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Mars probe onboard autonomous orbit calculation method

A technology for Mars probes and autonomous orbits, applied in neural learning methods, neural architectures, biological neural network models, etc., can solve the problem that the perturbation model does not reach the earth satellite, etc., and achieve the effect of satisfying constraints and limited resources

Inactive Publication Date: 2017-12-08
SHANGHAI AEROSPACE CONTROL TECH INST
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AI Technical Summary

Problems solved by technology

[0005] Compared with near-Earth satellites, the current perturbation model of the Mars probe during the flight is far from the accuracy of the Earth satellite. Require

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  • Mars probe onboard autonomous orbit calculation method

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Embodiment Construction

[0032] The present invention provides a method for calculating an autonomous orbit on a Mars rover. In order to make the present invention more obvious and easy to understand, the present invention will be further described below with reference to specific embodiments and drawings.

[0033] The autonomous orbit calculation method on the Mars rover of the present invention is a method for calculating the autonomous orbit on the Mars rover based on a radial basis neural network algorithm.

[0034] The RBF neural network structure is as figure 1 As shown, the radial basis function network is a forward network composed of three layers: the first layer is the input layer, such as figure 1 In the input layer nodes x1, x2, x3, xm, etc., the number of nodes m is equal to the dimension of the input; the second layer is the hidden layer, such as figure 1 The hidden layer nodes in Q1, Qi, Qn, etc., the number of nodes n depends on the complexity of the problem; the third layer is the output lay...

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Abstract

The invention discloses a mars probe onboard autonomous orbit calculation method, which is a calculation method based on radial basis function neural network curve fitting. The method includes the following steps: building a three-layer radial basis function network model; getting orbit prediction data of a mars probe within a period of time according to ground orbit determination, and training the radial basis function network model by taking the data as a training sample; and finally, uploading the trained radial basis function neural network model as an onboard orbit prediction model to the mars probe. There is neither need for establishment of a complex dynamic model on a satellite nor need for ephemeris calculation. The prediction precision is almost equal to the ground orbit prediction precision. The method is also suitable for engineering implementation. The method not only can satisfy the engineering precision constraints of the recursion result, but also can satisfy the constraints of limited resources of onboard computers.

Description

Technical field [0001] The invention relates to a deep space probe orbit calculation technology, in particular to an autonomous orbit calculation method on a Mars probe. Background technique [0002] The Mars rover is subject to the gravitational action of various celestial bodies and other non-gravitational perturbations during the flight. Due to the greater influence of the ground-based measurement and control communication delay during the Mars exploration process, the rover's autonomous orbit calculation capability is to obtain real-time attitude information and guarantee The key to the communication link. The Mars Climate Orbiter (Mars Climate Orbiter) launched by the National Aeronautics and Space Administration (NASA) in 1998 was burnt down due to the wrong parameter unit in the orbital dynamics model, which caused the probe to obtain the wrong navigation information to enter the Martian atmosphere. [0003] In the on-board real-time orbit recursive algorithm of the probe, ...

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Application Information

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IPC IPC(8): G06N3/04G06N3/08
CPCG06N3/08G06N3/045
Inventor 周杰肖东东聂钦博刘宇谭晓宇许贤峰
Owner SHANGHAI AEROSPACE CONTROL TECH INST
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