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Position Estimation Using the Image Derivative †

Aerospace Engineering, Texas A&M University, College Station, TX 77843, USA
Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX 78712, USA
NASA Johnson Space Center, Houston, TX 77058, USA
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in 25th AAS/AIAA Space Flight Mechanics Meeting, Williamsburg, VA, USA, 11–15 January 2015 .
Academic Editor: Konstantinos Kontis
Aerospace 2015, 2(3), 435-460;
Received: 19 March 2015 / Revised: 18 June 2015 / Accepted: 18 June 2015 / Published: 3 July 2015
(This article belongs to the Special Issue Driving Forward Aerospace Innovation)
This article describes an image processing algorithm to identify the size and shape of a spherical reflecting celestial body prominently depicted in images taken from a spacecraft with an optical camera, with the purpose of estimating the relative distance between target and observer in magnitude and direction. The approach is based on the fact that in such images, the pixels belonging to the target’s hard edge have the highest values of the image derivative; therefore, they are easily recognizable when the image is processed with a gradient filter. Eventual extraneous points polluting the dataset (outliers) are eliminated by two methods applied in sequence. The target center and radius are estimated by non-linear least squares using circular sigmoid functions. The proposed image processing has been applied to real and synthetic Moon images. An error analysis is also performed to determine the performance of the proposed method. View Full-Text
Keywords: navigation; image processing; autonomy navigation; image processing; autonomy
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MDPI and ACS Style

Mortari, D.; De Dilectis, F.; Zanetti, R. Position Estimation Using the Image Derivative. Aerospace 2015, 2, 435-460.

AMA Style

Mortari D, De Dilectis F, Zanetti R. Position Estimation Using the Image Derivative. Aerospace. 2015; 2(3):435-460.

Chicago/Turabian Style

Mortari, Daniele, Francesco De Dilectis, and Renato Zanetti. 2015. "Position Estimation Using the Image Derivative" Aerospace 2, no. 3: 435-460.

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