A method for predicting orbit errors of broadcast ephemeris by improved BP neural network

A technology of BP neural network and broadcast ephemeris, applied in the direction of biological neural network model, neural architecture, measuring device, etc., can solve problems such as easy to fall into local minimum, poor robustness, sensitive initial setting of parameters, etc., to improve satellite Effects of orbit determination accuracy, accuracy improvement, and sensitivity reduction

Inactive Publication Date: 2019-01-04
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0006] Aiming at the complicated problem of improving the accuracy of orbit determination by refining the dynamic model in the prior art, the BP neural network is used to train the nonlinear mapping relationship bet

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  • A method for predicting orbit errors of broadcast ephemeris by improved BP neural network
  • A method for predicting orbit errors of broadcast ephemeris by improved BP neural network
  • A method for predicting orbit errors of broadcast ephemeris by improved BP neural network

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Embodiment 1

[0051] This embodiment elaborates in detail the specific embodiment of the method for predicting the orbit error of broadcast ephemeris based on the improved BP neural network when applying the actual BDS broadcast ephemeris. figure 1 Be the implementation process flowchart of the present invention, concrete realization steps are as follows:

[0052] Step 1: Collect the data required for the BP neural network to predict the orbit error of broadcast ephemeris, including: epoch reference time, satellite position and velocity, perturbation correction number, and orbit error of broadcast ephemeris.

[0053] Step 1.1: This embodiment collects the data of 10 days in total from October 1st to 10th, 2017, and the sampling interval is 1 hour. Download the BDS broadcast ephemeris from NASA's Crustal Dynamics Data Information System (CDDIS) , using broadcast ephemeris parameters to calculate satellite three-dimensional position vector (X, Y, Z) and three-dimensional velocity vector (V x...

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Abstract

The invention discloses a method for predicting the orbit errors of a broadcast ephemeris by using an improved BP neural network, belonging to the technical field of satellite navigation data processing. The method for realizing the invention comprises the follow steps of: data required for predicting orbit error of broadcast ephemeris is collected by use of a BP neural network; the data needed byBP neural network is preprocessed; then the BP neural network model is constructed by using the preprocessed data; then the initial weights and thresholds of BP neural network model are optimized byPSO algorithm; the improved BP neural network model is trained again; finally, using the test data to evaluate the accuracy of the improved BP neural network model, the orbit error of broadcast ephemeris is predicted and compensated. The invention can reduce sensitivity to initial parameters, avoid falling into local minimum value, effectively improve satellite orbit determination accuracy and reduce system-level error of satellite navigation system.

Description

technical field [0001] The invention relates to a method for predicting broadcast ephemeris orbit errors by using an improved BP neural network, and belongs to the technical field of satellite navigation data processing. Background technique [0002] The BeiDou Navigation Satellite System (BDS) is an important national space infrastructure. The master control station uses the orbit determination value to extrapolate and form the broadcast ephemeris, and the receiver can calculate the satellite orbit according to the broadcast ephemeris parameters. Real-time location, and users can locate and navigate themselves through the location of several satellites, so orbit accuracy is one of the key factors restricting the performance of satellite navigation services. [0003] One way to improve the accuracy of orbit determination is to establish a more accurate mathematical model of the system. Satellites will be affected by various perturbations in actual operation. Some known pertu...

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Application Information

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IPC IPC(8): G06F17/50G06N3/04G06N3/00G01S19/23
CPCG06N3/006G01S19/23G06F30/20G06N3/045
Inventor 许承东彭雅奇牛飞郑学恩赵靖
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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