&lt;title&gt;CMOS active pixel sensor specific performance effects on star tracker/imager position accuracy&lt;/title&gt;

Hancock, B.; Stirbl, Robert C.; Cunningham, Thomas J.; Pain, Bedabrata; Wrigley, C.; Ringold, P.

doi:10.1117/12.426872

Cited by 61 publications

(22 citation statements)

References 4 publications

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“…Thus, the signal to noise ratio (SNR) of star image decreases, and the noise induced error increases. Therefore, a small number of pixels is utilized actually, such as 3-pixel-and 5-pixel-windows [8]. When the Gaussian width is relatively large and the star signal falls over the range of the sampling window, the widow limitation should be taken into consideration.…”

Section: Systematic Error Analysis Under Sampling Window Limitationmentioning

confidence: 99%

“…The center of mass (CoM) algorithm is the most widely used method to calculate the centroid of a star image [5][6][7][8]. The estimated location of the centroid is given by…”

Section: Systematic Error Of Center Of Mass (Com) Algorithmmentioning

confidence: 99%

“…Alexander et al [7] gave a general expression of the systematical error for the center of mass (CoM) method through frequency domain analysis. Hancock et al [8] studied systematic errors under different Gaussian widths, pixel fill ratios and detector sizes numerically. Fisher and Naidu [9] studied the systematic error of different algorithms under the condition of first-order approximation of Gaussian expression and derived the analytical relationship between Gaussian width and centroid error under the consideration of sampling windows limitation.…”

Section: Introductionmentioning

confidence: 99%

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Systematic error analysis and compensation for high accuracy star centroid estimation of star tracker

Jia

Yang

et al. 2010

Sci. China Technol. Sci.

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Subpixel centroid estimation is the most important star image location method of star tracker. This paper presents a theoretical analysis of the systematic error of subpixel centroid estimation algorithm utilizing frequency domain analysis under the consideration of sampling frequency limitation and sampling window limitation. Explicit expression of systematic error of centroid estimation is obtained, and the dependence of systematic error on Gaussian width of star image, actual star centroid location and the number of sampling pixels is derived. A systematic error compensation algorithm for star centroid estimation is proposed based on the result of theoretical analysis. Simulation results show that after compensation, the residual systematic errors of 3-pixel-and 5-pixel-windows' centroid estimation are less than 2×10 −3 pixels and 2×10 −4 pixels respectively. star tracker, star image location, subpixel centroid estimation, centroid algorithm, frequency domain analysis, systematic error compensation Citation:Jia H, Yang J K, Li X J, et al. Systematic error analysis and compensation for high accuracy star centroid estimation of star tracker.

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Section: Systematic Error Analysis Under Sampling Window Limitationmentioning

confidence: 99%

“…The center of mass (CoM) algorithm is the most widely used method to calculate the centroid of a star image [5][6][7][8]. The estimated location of the centroid is given by…”

Section: Systematic Error Of Center Of Mass (Com) Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Systematic error analysis and compensation for high accuracy star centroid estimation of star tracker

Jia

Yang

et al. 2010

Sci. China Technol. Sci.

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“…2 It is a constant, uncorrelated temporal noise 9 and was modeled as noise with a normal distribution, with zero mean and a constant standard deviation: σ ro .…”

Section: Noise Sourcesmentioning

confidence: 99%

An Accurate and Efficient Gaussian Fit Centroiding Algorithm for Star Trackers

2014

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This paper presents a novel centroiding algorithm for star trackers. The proposed algorithm, which is referred to as the Gaussian Grid algorithm, fits an elliptical Gaussian function to the measured pixel data and derives explicit expressions to determine the centroids of the stars. In tests, the algorithm proved to yield accuracy comparable to that of the most accurate existing algorithms, while being significantly less computationally intensive. Hence, the Gaussian Grid algorithm can deliver high centroiding accuracy to spacecraft with limited computational power. Furthermore, a hybrid algorithm is proposed in which the Gaussian Grid algorithm yields an accurate initial estimate for a least squares fitting method, resulting in a reduced number of iterations and hence reduced computational cost. The low computational cost allows to improve performance by acquiring the attitude estimates at a higher rate or use more stars in the estimation algorithms. It is also a valuable contribution to the expanding field of small satellites, where it could enable low-cost platforms to have highly accurate attitude estimation.

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“…To determine the luminance centroid accurately, keeping the required spot size in the image plane and decreasing the variation of the spot size with the axial distance (or view angle), are highly desirable 2,3 . Generally, the appropriate spot size is obtained by image plane defocus, and variation of spot size with a different view angle is controlled by aberrations balancing during the optical design of the lens system 4 .…”

Section: Introductionmentioning

confidence: 99%

Focal Adjustment for Star Tracker

Liu¹,

Yang²,

Tan³

et al. 2010

DSJ

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Technique of measuring intensity distribution and size of spot image developed has been discussed, which is especially suitable for defocus adjustment in ground test of star tracker. A novel approach for choosing a proper defocusing position has been proposed based on collimator, Gaussian surface fitting method, and other ordinary instruments. It proves to be practical and adequate in the development of distant object tracking such as star tracker.

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<title>CMOS active pixel sensor specific performance effects on star tracker/imager position accuracy</title>

Cited by 61 publications

References 4 publications

Systematic error analysis and compensation for high accuracy star centroid estimation of star tracker

Systematic error analysis and compensation for high accuracy star centroid estimation of star tracker

An Accurate and Efficient Gaussian Fit Centroiding Algorithm for Star Trackers

Focal Adjustment for Star Tracker

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