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Method for determining inertial navigation algorithm framework based on nonlinear network

A technology of inertial navigation and determination method, applied in the field of artificial intelligence and inertial navigation, can solve the problems of different error sources of working principle, increase of inertial navigation accuracy, etc., and achieve the effect of high precision, good adaptability to inertial devices, and high precision

Active Publication Date: 2017-01-25
NO 54 INST OF CHINA ELECTRONICS SCI & TECH GRP
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Problems solved by technology

[0016] The traditional inertial navigation algorithm relies on classical Newtonian mechanics, which is a generalized algorithm. However, different inertial measurement devices have different working principles and different error sources. When using general-purpose algorithms, it is difficult to give full play to its performance, and there is a large room for improvement in inertial navigation accuracy.

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  • Method for determining inertial navigation algorithm framework based on nonlinear network
  • Method for determining inertial navigation algorithm framework based on nonlinear network
  • Method for determining inertial navigation algorithm framework based on nonlinear network

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Embodiment Construction

[0057] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0058] The cognitive inertial navigation algorithm architecture includes two parts: training and application. First, model the neural network training architecture based on a large amount of measured data; then calculate the inertial navigation results based on the trained neural network, that is, the application architecture. Neural networks are able to model complex nonlinear models of acceleration measurements and inertial navigation without prior knowledge of the mathematical equations that describe the mapping. It uses a large amount of data to learn and train the nonlinear network, and can complete the nonlinear mapping from n-dimensional input space to m-dimensional output space; when inputting non-sample data that has never been seen during training to the network, the network can also be completed by Correct mapping of input space to output s...

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Abstract

The invention discloses a method for determining an inertial navigation algorithm framework based on a nonlinear network. Non-mechanical layout is reflected in that a conventional navigation calculation manner of calculating position and speed by utilizing Newtonian mechanics equation is abandoned; and acknowledge is mainly reflected in that a navigation calculation model is automatically established based on tools such as a neural network aiming at different inertial devices. The method has the following steps: 1, the precision is higher, and since a nonlinear network model of acknowledge inertial navigation is established by analysis and digging of mass data, the model is customized, and compared with an original mechanical layout universal model, the model can be better adapted to inertial devices, thus having higher precision; and 2, the capability is promoted, a neutral network training model processes in background, and along with the optimization of training data and training methods, the capability of the acknowledge inertial navigation system is constantly improved, and therefore, the system has online updating capability.

Description

technical field [0001] The invention relates to an inertial navigation algorithm framework of a nonlinear network, and belongs to the technical fields of inertial navigation and artificial intelligence. Background technique [0002] (1) Current status of inertial navigation technology [0003] The basic principle of inertial navigation is very simple. It was proposed more than 300 years ago. It is based on Newton’s laws of mechanics. The acceleration of the vehicle’s movement is measured by a navigation accelerometer in the vehicle, and the speed of the vehicle is obtained by integral operation. and location information. The inertial navigation system includes a platform inertial navigation system and a strapdown inertial navigation system. The algorithm architecture is as attached figure 1 shown. [0004] Platform strapdown inertial navigation algorithm. Install a stable platform in the inertial navigation system (referred to as the inertial navigation system), use the ...

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Application Information

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IPC IPC(8): G01C21/20G01C21/16
CPCG01C21/16G01C21/20
Inventor 贾瑞才王博远贾浩男智奇楠刘鹏飞王青江马国驹李枭楠
Owner NO 54 INST OF CHINA ELECTRONICS SCI & TECH GRP
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