview of the current state of navigation aids included as well as discussion of the Lunar Node – 1 payload being built at NASA/Marshall Space Flight Center. Expected navigation results of this beacon payload for planned operation from the lunar surface are provided. Applications of navigation beacons to multiple stages of the proposed human lunar landing architecture are given, with initial analysis showing performance gains from the use of this technology. This work provides a starting point for continued analysis and design, laying out the foundation of how navigation beacons can be incorporated into the architecture to enable continued analysis, design, and future expanded capability.

Lunar node-1↗
NASA NTRS2019

Guidance and Navigation for a Martian Sample Return Ascent Vehicle

Overview: Mission Design and Concept of Operations; Vehicle Concept and System Requirements; Guidance and Navigation Architecture; Simulation Architecture; Guidance Algorithm Development; Navigation System Design; Integrated Vehicle Performance; Continuing Analysis and Trades; Conclusions.

Anzalone, Evan↗
NASA NTRS2019

Efficient On-Orbit Singularity-Free Geopotential Estimation

For vehicles in orbital cruise, either in orbit around a body or in a transfer orbit, gravity is the primary external force; therefore, the complexity of the geopotential model heavily influences the accuracy of the navigation state. As this type of spacecraft requires a highly accurate geopotential model and performs the computation numerous times a second, this calculation needs to be efficient. This calculation needs to include the first and second derivatives of the geopotential because navigation systems can require both the gravitational acceleration and gradient for inertial integration and state filtering. The most efficient method for calculating the geopotential, the forward column method, is discussed in detail, as well as a method to avoid the singularities that exist when using this method. This is shown to decrease the computation time of the geopotential compared to other popular methods. In addition, methods for first and second order propagation are discussed, which decrease the rate at which the full geopotential model needs to be calculated while maintaining the accuracy required of navigation systems. These estimation methods are shown to decrease the necessary computation of the gravity model by multiple orders of magnitude. This method decreases the computation time of the Exploration Upper Stage navigation system geopotential model by potentially an order of magnitude compared with the previous model without affecting the navigation error. A properly implemented geopotential model can have the accuracy of an 8 by 8 model while approaching the computational requirement as using only the J234 coefficients.

Amert, Joel↗
NASA NTRS2019

Guidance, Navigation, and Control for NASA Lunar Pallet Lander

The NASA Lander Technology project is leading the development and integration of the Lunar Pallet Lander (LPL) concept. The objective is to demonstrate precision landing by delivering a payload to the lunar surface within 100 meters of a landing target. Potential landing sites are selected near the lunar pole where water may be present in permanently shadowed regions that could enable future in-situ resource utilization. The LPL is part of a sequence of missions aimed at maturing the necessary technologies, such as lunar precision landing sensors, that will enable the next generation of multi-ton lunar payloads and human landers. This paper provides an overview of the Mission Design, Guidance Navigation and Control (GNC) algorithms, and sensor suite. The results show the LPL simulated trajectory and landing precision performance under nominal and dispersed conditions. The landing precision simulation confirms the need to rely on high-accuracy navigation techniques and sensors such as Terrain Relative Navigation (TRN) and the Navigation Doppler Lidar (NDL), currently being developed for space applications. The results also demonstrate the ability of the guidance and control system to perform a soft lunar touchdown by combining thrust vector control during the solid rocket motor deceleration phase, and pulse engine control, for the liquid powered descent phase.

Orphee, Juan↗
NASA NTRS2019

Guidance and Navigation Design for a Martian Sample Return Ascent Vehicle

This paper focuses on the work being performed at the NASA Marshall Space Flight Center (MSFC) in support of Mars Ascent Vehicles (MAVs). Specifically, the analysis presented is in support of Martian sample return architectures. In or-der to assess vehicle sensitivities, a detailed simulation tool, (MAV Analysis Tool in Simscape) MANTIS, was implemented using the MATLAB/Simulink Sim-scape architecture. High fidelity navigation sensor models and guidance algorithms were included in order to facilitate sensor requirement development and flight algorithm selection. This work focuses on the performance of the integrated system and the coupling of navigation and guidance capabilities. The architecture trades are heavily dependent on the ascent flight profile chosen. This work assesses both open- and closed-loop guidance algorithms to capture their relative performance and the resulting requirements on sensor capability to support preliminary vehicle design. The analysis builds on previous work that focused on navigation performance for initialization and ascent flight of crewed vehicle. The results provide insight into the coupling between sensor requirements and ascent guidance approach. The analysis provides data to support requirements for hard-ware selection and testing. Additional discussion is also included focusing on other system constraints that affect hardware selection and operational constraints.

Anzalone, Evan↗
NASA NTRS2018

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. To accommodate this with regards to Navigation, the SLS utilizes an internally redundant Inertial Navigation System (INS) with built-in capability to detect, isolate, and recover from first failure conditions and still maintain adherence to performance requirements. The unit utilizes multiple hardware- and software-level techniques to enable detection, isolation, and recovery from these events in terms of its built-in Fault Detection, Isolation, and Recovery (FDIR) algorithms. Successful operation is defined in terms of sufficient navigation accuracy at insertion while operating under worst case single sensor outages (gyroscope and accelerometer faults at launch). In addition to first fault detection and recovery, the SLS program has also levied requirements relating to the capability of the INS to detect a second fault, tracking any unacceptable uncertainty in knowledge of the vehicle's state. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error and sensor faults can drive the vehicle outside of its operational as-designed environments and outside of its performance envelope causing loss of mission, or worse, loss of crew. The criteria for operation under second faults allows for a larger set of achievable missions in terms of potential fault conditions, due to the INS operating at the edge of its capability. As this performance is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design space. Due to the implications of the vehicle response to abort conditions (such as a potentially failed INS), it is important to consider a wide range of failure scenarios in terms of both magnitude and time. As such, the Navigation team is taking advantage of the INS's capability to schedule and change fault detection thresholds in flight. These values are optimized along a nominal trajectory in order to maximize probability of mission success, and reducing the probability of false positives (defined as when the INS would report a second fault condition resulting in loss of mission, but the vehicle would still meet insertion requirements within system-level margins). This paper will describe an optimization approach using Genetic Algorithms to tune the threshold parameters to maximize vehicle resilience to second fault events as a function of potential fault magnitude and time of fault over an ascent mission profile. The analysis approach, and performance assessment of the results will be presented to demonstrate the applicability of this process to second fault detection to maximize mission probability of success.

Anzalone, Evan↗
NASA NTRS2018

SLS Block 1-B and Exploration Upper Stage Navigation System Design

The SLS Block 1B vehicle is planned to extend NASA's heavy lift capability beyond the initial SLS Block 1 vehicle. The most noticeable change for this vehicle from SLS Block 1 is the swapping of the upper stage from the Interim Cryogenic Propulsion stage (ICPS), a modified Delta IV upper stage, to the more capable Exploration Upper Stage (EUS). As the vehicle evolves to provide greater lift capability and execute more demanding missions so must the SLS Integrated Navigation System to support those missions. The SLS Block 1 vehicle carries two independent navigation systems. The responsibility of the two systems is delineated between ascent and upper stage flight. The Block 1 navigation system is responsible for the phase of flight between the launch pad and insertion into Low-Earth Orbit (LEO). The upper stage system assumes the mission from LEO to payload separation. For the Block 1B vehicle, the two functions are combined into a single system intended to navigate from ground to payload insertion. Both are responsible for self-disposal once payload delivery is achieved. The evolution of the navigation hardware and algorithms from an inertial-only navigation system for Block 1 ascent flight to a tightly coupled GPS-aided inertial navigation system for Block 1-B is described. The Block 1 GN&C system has been designed to meet a LEO insertion target with a specified accuracy. The Block 1-B vehicle navigation system is designed to support the Block 1 LEO target accuracy as well as trans-lunar or trans-planetary injection accuracy. This is measured in terms of payload impact and stage disposal requirements. Additionally, the Block 1-B vehicle is designed to support human exploration and thus is designed to minimize the probability of Loss of Crew (LOC) through high-quality inertial instruments and Fault Detection, Isolation, and Recovery (FDIR) logic. The preliminary Block 1B integrated navigation system design is presented along with the challenges associated with meeting the design objectives. This paper also addresses the design considerations associated with the use of Block 1 and Commercial Off-the-Shelf (COTS) avionics for Block 1-B/EUS as part of an integrated vehicle suite for orbital operations.

Oliver, T. Emerson↗
NASA NTRS2018

SLS Navigation Model-Based Design Approach

The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and management of design requirements to the development of usable models, model requirements, and model verification and validation efforts. The models themselves are represented in C/C++ code and accompanying data files. Under the idealized process, potential ambiguity in specification is reduced because the model must be implementable versus a requirement which is not necessarily subject to this constraint. Further, the models are shown to emulate the hardware during validation. For models developed by the Navigation Team, a common interface/standalone environment was developed. The common environment allows for easy implementation in design and analysis tools. Mechanisms such as unit test cases ensure implementation as the developer intended. The model verification and validation process provides a very high level of component design insight. The origin and implementation of the SLS variant of Model-based Design is described from the perspective of the SLS Navigation Team. The format of the models and the requirements are described. The Model-based Design approach has many benefits but is not without potential complications. Key lessons learned associated with the implementation of the Model Based Design approach and process from infancy to verification and certification are discussed

Oliver, T. Emerson↗
NASA NTRS2018

Space Launch Systems Block 1B Preliminary Navigation System Design

NASA is currently building the Space Launch Systems (SLS) Block 1 launch vehicle for the Exploration Mission 1 (EM-1) test flight. In parallel, NASA is also designing the Block 1B launch vehicle. The Block 1B vehicle is an evolution of the Block 1 vehicle and extends the capability of the NASA launch vehicle. This evolution replaces the Interim Cryogenic Propulsive Stage (ICPS) with the Exploration Upper Stage (EUS). As the vehicle evolves to provide greater lift capability, increased robustness for manned missions, and the capability to execute more demanding missions so must the SLS Integrated Navigation System evolved to support those missions. This paper describes the preliminary navigation systems design for the SLS Block 1B vehicle. The evolution of the navigation hard-ware and algorithms from an inertial-only navigation system for Block 1 ascent flight to a tightly coupled GPS-aided inertial navigation system for Block 1B is described. The Block 1 GN&C system has been designed to meet a LEO insertion target with a specified accuracy. The Block 1B vehicle navigation system is de-signed to support the Block 1 LEO target accuracy as well as trans-lunar or trans-planetary injection accuracy. Additionally, the Block 1B vehicle is designed to support human exploration and thus is designed to minimize the probability of Loss of Crew (LOC) through high-quality inertial instruments and robust algorithm design, including Fault Detection, Isolation, and Recovery (FDIR) logic.

Oliver, T. Emerson↗
NASA NTRS2018

SLS Model Based Design: A Navigation Perspective

The SLS Program has implemented a Model-based Design (MBD) and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team is responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1B design, the additional GPS Receiver hardware model is managed as a DMM at the vehicle design level. This paper describes the models, and discusses the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the navigation components.

Oliver, T. Emerson↗