Improved triangular-based star pattern recognition algorithm for low-cost star trackers

Nabi, Abderrahim; Ahmed‐Foitih, Zoubir; Cheriet, Mohammed El-Amine

doi:10.1016/j.jksuci.2019.01.008

Cited by 7 publications

(2 citation statements)

References 20 publications

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“…Among them, one of the well-known methods was proposed by Liebe et al [1], which was based on finding the angular distance from a star to its two closest neighbours and the spherical angle between them to identify the star. This method paved the way for the development of algorithms that use star triangles for star identification [19,20,21,22,23,24]. Another well-known method, proposed by Mortari et al [23], is the pyramid algorithm which uses four stars to perform the star identification.…”

Section: Star Identification Processmentioning

confidence: 99%

Low-cost Raspberry Pi star sensor for small satellites

Sarpotdar

Nair

et al. 2022

J. Astron. Telesc. Instrum. Syst.

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We present here a low-cost Raspberry Pi (RPi)-based star sensor StarberrySense using commercial-off-theshelf (COTS) components, developed and built for applications in small satellites and CubeSat-based missions. A star sensor is one of the essential instruments onboard a satellite for attitude determination. However, most commercially available star sensors are expensive and bulky to be used in small satellite missions. StarberrySense is a configurable system -it can operate as an imaging camera, a centroiding camera, or as a star sensor. We describe the algorithms implemented in the sensor, its assembly and calibration. This payload was selected by a recent Announcement of Opportunity call for payloads to fly on the PS4-Orbital Platform by the Indian Space Research Organization (ISRO).

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Section: Star Identification Processmentioning

confidence: 99%

Low-cost Raspberry Pi star sensor for small satellites

Sarpotdar

Nair

et al. 2022

J. Astron. Telesc. Instrum. Syst.

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“…In addition, the proposed IGSWF algorithm was compared with Gaussian filtering, box filtering, mean filtering, Zheng processing [17], and SWF in the value of the centroid estimation error (CEE). The accuracy of star identification [21] was also tested when we chose different algorithms.…”

Section: Experimental Conditionsmentioning

confidence: 99%

Star Sensor Denoising Algorithm Based on Edge Protection

Liu

Zhao

et al. 2021

Sensors

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Single-pixel noise commonly appearing in a star sensor can cause an unexpected error in centroid extraction. To overcome this problem, this paper proposes a star image denoising algorithm, named Improved Gaussian Side Window Filtering (IGSWF). Firstly, the IGSWF algorithm uses four special triangular Gaussian subtemplates for edge protection. Secondly, it exploits a reconstruction function based on the characteristic of stars and noise. The proposed IGSWF algorithm was successfully verified through simulations and evaluated in a star sensor. The experimental results indicated that the IGSWF algorithm performed better in preserving the shape of stars and eliminating the single-pixel noise and the centroid estimation error (CEE) value after using the IGSWF algorithm was eight times smaller than the original value, six times smaller than that after traditional window filtering, and three times smaller than that after the side window filtering.

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