Kinematic Approximation of Position Accuracy Achieved Using Optical Observations of Distant Asteroids

Broschart, Stephen B.; Bradley, Nicholas; Bhaskaran, Shyam

doi:10.2514/1.a34354

Cited by 24 publications

(26 citation statements)

References 30 publications

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“…Recently, Broschart, et al [10] did an exhaustive study of kinematic positioning in the solar system using camera images (also known as OpNav) of main belt asteroids and developed a heuristic algorithm for selecting asteroids that could be adapted for use in autonomous deep space navigation to define asteroid imaging schedules. The algorithm factors asteroid brightness, camera quality, and asteroid location uncertainties to determine which asteroids to image based on certain heuristic cost functions.…”

Section: Onboard Optical Imaging (Opnav)mentioning

confidence: 99%

“…Additionally, representative navigation cameras examined by Broschart, et al [10] could be lumped into three categories consisting of low-end, mid-range, and highend camera features as noted in Table 2. FOV is the camera field-of-view, Θ is field of view of one camera pixel (called the IFOV), M max is the maximum apparent magnitude of the asteroid that can be detected, ψ min is the minimum allowable sun-spacecraftasteroid angle allowable.…”

Section: Onboard Optical Imaging (Opnav)mentioning

confidence: 99%

“…Note that the imaging campaign with the OpNav camera includes 37 different main belt asteroids. These were arrived at by the heuristic asteroid selection algorithm developed by Broschart [10] as being a judicious choice for this trajectory that factors asteroid brightness, camera quality, and asteroid locations plus their associated uncertainties to arrive an optimal mix of asteroids. Additionally, Phobos and Deimos, Mars' moons, are imaged by the camerathis becomes especially valuable as the spacecraft nears Mars since, with the precise knowledge of Phobos and Deimos orbits relative to Mars, these images provide strong target-relative information.…”

Section: Other Modelsmentioning

confidence: 99%

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Radiometric Autonomous Navigation Fused with Optical for Deep Space Exploration

et al. 2021

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With the advent of the Deep Space Atomic Clock, operationally accurate and reliable one-way radiometric data sent from a radio beacon (i.e., a DSN antenna or other spacecraft) and collected using a spacecraft's radio receiver enables the development and use of autonomous radio navigation. This work examines the fusion of radiometric data with optical data (i.e. OpNav) to yield robust and accurate trajectory solutions that include selected model reductions and computationally efficient navigation algorithms that can be readily adopted for onboard, autonomous navigation. The methodology is characterized using a representative high-fidelity simulation of deep space cruise, approach, and delivery to Mars. The results show that the combination of the two data types yields solutions that are almost an order of magnitude more accurate than those obtained using each data type by itself. Furthermore, the combined data solutions readily meet representative entry navigation requirements (in this case at Mars).

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Section: Onboard Optical Imaging (Opnav)mentioning

confidence: 99%

Section: Onboard Optical Imaging (Opnav)mentioning

confidence: 99%

Section: Other Modelsmentioning

confidence: 99%

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Radiometric Autonomous Navigation Fused with Optical for Deep Space Exploration

et al. 2021

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“…For a vehicle in heliocentric orbit far away from a planet, the BCRF position may be autonomously determined to sufficient accuracy to remove parallax (∼105 km) through triangulation using optical LOS observations of known planets [85], asteroids [19], or both.…”

Section: Mathematical Models For the Observation Of Starlight By Amentioning

confidence: 99%

“…Autonomous OPNAV with horizon-based methods [3] works well with resolved imagery of ellipsoidal bodies and will be demonstrated on NASA’s Artemis 1 mission [17]. Autonomous OPNAV with unresolved imagery (e.g., of asteroids [18,19] or moons [20]) may be used for kinematic positioning (essentially triangulation), a procedure that was demonstrated using JPL’s AutoNav system on the Deep Space 1 mission [21]. Third is enabling one-way ranging using radio frequency (RF) signals from the Deep Space Network (DSN) through the Deep Space Atomic Clock (DSAC) [22,23,24], which was launched during the writing of this manuscript (June 2019).…”

Section: Introductionmentioning

confidence: 99%

StarNAV: Autonomous Optical Navigation of a Spacecraft by the Relativistic Perturbation of Starlight

Christian

2019

Sensors

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Future space exploration missions require increased autonomy. This is especially true for navigation, where continued reliance on Earth-based resources is often a limiting factor in mission design and selection. In response to the need for autonomous navigation, this work introduces the StarNAV framework that may allow a spacecraft to autonomously navigate anywhere in the Solar System (or beyond) using only passive observations of naturally occurring starlight. Relativistic perturbations in the wavelength and direction of observed stars may be used to infer spacecraft velocity which, in turn, may be used for navigation. This work develops the mathematics governing such an approach and explores its efficacy for autonomous navigation. Measurement of stellar spectral shift due to the relativistic Doppler effect is found to be ineffective in practice. Instead, measurement of the change in inter-star angle due to stellar aberration appears to be the most promising technique for navigation by the relativistic perturbation of starlight.

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Optimal Beacons Selection for Deep-Space Optical Navigation

Franzese

Topputo

2020

J Astronaut Sci

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Deep-space optical navigation is among the most promising techniques to autonomously estimate the position of a spacecraft in deep space.The method relies on the acquisition of the line-of-sight directions to a number of navigation beacons. The position knowledge depends upon the tracked objects. This paper elaborates on the impact of the observation geometry to the overall performances of the method. A covariance analysis is carried out considering beacons geometry as well as pointing and input errors. A performance index is formulated, and criteria for an optimal beacons selection are derived in a scenario involving two measurements. A test case introducing ten available beacons pairs is used to prove the effectiveness of the developed strategy in selecting the optimal pair, which leads to the smallest achievable error.

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Kinematic Approximation of Position Accuracy Achieved Using Optical Observations of Distant Asteroids

Cited by 24 publications

References 30 publications

Radiometric Autonomous Navigation Fused with Optical for Deep Space Exploration

Radiometric Autonomous Navigation Fused with Optical for Deep Space Exploration

StarNAV: Autonomous Optical Navigation of a Spacecraft by the Relativistic Perturbation of Starlight

Optimal Beacons Selection for Deep-Space Optical Navigation

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