Top level systems requirements analysis for a ground cooperative orbital debris avoidance system

Vance, Leonard; Thangavelautham, Jekan; Fernández, José María Rodríguez

doi:10.1109/aero50100.2021.9438319

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Table 3 shows the number of overlapping cycles and calculation time for each calculation process. The design principle of overlapping cycles between processes is to ensure that the input used in the next level process calculation is the output completed by the previous level process calculation, which is searched and filtered in D(n) ∈ [3,7] (k = 1). Parallel computing processes such as s1.1 and s1.2, due to simultaneous computation, the parallelism is based on the longest module time, and the selection of the parallelism for the second longest module is based on the calculation time not exceeding the longest module calculation time.…”

Section: Parallelism Parameter Calculationmentioning

confidence: 99%

“…2 The space-based target observation system mainly relies on the optical load to carry out continuous detection in the airspace, screen the moving targets in the stellar background that are different from the background, obtain the target position and trajectory information, and make prediction based on the existing trajectory for collision warning and other applications. 3 For the tracking of faint space targets, especially the tracking and trajectory prediction of multiple targets, Kalman filtering is mainly relied on to complete the discontinuous trajectory association and the differentiation of near trajectory. 4 Especially for attitude changes of close-range targets and trajectory attitude changes in maneuvering process, Kalman filter can effectively complete estimation and solution.…”

Section: Introductionmentioning

confidence: 99%

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Parallel accelerated computing architecture for dim target tracking on‐board

Yu,

Huang,

et al. 2023

Computational Intelligence

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The real‐time tracking process of dim targets in space is mainly achieved through the correlation and prediction of dots after the detection and calculation process. The on‐board calculation of the tracking needs to be completed in milliseconds, and it needs to reach the microsecond level at high frame rates. For real‐time tracking of dim targets in space, it is necessary to achieve universal tracking calculation acceleration in response to different space regions and complex backgrounds, which poses high requirements for engineering implementation architecture. This paper designs a Kalman filter calculation based on digital logic parallel acceleration architecture for real‐time solution of dim target tracking on‐board. A unified architecture of Vector Processing Element (VPE) was established for the calculation of Kalman filtering matrix, and an array computing structure based on VPE was designed to decompose the entire filtering process and form a parallel pipelined data stream. The prediction errors under different fixed point bit widths were analyzed and deduced, and the guidance methods for selecting the optimal bit width based on the statistical results were provided. The entire design was engineered based on Xilinx's XC7K325T, resulting in an energy efficiency improvement compared to previous designs. The single iteration calculation time does not exceed 0.7 microseconds, which can meet the current high frame rate target tracking requirements. The effectiveness of this design has been verified through simulation of random trajectory data, which is consistent with the theoretical calculation error.

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Section: Parallelism Parameter Calculationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Parallel accelerated computing architecture for dim target tracking on‐board

Yu,

Huang,

et al. 2023

Computational Intelligence

View full text Add to dashboard Cite

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Real-Time Parallel LU Decomposition of Space Debris Features On-Board

Yu,

Huang,

et al. 2023

2023 IEEE 15th International Conference on Advanced Infocomm Technology (ICAIT)

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Dim Staring Debris Targets Detection Method with Dense Long Trailing Star

Huang

et al. 2023

Applied Sciences

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With the gradual increase in spacecraft in orbit, space debris monitoring has become the key to the sustainable development of space missions. A staring debris detection method is proposed for high-density stars with long tails. In order to solve the problem that the gray level of a long trailing image is not stable and continuous, rectangular fitting is used to complete the aggregation of the trailing image and reduce the influence of noise on the trailing information. The occluded state of the target was analyzed, the feature calculation method was improved, the semi-occluded scene was statistically classified, the fully connected network (FCN) based finite point feature was accurately classified, and the semi-occluded image was extracted. Based on the extracted semi-occluded image, the inter-frame association can improve the success probability of target association and realize the effective detection and tracking of debris. The detection accuracy was tested for the changing inter-frame interval and signal-to-noise ratio (SNR), and the relationship between the index parameters and key parameters was given. Compared with previous literature, this design can detect and track the occluded target with a detection rate of more than 90% and a false alarm rate of less than 10%.

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Top level systems requirements analysis for a ground cooperative orbital debris avoidance system

Cited by 3 publications

References 7 publications

Parallel accelerated computing architecture for dim target tracking on‐board

Parallel accelerated computing architecture for dim target tracking on‐board

Real-Time Parallel LU Decomposition of Space Debris Features On-Board

Dim Staring Debris Targets Detection Method with Dense Long Trailing Star

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