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Multi-sensor fusion wind speed and direction estimation method based on radar wind measurement combination strategy

A multi-sensor fusion, wind speed and wind direction technology, applied to instruments, measuring devices, radio wave measurement systems, etc., can solve the problems of poor sensor estimation accuracy and low accuracy

Active Publication Date: 2020-09-22
HARBIN ENG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Existing sensors have poor estimation accuracy for wind speed and wind direction. Since the error of wind measurement by on-board sensors has a nonlinear relationship with the free flow wind direction / wind speed, the wind estimated by the traditional optimal weighted fusion algorithm will not High accuracy in all wind angles
Another means of wind measurement on board is to use nautical radar images to invert the wind direction value on the sea surface several kilometers away from the ship. Its advantage is that the measurement area is far away from the ship and the free flow field is not disturbed by structures such as the hull. However, its disadvantage is accuracy lower

Method used

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  • Multi-sensor fusion wind speed and direction estimation method based on radar wind measurement combination strategy
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  • Multi-sensor fusion wind speed and direction estimation method based on radar wind measurement combination strategy

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specific Embodiment approach 1

[0070] Step 1, get sensor weights:

[0071] The experiment of obtaining wind speed and wind direction measurements was carried out offline, and the modeled structure of the mast part of the ship was meshed and the boundary conditions and inlet conditions were set. According to the set physical model and equations, the CFD calculation software calculated the The wind direction and wind speed values ​​at different sensor placement positions, the obtained sensor wind speed and wind direction values ​​at different sensor placement positions are used as the basic data for sensor fusion, and the sensor wind speed values ​​are grouped one by one with a fixed step within the specified wind direction range. Under the condition of sensors, the corresponding weight of each group of sensors after grouping is obtained.

[0072] Step 2, introduce radar wind direction for data screening:

[0073] According to the free flow wind direction value measured by the radar as the reference constrai...

specific Embodiment approach 2

[0077] On the basis of the specific embodiment one, step 1 further includes the following steps:

[0078] Step 1.1, carry out the experiment of obtaining the wind speed and wind direction measurement value of the sensor at different sensor arrangement positions offline through the CFD calculation software, model the mast part of the ship, mesh the mast model structure, and set the boundary conditions of the entire model, Calculate the wind direction and wind speed at different sensor layout positions according to the set physical model and equation;

[0079] Step 1.2, according to step 1.1, obtain the sensor wind speed and direction values ​​at different sensor locations as the basic data for sensor fusion, and use the free flow true wind speed v ref With each sensor arrangement location wind speed v sensor Orthogonal decomposition along the X-axis and Y-axis;

[0080] Step 1.3, according to the true wind speed determined in step 1.2 and all sensor wind speed component data,...

specific Embodiment approach 3

[0103] On the basis of the second specific embodiment, step 2 further includes the following steps:

[0104] Step 2.1, introduce the radar wind direction measurement data θ radar Constrain the wind direction and angle range of sensor measurement data;

[0105] Step 2.2, there is an error in the wind direction data measured by the radar, and the wind direction error measured by the radar is added to constrain the angle range θ radar ±θ 0 Within, after completing the grouping in step 1, find and store the weight distribution of each sensor under the corresponding angle range;

[0106] Step 2.3, according to the corresponding weight value of each sensor obtained in 2.2, estimate the estimated value of wind speed and wind direction in each group of angle ranges.

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Abstract

The invention provides a multi-sensor fusion wind speed and direction estimation method based on a radar wind measurement combination strategy. The method comprises: acquiring a sensor weight; takinga free incoming flow wind direction value measured by a radar as a reference constraint of a relative wind direction, verifying sensor information under a wind direction angle range constraint, screening sensor weights of corresponding groups, and further estimating wind directions and wind speed values under different sensor weights; and adding each group of obtained wind speed component vectors,calculating estimated values of each group of wind direction and wind speed, introducing a cost function, inputting the estimated values of each group of wind direction and wind speed in a radar measurement wind direction angle error range, and outputting a result with the minimum cost function as an optimal estimated value of the wind direction and the wind speed. Compared with a traditional optimal weighted fusion method, the method has the advantages that the corrected wind speed and wind direction measurement precision is greatly improved, and the fusion effect is better than that of thetraditional method.

Description

technical field [0001] The invention relates to a method for estimating wind speed and direction, in particular to a method for estimating wind speed and direction through multi-sensor fusion. Background technique [0002] Nowadays, with the development of science and technology, the country pays more and more attention to the development and utilization of the ocean, and there are abundant resources in the ocean. The development of ship equipment at sea must keep up with the development of the times. For some ships that can provide aircraft takeoff or landing, the measurement and estimation of the accurate spatial distribution of the airflow field on the surface of the ship is a very important link. For example, when a helicopter ascends or lands, it is necessary to provide the pilot with real-time measurements or estimated parameters of the steady-state free-flow wind speed and wind direction on the ship surface, so that the pilot can control the safe take-off or landing ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S13/95
CPCG01S13/956Y02A90/10
Inventor 卢志忠张玉莹孟琳琳于环宇孙雷郭树渊文保天
Owner HARBIN ENG UNIV