A Fast Search-Free Algorithm for Star Sensor Frame Identification by Star Configurations. A Version of Onboard Implementation

2021 ◽  
Vol 12 (3) ◽  
pp. 254-264
Author(s):  
V. V. Barke ◽  
A. A. Venkstern ◽  
V. A. Kottsov ◽  
A. V. Tavrov ◽  
A. V. Yudaev
Keyword(s):  
Star Sensor ◽  
Fast Search ◽  
Star Configurations

A Fast Search-Free Algorithm for Star Sensor Frame Identification by Star Configurations. A Version of Onboard Implementation

2021 ◽  
Vol 29 (3) ◽  
pp. 80-95
Author(s):  
V.V. Barke ◽  
◽  
А.А. Venkstern ◽  
V.A. Kottsov ◽  
A.V. Tavrov ◽  
...  
Keyword(s):  
Feature Space ◽  
Local Features ◽  
Computer Memory ◽  
Identification Algorithm ◽  
Star Sensor ◽  
Relevant Feature ◽  
Fast Search ◽  
Onboard Computer ◽  
Star Configurations

The paper presents a method for identifying the frame of a star sensor (SS), based on determination of the star local features allowing its unique recognition. The star identifiers are located in a multidimensional integer feature space, and the relevant feature catalog presents a disperse array, which provides search-free star determination. Examples of onboard implementation of feature catalog are presented, containing the stars up to magnitude of six. The required memory is estimated, and a method is proposed for compressing the feature catalog to be recorded in the onboard computer memory. The frame identification algorithm using the reduced feature catalog is described in detail. The algorithm was tested on real sky frames.

scholarly journals The Forward-Plane Star in $$^1$$H(d, pp)n Breakup at E$$_{{{\varvec{d}}}}=\mathbf{80}$$ MeV/nucleon

2021 ◽  
Vol 62 (4) ◽  
Author(s):  
A. Wilczek ◽  
A. Szadziński ◽  
N. Kalantar-Nayestanaki ◽  
St. Kistryn ◽  
A. Kozela ◽  
...  
Keyword(s):  
Cross Section ◽  
Beam Energy ◽  
Detector System ◽  
Systematic Analysis ◽  
Star Configurations

AbstractAnalysis of the data acquired with the BINA detector system in $$^1$$ 1 H(d, pp)n reaction at the beam energy of 80 MeV/nucleon makes a systematic analysis of the star configurations possible. This paper shows the preliminary cross section of the Forward-Plane Star (FPS) configuration with the neighbouring configurations.

scholarly journals Fast Search Method Based on Vector Quantization for Raman Spectroscopy Identification

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1970
Author(s):  
Jun-Kyu Park ◽  
Suwoong Lee ◽  
Aaron Park ◽  
Sung-June Baek
Keyword(s):  
Search Algorithm ◽  
Principal Component ◽  
Search Method ◽  
Reference Spectrum ◽  
Search Range ◽  
Fast Search ◽  
Input Spectrum ◽  
Computationally Intensive ◽  
Multiple Clusters ◽  
Full Search

In spectroscopy, matching a measured spectrum to a reference spectrum in a large database is often computationally intensive. To solve this problem, we propose a novel fast search algorithm that finds the most similar spectrum in the database. The proposed method is based on principal component transformation and provides results equivalent to the traditional full search method. To reduce the search range, hierarchical clustering is employed, which divides the spectral data into multiple clusters according to the similarity of the spectrum, allowing the search to start at the cluster closest to the input spectrum. Furthermore, a pilot search was applied in advance to further accelerate the search. Experimental results show that the proposed method requires only a small fraction of the computational complexity required by the full search, and it outperforms the previous methods.

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