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At least 19 records

New Algorithms for Estimating Spacecraft Position Using Scanning Techniques for Deep Space Network Antennas

As more and more nonlinear estimation techniques become available, our interest is in finding out what performance improvement, if any, they can provide for practical nonlinear problems that have been traditionally solved using linear methods. In this paper we examine the problem of estimating spacecraft position using conical scan (conscan) for NASA's Deep Space Network antennas. We show that for additive disturbances on antenna power measurement, the problem can be transformed into a linear one, and we present a general solution to this problem, with the least square solution reported in literature as a special case. We also show that for additive disturbances on antenna position, the problem is a truly nonlinear one, and we present two approximate solutions based on linearization and Unscented Transformation respectively, and one 'exact' solution based on Markov Chain Monte Carlo (MCMC) method. Simulations show that, with the amount of data collected in practice, linear methods perform almost the same as MCMC methods. It is only when we artificially reduce the amount of collected data and increase the level of noise that nonlinear methods show significantly better accuracy than that achieved by linear methods, at the expense of more computation.

Metropolis-Hastings (MH)

Estimating Accurate Relative Spacecraft Angular Position from DSN VLBI Phases Using X-Band Telemetry or DOR Tones

At present spacecraft angular position with Deep Space Network (DSN) is determined using group delay estimates from very long baseline interferometer (VLBI) phase measurements employing differential one way ranging (DOR) tones. As an alternative to this approach, we propose estimating position of a spacecraft to half a fringe cycle accuracy using time variations between measured and calculated phases as the Earth rotates using DSN VLBI baseline(s). Combining fringe location of the target with the phase allows high accuracy for spacecraft angular position estimate. This can be achieved using telemetry signals of at least 4-8 MSamples/sec data rate or DOR tones.

x-band telemetry

Gravity field of Venus - A preliminary analysis

The gravitational field of Venus obtained by tracking the Pioneer Venus Orbiter is examined. For each spacecraft orbit, two hours of Doppler data centered around periapsis were used to estimate spacecraft position and velocity and the velocity residuals obtained were spline fit and differentiated to produce line of sight gravitational accelerations. Consistent variations in line of sight accelerations from orbit to orbit reveal the presence of gravitational anomalies. A simulation of isostatic compensation for an elevated region on the surface of Venus indicates that the mean depth of compensation is no greater than about 100 km. Gravitational spectra obtained from a Fourier analysis of line of sight accelerations from selected Venus orbits are compared to the earth's gravitational spectrum and spherical harmonic gravitational potential power spectra of the earth, the moon and Mars. The Venus power spectrum is found to be remarkably similar to that of the earth, however systematic variations in the harmonics suggest differences in dynamic processes or lithospheric behavior.

Phillips, R. J.

Orbit determination and orbit control for the Earth Observing System (EOS) AM spacecraft

Future NASA Earth Observing System (EOS) Spacecraft will make measurements of the earth's clouds, oceans, atmosphere, land and radiation balance. These EOS Spacecraft will be part of the NASA Mission to Planet Earth. This paper specifically addresses the EOS AM Spacecraft, referred to as 'AM' because it has a sun-synchronous orbit with a 10:30 AM descending node. This paper describes the EOS AM Spacecraft mission orbit requirements, orbit determination, orbit control, and navigation system impact on earth based pointing. The EOS AM Spacecraft will be the first spacecraft to use the TDRSS Onboard Navigation System (TONS) as the primary means of navigation. TONS flight software will process one-way forward Doppler measurements taken during scheduled TDRSS contacts. An extended Kalman filter will estimate spacecraft position, velocity, drag coefficient correction, and ultrastable master oscillator frequency bias and drift. The TONS baseline algorithms, software, and hardware implementation are described in this paper. TONS integration into the EOS AM Spacecraft Guidance, Navigation, and Control (GN&C) System; TONS assisted onboard time maintenance; and the TONS Ground Support System (TGSS) are also addressed.

Herberg, Joseph R.

Building Lunar Maps for Terrain Relative Navigation and Hazard Detection Applications

Terrain Relative Navigation (TRN) systems localize a spacecraft with respect to a map of the surface by comparing descent imagery to that reference map. The spacecraft position estimates can only be as accurate as the reference map itself. Accurate map products that are based on orbital reconnaissance data must be validated for navigation applications to ensure that all relevant error sources are minimized. Currently available map products have been generated for scientific applications, so the need for accurate TRN maps remains a gap to be filled for upcoming lunar lander missions, in particular missions to the South Pole region. Additionally, representative high-resolution maps that contain lander-scale features are needed for successful development and testing of Hazard Detection (HD) systems. This paper describes one of NASA’s current efforts to develop benchmark data sets that can be used for developing and testing TRN and HD algorithms as well as suggested processes and metrics for generating and validating lunar maps that can be used for navigation and hazard detection.

Lunar Maps

X-Ray Detection and Processing Models for Spacecraft Navigation and Timing

The current primary method of deepspace navigation is the NASA Deep Space Network (DSN). High-performance navigation is achieved using Delta Differential One-Way Range techniques that utilize simultaneous observations from multiple DSN sites, and incorporate observations of quasars near the line-of-sight to a spacecraft in order to improve the range and angle measurement accuracies. Over the past four decades, x-ray astronomers have identified a number of xray pulsars with pulsed emissions having stabilities comparable to atomic clocks. The x-ray pulsar-based navigation and time determination (XNAV) system uses phase measurements from these sources to establish autonomously the position of the detector, and thus the spacecraft, relative to a known reference frame, much as the Global Positioning System (GPS) uses phase measurements from radio signals from several satellites to establish the position of the user relative to an Earth-centered fixed frame of reference. While a GPS receiver uses an antenna to detect the radio signals, XNAV uses a detector array to capture the individual xray photons from the x-ray pulsars. The navigation solution relies on detailed xray source models, signal processing, navigation and timing algorithms, and analytical tools that form the basis of an autonomous XNAV system. Through previous XNAV development efforts, some techniques have been established to utilize a pulsar pulse time-of-arrival (TOA) measurement to correct a position estimate. One well-studied approach, based upon Kalman filter methods, optimally adjusts a dynamic orbit propagation solution based upon the offset in measured and predicted pulse TOA. In this delta position estimator scheme, previously estimated values of spacecraft position and velocity are utilized from an onboard orbit propagator. Using these estimated values, the detected arrival times at the spacecraft of pulses from a pulsar are compared to the predicted arrival times defined by the pulsar s pulse timing model. A discrepancy provides an estimate of the spacecraft position offset, since an error in position will relate to the measured time offset of a pulse along the line of sight to the pulsar. XNAV researchers have been developing additional enhanced approaches to process the photon TOAs to arrive at an estimate of spacecraft position, including those using maximum-likelihood estimation, digital phase locked loops, and "single photon processing" schemes that utilize all available time data associated with each photon. Using pulsars from separate, non-coplanar locations provides range and range-rate measurements in each pulsar s direction. Combining these different pulsar measurements solves for offsets in position and velocity in three dimensions, and provides accurate overall navigation for deep space vehicles.

Sheikh, Suneel

Fast Kalman Filtering for Relative Spacecraft Position and Attitude Estimation for the Raven ISS Hosted Payload

The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors.

estimation

Fast Kalman Filtering for Relative Spacecraft Position and Attitude Estimation for the Raven ISS Hosted Payload

The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors

estimation

Inertial attitude control of Voyager spacecraft using dry tuned rotor gyro

The inertial attitude control system designed for the Voyager spacecraft, which will carry out flybys of Jupiter and Saturn in 1979 and 1981, respectively, is described. The attitude of the spacecraft in three-dimensional space will be measured by a Dry Inertial Reference Unit (DIRU) based on three identical two-degree-of-freedom dry gyros. A software estimation process has been developed to use DIRU data and other information to obtain optimum estimates of spacecraft position, velocity, and acceleration. The attitude of the spacecraft is corrected using these estimates by activating hydrazine thrusters. The operation of dry gyros is discussed, together with the network compensation techniques used in their associated capture loop to obtain a capture capability of 8 deg/sec and a frequency response of 10 Hz (3-dB point). The control law and estimation process are examined. Results of computer simulation studies of the performance of the attitude control system are presented.

Bahrami, K.

Autonomous reconfigurable GPS/INS navigation and pointing system for rendezvous and docking

This paper describes the results of an integrated navigation and pointing system software development effort sponsored by the NASA MSFC through a SBIR Phase 2 Program. The integrated Global Positioning System (GPS)/Inertial Navigation System (INS) implements an autonomous navigation filter that is reconfigurable in real-time to accommodate mission contingencies. An onboard expert system monitors the spacecraft status and reconfigures the navigation filter accordingly, to optimize the system performance. The navigation filter is a multi-mode Kalman filter to estimate the spacecraft position, velocity, and attitude. Three different GPS-based attitude determination techniques, namely, velocity vector matching, attitude vector matching, and interferometric processing, are implemented to encompass different mission contingencies. The integrated GPS/INS navigation filter will use any of these techniques depending on the mission phase and the state of the sensors. The first technique, velocity vector matching, uses the GPS velocity measurement to estimate the INS velocity errors and exploits the correlation between INS velocity and attitude errors to estimate the attitude. The second technique, attitude vector matching, uses INS gyro measurements and GPS carrier phase (integrated Doppler) measurements during a spacecraft rotation maneuver to determine the attitude. Both of these techniques require only one GPS antenna onboard to determine the spacecraft attitude. The third technique, interferometric processing, requires use of multiple GPS antennae. In order to determine 3-axis body attitude, three GPS antennae (2 no-coplanor baselines) are required.

Upadhyay, Triveni N.

Tracking and Data Relay Satellite (TDRS) Orbit Estimation Using an Extended Kalman Filter

Alternatives to the Tracking and Data Relay Satellite (TDRS) orbit estimation procedure were studied to develop a technique that both produces more reliable results and is more amenable to automation than the prior procedure. The Earth Observing System (EOS) Terra mission has TDRS ephemeris prediction 3(sigma) requirements of 75 meters in position and 5.5 millimeters per second in velocity over a 1.5-day prediction span. Meeting these requirements sometimes required reruns of the prior orbit determination (OD) process, with manual editing of tracking data to get an acceptable solution. After a study of the available alternatives, the Flight Dynamics Facility (FDF) began using the Real-Time Orbit Determination (RTOD(Registered TradeMark)) Kalman filter program for operational support of TDRSs in February 2007. This extended Kalman filter (EKF) is used for daily support, including within hours after most thrusting, to estimate the spacecraft position, velocity, and solar radiation coefficient of reflectivity (C(sub R)). The tracking data used are from the Bilateration Ranging Transponder System (BRTS), selected TDRS System (TDRSS) User satellite tracking data, and Telemetry, Tracking, and Command (TT&C) data. Degraded filter results right after maneuvers and some momentum unloads provided incentive for a hybrid OD technique. The results of combining EKF strengths with the Goddard Trajectory Determination System (GTDS) Differential Correction (DC) program batch-least-squares solutions, as recommended in a 2005 paper on the chain-bias technique, are also presented.

Ward, Douglas T.

An improved Venus gravity field from Doppler tracking of the Pioneer Venus Orbiter and Magellan spacecraft

A total of 365,000 Pioneer Venus Orbiter (PVO) S-band Doppler data points were fit in arcs ranging from one to four revolutions in length by estimating the spacecraft position and velocity, atmospheric density, and a solar pressure parameter at each arc epoch. The resultant converged PVO orbits were used to produce 194 information arrays for the Venus spherical harmonic coefficients complete to degree and order 21. A similar procedure was used to produce a second set of 72 information arrays for a 21 x 21 gravitational field from a limited, but global, sampling of Magellan S- and X-band data from cycles 1 and 2. The PVO and Magellan information arrays were combined and solved to obtain the 21 x 21 spherical harmonic expansion designated JPL-Venus Gravity Model 6A (VGM6A). The VGM6A harmonic field field produced significant improvements in the Doppler residual statistics obtained from field validation fits to both PVO and Magellan tracking data in comparison with alternative representations of Venus gravity.

Mcnamee, J. B.

Real-time Terrain Relative Navigation Test Results from a Relevant Environment for Mars Landing

Terrain Relative Navigation (TRN) is an on-board GN&C function that generates a position estimate of a spacecraft relative to a map of a planetary surface. When coupled with a divert, the position estimate enables access to more challenging landing sites through pin-point landing or large hazard avoidance. The Lander Vision System (LVS) is a smart sensor system that performs terrain relative navigation by matching descent camera imagery to a map of the landing site and then fusing this with inertial measurements to obtain high rate map relative position, velocity and attitude estimates. A prototype of the LVS was recently tested in a helicopter field test over Mars analog terrain at altitudes representative of Mars Entry Descent and Landing conditions. TRN ran in real-time on the LVS during the flights without human intervention or tuning. The system was able to compute estimates accurate to 40m (3 sigma) in 10 seconds on a flight like processing system. This paper describes the Mars operational test space definition, how the field test was designed to cover that operational envelope, the resulting TRN performance across the envelope and an assessment of test space coverage.

Pin-point Landing

Navigation Concepts for the James Webb Space Telescope

This paper evaluates the performance that can be achieved using candidate ground and onboard navigation approaches for operation of the James Webb Space Telescope, which will be in an orbit about the Sun-Earth L2 libration point. The ground navigation approach processes standard range and Doppler measurements from the Deep Space Network The onboard navigation approach processes celestial object measurements and/or ground-to- spacecraft Doppler measurements to autonomously estimate the spacecraft s position and velocity and Doppler reference frequency. Particular attention is given to assessing the absolute position and velocity accuracy that can be achieved in the presence of the frequent spacecraft reorientations and momentum unloads planned for this mission. The ground navigation approach provides stable navigation solutions using a tracking schedule of one 30-minute contact per day. The onboard navigation approach that uses only optical quality celestial object measurements provides stable autonomous navigation solutions. This study indicates that unmodeled changes in the solar radiation pressure cross-sectional area and modeled momentum unload velocity changes are the major error sources. These errors can be mitigated by modeling these changes, by estimating corrections to compensate for the changes, or by including acceleration measurements.

Long, Anne

Deep space tracking in local reference frames

A self-calibrating deep space tracking technique is described which can potentially produce two nanoradian angular spacecraft determinations. The technique uses very long base interferometric observations of a spacecraft and several radio sources. The currently employed single source technique is described as a parameter estimation procedure. Then, the number of parameters and observations leads to the proposed local reference frame technique. Station clock, Earth rotation, and tropospheric parameters are estimated along with spacecraft position from the multisource observation sequence. The contributions to spacecraft angular uncertainty from system noise, tropospheric fluctuations, and uncalibrated radio source structure are evaluated. Of these experimental errors, radio source structure dominates the determination of the spacecraft position in the radio reference frame. It is shown, however, that the sensitivity of relative spacecraft position accuracies to time-invariant radio source structure effects may be on the order of 2 nanoradians.

Treuhaft, R. N.

A Minimal State Augmentation Algorithm for Vision-Based Navigation without Using Mapped Landmarks

This paper describes MAVeN (Minimal State Augmentation Algorithm for Vision-Based Navigation), which is a new algorithm for vision-based navigation that has only 21 states, yet is able to track features in successive camera images and use them to propagate estimates of the spacecraft position and velocity. The filter dimension drops to 12 if attitude information is already available. The low filter dimension makes MAVeN a very reliable and practical algorithm for real-time flight implementation. The main idea is to project observed features onto a rough shape model of the ground surface, which are then used by the filter as pseudo-landmarks. The shape model is assumed to be known beforehand, as would be obtained from prior surveillance of the landing site from orbit. MAVeN does not require pre-mapped landmarks, so it is able to navigate terrain that has not been previously observed up close. This property is especially important for close proximity operations in small body missions where ground surface features are being seen for the first time at close range. MAVeN is also able to hover motionless above the ground without position error growth, which is unusual for this class of vision-based navigation algorithms.

San Martin, A. Miguel

Magnetospheric Multiscale Mission (MMS) Phase 2B Navigation Performance

The Magnetospheric Multiscale (MMS) formation flying mission, which consists of four spacecraft flying in a tetrahedral formation, has challenging navigation requirements associated with determining and maintaining the relative separations required to meet the science requirements. The baseline navigation concept for MMS is for each spacecraft to independently estimate its position, velocity and clock states using GPS pseudorange data provided by the Goddard Space Flight Center-developed Navigator receiver and maneuver acceleration measurements provided by the spacecraft's attitude control subsystem. State estimation is performed onboard in real-time using the Goddard Enhanced Onboard Navigation System flight software, which is embedded in the Navigator receiver. The current concept of operations for formation maintenance consists of a sequence of two maintenance maneuvers that is performed every 2 weeks. Phase 2b of the MMS mission, in which the spacecraft are in 1.2 x 25 Earth radii orbits with nominal separations at apogee ranging from 30 km to 400 km, has the most challenging navigation requirements because, during this phase, GPS signal acquisition is restricted to less than one day of the 2.8-day orbit. This paper summarizes the results from high-fidelity simulations to determine if the MMS navigation requirements can be met between and immediately following the maintenance maneuver sequence in Phase 2b.

Scaperoth, Paige Thomas

Relative Terrain Imaging Navigation (RETINA) Tool for the Asteroid Redirect Robotic Mission (ARRM)

As a part of the NASA initiative to collect a boulder off of an asteroid and return it to Lunar orbit, the Satellite Servicing Capabilities Office (SSCO) and NASA GSFC are developing an on-board relative terrain imaging navigation algorithm for the Asteroid Redirect Robotic Mission (ARRM). After performing several flybys and dry runs to verify and refine the shape, spin, and gravity models and obtain centimeter level imagery, the spacecraft will descend to the surface of the asteroid to capture a boulder and return it to Lunar Orbit. The algorithm implements Stereophotoclinometry methods to register landmarks with images taken onboard the spacecraft, and use these measurements to estimate the position and orientation of the spacecraft with respect to the asteroid. This paper will present an overview of the ARRM GN&C system and concept of operations as well as a description of the algorithm and its implementation. These techniques will be demonstrated for the descent to the surface of the proposed asteroid of interest, 2008 EV5, and preliminary results will be shown.

Navigation