Spacecraft orbit determination method based on data driving

A data-driven, method-determining technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as inability to make full use of big data, analytical model description, and complex high-precision dynamic models

Active Publication Date: 2019-07-26
PLA PEOPLES LIBERATION ARMY OF CHINA STRATEGIC SUPPORT FORCE AEROSPACE ENG UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

The traditional method has high stability and maturity for dealing with the problem of orbit determination with a small amount of data. However, with the increasing frequency of space launch missions, the number of various spacecraft in space has increased significantly. When fa

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  • Spacecraft orbit determination method based on data driving
  • Spacecraft orbit determination method based on data driving
  • Spacecraft orbit determination method based on data driving

Examples

Experimental program
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Effect test

Embodiment 1

[0067] Embodiment 1 of the present invention provides a data-driven spacecraft orbit determination method, which is different from the traditional orbit determination method. It is not necessary to establish the observation equation and dynamic equation of the spacecraft from the station, but from the perspective of data-driven, First construct a weighted sample set for orbit determination, then use the distribution regression theory in machine learning, use the elastic network as the loss function, and learn the mapping relationship from the measurement data to the target orbit through the samples, so as to realize the orbit determination of the spacecraft, including:

[0068] Step 1: Orbit determination sample set Z={X, Y} composed of measurement data set X and corresponding target spacecraft orbit set Y, and weight the measurement data to construct orbit determination weighted sample set;

[0069] Step 2: Calculate the Gram matrix of the constructed orbit determination weigh...

Embodiment 2

[0104] Embodiment two: a specific embodiment:

[0105] Measurement datasets are noise-free

[0106] Taking space-based spacecraft orbit determination that only measures angles as an example, simulate the orbit determination scenario of a low-orbit observation platform for a high-orbit spacecraft, and construct a weighted orbit determination sample set through error-free simulation data Among them, a total of 800 sets of simulation data, each set of data, x i The number of samples is 50, the interval is 10 seconds, and the x i,n In , there are 5-dimensional data including right ascension, declination and the position vector of the space-based observation platform. Using the method of cross-validation, 160 groups are randomly selected from 800 groups of data as the verification set, 80 groups are used as the test set, and the remaining 560 groups are used as the training set.

[0107] In the selection of the weight coefficient matrix, different groups of weight coefficients ...

Embodiment 3

[0115] Embodiment three: another specific embodiment:

[0116] The measurement data set is noisy

[0117] In order to reflect the real orbit determination situation, in this embodiment, the variance of (2″) is added to the angle measurement data and the platform position vector respectively. 2 、(0.1km) 2 Gaussian white noise, and keep other implementation steps consistent with Example 1, the results obtained are as follows Figure 7 ~ Figure 12 shown in . The detailed comparison results for noise-free and noise-containing are shown in Table 1:

[0118] Table 1 RMSE comparison of orbit determination results without noise and with noise

[0119]

[0120]

[0121] It can be seen that the effect of adding noise on the orbit determination result is not significant, which is consistent with the results shown in the attached figure.

[0122] In order to reflect this advantage, the Laplace method is introduced as the traditional orbit determination method for comparison, an...

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Abstract

The invention discloses a spacecraft weighted orbit determination method based on data driving, and the method comprises the steps: enabling an orbit determination sample set Z consisting of a measurement data set X and a corresponding target spacecraft orbit set Y to be equal to {X, Y}, carrying out the weighting of the measurement data, and constructing an orbit determination weighted sample set; calculating a Gram matrix of the constructed orbit determination weighted sample set, and taking an elastic network as a loss function; and calculating an optimal estimation value of a spacecraft orbit determination result y (t) based on the Gram matrix. According to the method, a complex dynamic model does not need to be constructed, the idea of machine learning is introduced, and an unknown spacecraft orbit can be estimated by learning a large number of nominal orbits with existing tags; besides, the training data and the test data have the same noise characteristics, and the sample data is taken as the training data, so that the sensitivity of the orbit determination result to the measurement noise can be reduced, and the application prospect is wide.

Description

technical field [0001] The invention relates to a method for determining a spacecraft orbit, that is, a data-driven method for determining a spacecraft orbit, belonging to the field of spacecraft orbit dynamics. Background technique [0002] Spacecraft orbit determination is a fundamental issue in the field of spacecraft on-orbit measurement and control and space situational awareness, and has a wide range of application backgrounds. The so-called spacecraft orbit determination is to determine the orbital elements of the target based on the observation data of the unknown spacecraft (target) by ground-based or space-based observation equipment. The types of observation data include angle measurement (right ascension, declination), distance measurement, etc. information. The traditional orbit determination method needs to establish two models: one is the observation model describing the relative positional relationship between the spacecraft and the observation equipment, an...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06F17/18
CPCG06F17/18G06F30/20
Inventor 冯飞张雅声李智李恒年方宇强黄秋实陶雪峰卢旺霍俞蓉李纪莲汤亚锋刁华飞
Owner PLA PEOPLES LIBERATION ARMY OF CHINA STRATEGIC SUPPORT FORCE AEROSPACE ENG UNIV
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