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Integrated navigation method and system

An integrated navigation system and integrated navigation technology, applied in the field of integrated navigation methods and systems, to achieve the effects of solving the difficulty of gradient backhaul, fast tuning speed, and strong learning ability

Active Publication Date: 2020-06-12
INST OF COMPUTING TECH CHINESE ACAD OF SCI
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem of flooding caching data in the named data network in the prior art, and the shortcomings of the above-mentioned existing solutions, the present invention proposes a combined navigation method and system

Method used

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  • Integrated navigation method and system

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Embodiment

[0056] The technical solution of the present invention involves the following aspects: 1) The value of the process noise covariance matrix depends on prior knowledge. In the traditional Kalman filter integrated navigation algorithm, the values ​​of process noise covariance matrix Q and measurement noise covariance matrix R have a great influence on the performance of Kalman filter. If the Q array and R array with large errors are used, the accuracy of integrated navigation will inevitably be reduced, and sometimes even filter divergence will be caused. In practical applications, the parameter values ​​of the R matrix often depend on the quality of the currently received GNSS measurements, while the Q matrix depends on the prior knowledge of the performance of a specific IMU device. 2) The Q matrix has no true value to be calibrated, and the calculation involved is extremely complicated. The process noise covariance matrix depends on the inherent performance of the sensor, and...

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Abstract

The invention discloses an integrated navigation method and an integrated navigation system. The method comprises the following steps: acquiring and storing integrated navigation positioning data of the integrated navigation system in the latest specific duration; calculating a current integrated navigation positioning error, and judging whether the error is greater than a threshold; if the positioning error is greater than the threshold value, constructing an initial inertial navigation process noise covariance matrix, and performing reinforcement learning-based adaptive estimation on the process noise covariance matrix to obtain optimal estimation of the process noise covariance matrix; and optimizing the relative weight of the predicted value and the measured value, and outputting an adjusted integrated navigation result. According to the invention, a personalized integrated navigation scheme can be provided for single specific inertial navigation equipment, and dependence on prioriknowledge is avoided; the adopted model is strong in learning ability and high in tuning speed, and the challenge of difficulty in gradient backhaul is solved; the positioning accuracy of the integrated navigation system is improved, and the robustness is high in different environments.

Description

technical field [0001] The invention belongs to the technical field of navigation control, and in particular relates to a combined navigation method and system. Background technique [0002] In recent years, more and more people pay attention to autonomous navigation system with high reliability. In terms of industry demand, autonomous navigation systems can be used for mobile measurement, providing precise positioning and attitude determination technology, bringing revolutionary changes to the surveying and mapping industry; in terms of public demand, smart phones, drones, self-driving cars, mobile robots The intelligent carrier represented by the mobile phone is highly dependent on precise position information when performing autonomous movements. The autonomous navigation system is the basis and core of its environmental perception and decision-making control. As far as autonomous driving is concerned, the market potential for autonomous navigation systems is huge. Cont...

Claims

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Application Information

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IPC IPC(8): G01C21/16G01C21/28G01S19/47
CPCG01C21/165G01C21/28G01S19/47
Inventor 罗海勇高喜乐包林封宁勃坤龚依林肖逸敏
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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