A gyrocompassing spacecraft navigator.
Spacecraft navigation near planet by onboard determination of conic orbit parameters with gyrocompass for measuring orbital angular velocity
Mcdonald, W. T.↗
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ARTSN: Prototype for an Automated Real-Time Spacecraft Navigation System
The Automated Real-Time Spacecraft Navigation system (ARTSN) is a prototype of a new class of software for automated spacecraft navigation and monitoring.
Automated↗
ARTSN: An Automated Real-Time Spacecraft Navigation System
ARTSN, the Automated Real-Time Spacecraft Navigation system is a real time system for the automated navigation of interplanetary spacecraft. The system processes the real time DSN radio metric data flow and generates updated spacecraft solutions and the associated covariance. ARTSN is designed modularly with the user interface input and output separated from the data analysis modules. Designed for distributed application, the system provided, for the first time, an automated method of processing radio metric navigation data for interplanetary spacecraft.
ARTSN↗
Autonomous landmark based spacecraft navigation system
An autonomous landmark based spacecraft navigation scheme is presented. This new schme involves the following data processing steps: image selection and planning; landmark detection; preliminary image matching; crater matching; database management; and finally landmark based orbit determination.
autonomous↗
Processing Images of Craters for Spacecraft Navigation
A crater-detection algorithm has been conceived to enable automation of what, heretofore, have been manual processes for utilizing images of craters on a celestial body as landmarks for navigating a spacecraft flying near or landing on that body. The images are acquired by an electronic camera aboard the spacecraft, then digitized, then processed by the algorithm, which consists mainly of the following steps: 1. Edges in an image detected and placed in a database. 2. Crater rim edges are selected from the edge database. 3. Edges that belong to the same crater are grouped together. 4. An ellipse is fitted to each group of crater edges. 5. Ellipses are refined directly in the image domain to reduce errors introduced in the detection of edges and fitting of ellipses. 6. The quality of each detected crater is evaluated. It is planned to utilize this algorithm as the basis of a computer program for automated, real-time, onboard processing of crater-image data. Experimental studies have led to the conclusion that this algorithm is capable of a detection rate >93 percent, a false-alarm rate <5 percent, a geometric error <0.5 pixel, and a position error <0.3 pixel.
Cheng, Yang↗
Altimeter Range Processing Analysis for Spacecraft Navigation about Small Bodies
The impact of using altimeter range measurements as an observation type for navigation of spacecraft about small bodies is evaluated.
altimetry↗
Reinforcement Learning for Spacecraft Navigation & Environment Characterization in the Planar-Restricted Two-Body Problem
As science, exploration, and commercial space missions become increasingly complex, so does the need for efficient, autonomous, and integrated spacecraft navigation and operations techniques. Key operational functions, including data collection and transmission, environment characterization, systems constraints, human factors, and navigation, often are intertwined and conflicted. Deep Reinforcement Learning (DRL) offers a framework for addressing integrated spacecraft navigation and planning in an uncertain dynamical environment. The goal of this study is to evaluate the utility of DRL for integrated spacecraft navigation and planning. This is achieved by developing a simple environmental characterization training environment in the Planar-Restricted 2-Body Problem (PR2BP), establishing benchmarks and heuristic baselines, and designing a previously unstudied Markov Decision Process (MDP) formulation. This MDP formulation enables the spacecraft DRL agents to appropriately balance navigation and actuation capabilities. The resulting DRL-derived policy exceeds a random or untrained policy and meets or exceeds the level of performance of a heuristic without actuation. In the process, valuable intuition is gained about the problem with insight into how DRL methods could scale to increasingly more realistic scenarios, including net-work design and training architectures, efficient state space representations, and methods for encouraging exploration in a parametric action space, among others.
navigation↗
Autonomous Spacecraft Navigation Using Above-the-Constellation GPS Signals
GPS-based spacecraft navigation offers many performance and cost benefits, and GPS receivers are now standard GNC components for LEO missions. Recently, more and more high-altitude missions are taking advantage of the benefits of GPS navigation as well. High-altitude applications pose challenges, however, because receivers operating above the GPS constellations are subject to reduced signal strength and availability, and uncertain signal quality. This presentation will present the history and state-of-the-art in high-altitude GPS spacecraft navigation, including early experiments, current missions and receivers, and efforts to characterize and protect signals available to high-altitude users. Recent results from the very-high altitude MMS mission are also provided.
High Altitude↗
Method and System for Gamma-Ray Localization Induced Spacecraft Navigation Using Celestial Gamma-Ray Sources
A method and system for spacecraft navigation using distant celestial gamma-ray bursts which offer detectable, bright, high-energy events that provide well-defined characteristics conducive to accurate time-alignment among spatially separated spacecraft. Utilizing assemblages of photons from distant gamma-ray bursts, relative range between two spacecraft can be accurately computed along the direction to each burst's source based upon the difference in arrival time of the burst emission at each spacecraft's location. Correlation methods used to time-align the high-energy burst profiles are provided. The spacecraft navigation may be carried out autonomously or in a central control mode of operation.
Sheikh, Suneel I.↗
Software Searches for Better Spacecraft-Navigation Models
ADAPT is a computer program that searches for better mathematical models for spacecraft navigation. The task of tuning trajectory-determination models for interplanetary navigation is complex, requiring an intensive search of multiple dynamical and nondynamical models that yield trajectory solutions with minimal errors. By automating the search, ADAPT eases the task of human analysts and enables them to consider wider ranges of potential solutions. ADAPT uses genetic algorithms to search a range of relevant parameters in a user-selected design space to arrive at values for those parameters that best fit the measured spacecraft-tracking data. The user s guide for ADAPT reviews the theoretical basis of the program and presents two example applications. One example is that of selecting a solar-radiation model for the Mars Pathfinder (MPF) mission using MPF tracking data and an extended Kalman filter from prior spacecraft-navigation software. The second example is of the use of tracking data from the Stardust spacecraft mission combined with a pseudo-epoch-state batch filter and an empirical small-forces model to find improved impulse models for use during Stardust attitude adjustments.
Ely, Todd↗
Technical Characteristics and Accuracy Capabilities of Delta Differential One-Way Ranging (DeltaDOR) as a Spacecraft Navigation Tool
The technique of determining spacecraft angular position by Delta Differential One-Way Ranging (DeltaDOR) is described. The dependence of measurement accuracy on parameters which define the spacecraft signal spectrum is shown. An illustration of DeltaDOR measurement accuracy, using the Mars Observer spacecraft, is presented. Guidelines for specifying spacecraft tone spectra are presented based on typical accuracy and ambiguity resolution needs, on frequency allocation for deep space tracking, on the efficient use of spacecraft signal power, and on the efficient use of ground tracking resources.
VLBI Very Long Baseline Interferometry DOR tones D↗
ARTSN: An Automated Real-Time Spacecraft Navigation System
As part of the Deep Space Network (DSN) advanced technology program an effort is underway to design a filter to automate the deep space navigation process.The automated real-time spacecraft navigation (ARTSN) filter task is based on a prototype consisting of a FORTRAN77 package operating on an HP-9000/700 workstation running HP-UX 9.05. This will be converted to C, and maintained as the operational version. The processing tasks required are: (1) read a measurement, (2) integrate the spacecraft state to the current measurement time, (3) compute the observable based on the integrated state, and (4) incorporate the measurement information into the state using an extended Kalman filter. This filter processes radiometric data collected by the DSN. The dynamic (force) models currently include point mass gravitational terms for all planets, the Sun and Moon, solar radiation pressure, finite maneuvers, and attitude maintenance activity modeled quadratically. In addition, observable errors due to troposphere are included. Further data types, force and observable models will be ncluded to enhance the accuracy of the models and the capability of the package. The heart of the ARSTSN is a currently available continuous-discrete extended Kalman filter. Simulated data used to test the implementation at various stages of development and the results from processing actual mission data are presented.
Burkhart, P. Daniel↗
Manned spacecraft navigation guidance and control
Technological problem areas in developing manned spacecraft navigation guidance and control systems
Creer, B. Y.↗
Determining, Combining, and Predicting Earth Orientation Parameters for Spacecraft Navigation
A description is given of the operational JPL project to measure, combine, and predict Earth rotation parameters in support of spacecraft navigation.
Observations TEMPO Deep Space Network DSN↗
Machine Vision for Relative Spacecraft Navigation During Approach to Docking
This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.
Chien, Chiun-Hong↗
Use of Very Long Baseline Array Interferometric Data for Spacecraft Navigation
The main VLBI technique that is used at JPL is known as the Delta Differential One-way Ranging ((Delta)DOR). Two DSN antennas simultaneously track a source, and alternate between sources. The signals recorded at the antennas from each source are correlated to obtain the delay in arrival to the two antennas, and the delays are differenced to remove common-source errors. An alternative technique is to use carrier phase differences between antennas. This is routinely done by the Very Large Baseline Array (VLBA) as part of source imaging. The VLBA capabilities are used for scientific research, but also have the potential to be used for navigation. Two main experiments were performed with the VLBA and JPL spacecraft. This paper describes and analyzes these experiments and discusses the possible uses of VLBA tracking for spacecraft navigation.
Very Large Baseline Array (VLBA)↗
Spacecraft navigation at Mars using earth-based and in situ radio tracking techniques
A survey of earth-based and in situ radiometric data types and results from a number of studies investigating potential radio navigation performance for spacecraft approaching/orbiting Mars and for landed spacecraft and rovers on the surface of Mars are presented. The performance of Doppler, ranging and interferometry earth-based data types involving single or multiple spacecraft is addressed. This evaluation is conducted with that of in situ data types, such as Doppler and ranging measurements between two spacecraft near Mars, or between a spacecraft and one or more surface radio beacons.
Thurman, S. W.↗
Navigation Operations with Prototype Components of an Automated Real-Time Spacecraft Navigation System
At present, ground navigation support for interplanetary spacecraft requires human intervention for data pre-processing, filtering, and post-processing activities; these actions must be repeated each time a new batch of data is collected by the ground data system.
Automation Deep Space Navigation Mission Operation↗