Autonomous optical navigation using nanosatellite-class instruments: a Mars approach case study

Enright, John; Jovanovic, Ilija; Kazemi, Laila; Zhang, Harry; Dzamba, Tom

doi:10.1007/s10569-017-9800-x

Cited by 11 publications

(19 citation statements)

References 19 publications

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“…The previous studies on interplanetary optical-only orbit determination, including those from the DS1 team, presented accuracy results derived from various types of navigation filter for one or more specific trajectories [21,[23][24][25]. To facilitate a broader assessment, the uncertainty associated with a kinematic estimate of spacecraft position § is used here as a conservative approximation of the uncertainty that would be achieved with a navigation filter.…”

mentioning

confidence: 99%

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

Broschart

Bradley

Bhaskaran

2019

Journal of Spacecraft and Rockets

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mentioning

confidence: 99%

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

Broschart

Bradley

Bhaskaran

2019

Journal of Spacecraft and Rockets

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“…The scenario used observations of Mars and its moons to aid in state estimation. In previous work, Enright et al [22] studied the feasibility of using an EKF-based navigation system during a hyperbolic Mars approach. The filter fused observations of Mars and its moons to provide orbit determination.…”

Section: Hyperbolic Mars Approachmentioning

confidence: 99%

“…This work utilizes a previously defined framework derived in Enright et al [22], but evaluates the convergence and accuracy of various algorithms to perform nonlinear estimation. Other studies have examined similar scenarios, Christian and Lightsey [23], used a EKF for autonomous OpNav in a planetary flyby of Venus.…”

Section: Hyperbolic Mars Approachmentioning

confidence: 99%

Nonlinear Estimation for Autonomous Optical Navigation

Hallgrimson¹

2021

Preprint

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Many interplanetary mission concepts can benefit from autonomous orbit estimation, particularly during critical mission phases. Previous studies have examined the feasibility of optical navigation using nanosatellite class instruments. While promising, these techniques are not without drawbacks. Convergence of the navigation estimates are often sensitive to errors in initial state estimates. This thesis compares various methods to perform nonlinear estimation for autonomous optical navigation. These methods include an extended Kalman filter (EKF), an unscented Kalman filter (UKF), a particle filter (PF), a fixed-lag smoother (FLS), and moving horizon estimation (MHE). The EKF, UKF, and PF can be implemented in real time, while the FLS and MHE implement a delay into the estimation process. To compare the performance of each state estimator three initial reference scenarios around Mars were considered: a hyperbolic flyby, an elliptic orbit and a orbital maneuver using observations of Mars and its moons. Parameter estimation was also explored, where the mass of Mars was to be estimated as a reference parameter in both the hyperbolic and elliptical trajectories. One last reference scenario included a low Earth orbit (LEO) using observations of satellites in a geosynchronous equatorial orbit. In each case, the FLS and MHE showed similar or better performance over each state estimator but at the cost of an increased computation time with respect to the reference EKF. Similarly the UKF was able to provide improved results withe respect to the EKF. While, the PF provided poor estimates in the Mars trajectories but improvements were seen from the UKF and EKF in the LEO scenario.

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“…In our work, we extend the analysis including image distortion and frame drop. In [ 17 ], authors derive a mathematical model for a nanosatellite and implement an Extended Kalman Filter to support Autonomous Optical Navigation. In [ 18 ], authors describe a flexible and easy to implement interplanetary autonomous optical navigation system.…”

Section: Previous Workmentioning

confidence: 99%

A Robust RANSAC-Based Planet Radius Estimation for Onboard Visual Based Navigation

Gioia

Meoni

Giuffrida

et al. 2020

Sensors

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Individual spacecraft manual navigation by human operators from ground station is expected to be an emerging problem as the number of spacecraft for space exploration increases. Hence, as an attempt to reduce the burden to control multiple spacecraft, future missions will employ smart spacecraft able to navigate and operate autonomously. Recently, image-based optical navigation systems have proved to be promising solutions for inexpensive autonomous navigation. In this paper, we propose a robust image processing pipeline for estimating the center and radius of planets and moons in an image taken by an on-board camera. Our custom image pre-processing pipeline is tailored for resource-constrained applications, as it features a computationally simple processing flow with a limited memory footprint. The core of the proposed pipeline is a best-fitting model based on the RANSAC algorithm that is able to handle images corrupted with Gaussian noise, image distortions, and frame drops. We report processing time, pixel-level error of estimated body center and radius and the effect of noise on estimated body parameters for a dataset of synthetic images.

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Autonomous optical navigation using nanosatellite-class instruments: a Mars approach case study

Cited by 11 publications

References 19 publications

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

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

Nonlinear Estimation for Autonomous Optical Navigation

A Robust RANSAC-Based Planet Radius Estimation for Onboard Visual Based Navigation

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