A Star Pattern Recognition Technique Based on the Binary Pattern Formed from the FFT Coefficients

Mehta, Deval; Chen, Shoushun

doi:10.1109/iscas.2018.8350965

Cited by 4 publications

(1 citation statement)

References 21 publications

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“…In spite of many previous studies to accommodate dynamic conditions, there have been few studies on the aspects of the identification process. Star identification in LIS mode is essential for star trackers, and could thus serve as a direct measure of its performance [14][15][16]. Of course, some recent literature has focused on fast identification of stars for agile spacecraft or for fast recovery after an abrupt power outage [17,18].…”

Section: Introductionmentioning

confidence: 99%

Algorithm with Patterned Singular Value Approach for Highly Reliable Autonomous Star Identification

Kim

Bang

2020

Sensors

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In the work reported in this paper, a lost-in-space star pattern identification algorithm for agile spacecraft was studied. Generally, the operation of a star tracker is known to exhibit serious degradation or even failure during fast attitude maneuvers. While tracking methods are widely used solutions to handle the dynamic conditions, they require prior information about the initial orientation. Therefore, the tracking methods may not be adequate for autonomy of attitude and control systems. In this paper a novel autonomous identification method for dynamic conditions is proposed. Additional constraints are taken into account that can significantly decrease the number of stars imaged and the centroid accuracy. A strategy combining two existing classes for star pattern identification is proposed. The new approach is intended to provide a unique way to determine the identity of stars that promises robustness against noise and rapid identification. Moreover, representative algorithms implemented in actual space applications were utilized as counterparts to analyze the performance of the proposed method in various scenarios. Numerical simulations show that the proposed method is not only highly robust against positional noise and false stars, but also guarantees fast run-time, which is appropriate for high-speed applications.

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Section: Introductionmentioning

confidence: 99%

Algorithm with Patterned Singular Value Approach for Highly Reliable Autonomous Star Identification

Kim

Bang

2020

Sensors

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On efficient 3D object retrieval

Liu,

Wong

2024

The VLDB Journal

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Due to the growth of the 3D technology, digital 3D models represented in the form of point clouds have attracted a lot of attention from both industry and academia. In this paper, due to a variety of applications, we study a fundamental problem called the 3D object retrieval, which is to find a set of 3D point clouds stored in a database that are similar to a given query 3D point cloud. To the best of our knowledge, solving the problem of 3D object retrieval efficiently remains unexplored in the research community. In this paper, we propose a framework called C$$_2$$ 2 O to find the answer efficiently with the help of an index built on the database. In most of our experiments, C$$_2$$ 2 O performs up to 2 orders of magnitude faster than all adapted algorithms in the literature. In particular, when the database size scales up to 100 million points, C$$_2$$ 2 O answers the 3D object retrieval within 10 s but all adapted exact algorithms need more than 1000 s.

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Maximum radial pattern matching for minimum star map identification

Fu,

Li,

Lin

et al. 2024

EURASIP J. Adv. Signal Process.

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This paper proposes an all-sky star map identification algorithm that can simultaneously achieve high identification probability, low algorithm complexity, and small databases for well photometric and intrinsic parameters-calibrated star sensors. The proposed algorithm includes three main steps. First, a binary radial pattern table is constructed offline. Then, the maximum value matching of the radial pattern is performed between the star spots and the guide stars, and the star pairs (i.e., the minimum star map) after radial pattern matching undergo a coarse matching through angular distance cross-validation. Finally, a reference star map is designed based on the identified star pairs, and the matching of all the star spots in the field of view is realized. Simulation and analysis results show that the database required by the proposed algorithm for 5,000 guide stars is not larger than 200 KB. Also, when false and missing star spots account for 50% of all guide stars and the star spot extraction error is 0.5 pixel (the corresponding pointing error is 26″), the average star map identification time of the proposed algorithm is less than 2 ms, and its identification probability is higher than 98%. The results demonstrate that the proposed algorithm performs better than similar algorithms.

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A Star Pattern Recognition Technique Based on the Binary Pattern Formed from the FFT Coefficients

Cited by 4 publications

References 21 publications

Algorithm with Patterned Singular Value Approach for Highly Reliable Autonomous Star Identification

Algorithm with Patterned Singular Value Approach for Highly Reliable Autonomous Star Identification

On efficient 3D object retrieval

Maximum radial pattern matching for minimum star map identification

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