Calculation method for average wind under high-precision moving platform

Abstract

The invention discloses a method for calculating average wind under a high-precision moving platform, and the method comprises the following steps: S1, judging the motion state of the platform through the attitude information of the platform; s2, judging a selection mode of a weight coefficient according to the motion state of the platform, and selecting a relative distance or relative time as the weight coefficient; s3, according to the platform attitude information, whether the platform stops moving within the calculation time range is judged, if yes, the step S5 is executed, and if not, the step S4 is executed; s4, the platform keeps moving all the time within the calculation time range, and average wind is calculated in a weighted mode; s5, if the platform stops moving within the calculation time range, the average wind in the stop state is calculated firstly; and S6, correcting the selected weight coefficient according to the platform stop time, and calculating the average wind in the whole time range after the correction is completed. The method can solve the problem that the instantaneous wind measured by the mobile platform laser wind measurement radar does not correspond to the same space area, and improves the calculation precision of the average wind of the wind measurement radar.

Description

Technical Field

[0001] The invention belongs to the technical field of wind field information calculation, and relates to a method for calculating average wind under a high-precision moving platform. Background Art

[0002] The acquisition of wind field information is one of the main tasks in the fields of meteorology and aerodynamics, and the accuracy of its measurement data is particularly important for meteorological research. Traditional wind field measurement methods mainly include radiosondes, cup anemometers, ultrasonic anemometers, wind profiler radars and other equipment, but most of them have problems such as limited installation locations, low measurement accuracy, and small measurement range. In recent years, with the development of laser technology, laser wind radar has gradually developed into one of the important means of wind field remote sensing due to its high measurement accuracy, fast scanning speed, and convenient installation.

[0003] As an important means of remote wind measurement, laser wind radar can obtain wind field information within a certain spatial range, including wind speed, wind direction, and vertical airflow. It can be installed near the airport runway to monitor real-time wind field changes over the runway. In recent years, with the continuous development of radar technology, laser wind radar has gradually been developed and applied on various dynamic platforms, such as meteorological detection vehicles equipped with laser wind radar to obtain wind field information in different geographical locations, ship-borne laser wind radar to obtain three-dimensional wind field information around the ship, and airborne laser wind radar to obtain wind profile information under the aircraft.

[0004] For wind radars installed on fixed platforms, their measurement range is relatively fixed, and they can measure wind field information in the space around the radar installation location. The instantaneous wind measured by the radar in real time is not representative due to its relatively fast dynamic fluctuations. Therefore, in the process of secondary processing and calculation of its measurement data, the average wind within a certain time range can be obtained by averaging the instantaneous wind vector, including the average wind speed and average wind direction, to reflect the wind field changes in the airspace near the radar installation location.

[0005] For wind radars under moving platforms, since the radar itself moves with the platform, the instantaneous data measured by the radar at different times correspond to wind field information in different spatial regions. If the traditional vector average method is still used to calculate the average wind, the calculated result cannot fully represent the wind field state in the area where the radar is located at the time of calculation. In addition, existing technologies are often difficult to adapt to complex dynamic changes and multi-element composite influences, and the measurement accuracy still needs to be improved. Summary of the invention

[0006] (I) Purpose of the invention

[0007] The purpose of the present invention is to provide a high-precision method for calculating the average wind under a moving platform, based on the existing moving platform laser wind measurement radar, to improve the calculation accuracy of the average wind under the moving platform.

[0008] (II) Technical solution

[0009] In order to solve the above technical problems, the present invention provides a method for calculating the average wind speed under a high-precision moving platform, comprising the following steps:

[0010] S1: Determine the platform motion state through the platform posture information;

[0011] S2: According to the platform motion state, determine the selection method of the weight coefficient and select relative distance or relative time as the weight coefficient;

[0012] S3: judging whether the platform has stopped moving within the calculation time range according to the platform posture information, if yes, go to step S5, otherwise go to step S4;

[0013] S4: The platform keeps moving within the calculation time range, and the weighted average wind is calculated;

[0014] S5: If the platform stops moving within the calculation time range, the average wind in the stopped state is calculated first;

[0015] S6: According to the platform stop time, the selected weight coefficient is corrected, and after the correction is completed, the average wind speed in the entire time range is calculated.

[0016] In step S1, the platform attitude information within the time range to be calculated is obtained, including the platform movement heading, movement speed, and the platform's own longitude and latitude. According to the change of the platform attitude within the set time range, it is determined whether the platform is performing linear motion within the current calculation time range.

[0017] In step S1, the time range T and platform movement speed (V E , V N , V S ) is the northeast celestial velocity of the platform, and the platform heading angle A H , platform pitch angle A P , the condition for judging whether it is linear motion is:

[0018]

[0019] Among them, THA H , THA P Set thresholds for heading angle and pitch angle respectively; ΔA H is the change in platform heading angle within time T, ΔA P is the change in the platform pitch angle within the time T.

[0020] In step S2, if the platform is moving in a straight line, the platform movement distance corresponding to each instantaneous wind is selected as the calculation weight; if the platform is moving in other movements other than straight line, the relative time corresponding to each instantaneous wind is selected as the calculation weight.

[0021] In step S2, if the platform moves in a straight line, the weight coefficient is calculated according to the platform moving distance. It is designed that there are N groups of instantaneous wind data in the time T, and the total distance moved in the time T is L. The platform moving distances corresponding to each group of instantaneous wind data are L1, L2, L3, ... L N ,in:

[0022] L=L1+L2+L3+…+L N

[0023] The corresponding weights are:

[0024]

[0025] In step S2, if the platform is in non-linear motion, the weight coefficient is calculated according to the time corresponding to each group of instantaneous wind. It is designed that there are N groups of instantaneous wind data within the calculation time T, and the time interval corresponding to each group of instantaneous wind data is T1, T2, T3, ...T N ,in:

[0026] T=T1+T2+T3+…+T N

[0027] The corresponding weights are:

[0028]

[0029] In step S3, after selecting the weight coefficient according to the platform motion state, the platform posture information within the calculation time range is used to determine whether the platform is in a stopped state within the time period. The judgment condition for the platform stopped state is:

[0030]

[0031] In step S4, when the weighted average wind is calculated, all instantaneous wind data within the time range are weighted averaged according to the calculated weight coefficient to finally obtain the average wind result.

[0032] In step S4, the average wind result calculation process is:

[0033] The instantaneous wind speed of each group is V1, V2, V3, ... V N , the instantaneous wind direction is A1, A2, A3, ...A N , then the components u and v projected onto the x-axis and y-axis are:

[0034]

[0035] Calculate the u and v components corresponding to the average wind:

[0036]

[0037] Then the horizontal wind speed V H and the horizontal wind direction α is:

[0038]

[0039] The angle value α is converted as follows:

[0040] when hour,

[0041] when hour,

[0042] α 气象 It is the horizontal wind direction angle value in meteorology.

[0043] In step S5, if the platform stops moving within the calculation time range, the average wind speed during the stop time period is calculated. There are M groups of instantaneous wind data in this time period. The average wind speed V in this time period is calculated. T The corresponding u T 、v T Serving size:

[0044]

[0045] In step S6, after the calculation is completed, the weight coefficient is corrected according to the time when the platform stops. If the relative distance is selected as the weight coefficient, the distance corresponding to the instantaneous wind before the stop is used as V T If time is selected as the weight coefficient, then the total time corresponding to the M group of data is used as V T The weight is corrected; finally, the average wind in the stop time period and the instantaneous wind at other times are weighted averaged according to the formula described in S4 corresponding to the corrected weight coefficients, and finally the average wind calculation result is obtained.

[0046] (III) Beneficial effects

[0047] The method for calculating the average wind speed under a high-precision moving platform provided by the above technical solution has the following beneficial effects:

[0048] (1) High precision. In view of the difference between the moving platform and the fixed platform, the present invention introduces a weight coefficient in the process of calculating the average wind. Instead of performing a single average calculation on all instantaneous data, the average wind calculation error caused by the change in spatial position can be reduced to a certain extent, thereby improving the accuracy of the average wind calculation result of the laser wind radar under the moving platform.

[0049] (2) Adaptation. The present invention adaptively selects the calculation method of the weight coefficient according to the characteristics of the moving platform, and selects the optimal weight coefficient for calculation by judging the posture information of the moving platform itself, thereby further improving the accuracy of the calculation result. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a flow chart of weight coefficient selection involved in the present invention.

[0051] Figure 2 This is a weighted average calculation flow chart involved in the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, content and advantages of the present invention more clear, the specific implementation methods of the present invention are further described in detail below in conjunction with the drawings and examples.

[0053] See also Figure 1 and Figure 2 The method for calculating the average wind speed under the high-precision moving platform of this embodiment includes the following steps:

[0054] S1: Determine the platform motion state through the platform posture information.

[0055] Obtain the platform attitude information within the time range to be calculated, including the platform's heading, speed, and the platform's own longitude and latitude. According to the changes in the platform attitude within the set time range, determine whether the platform is performing linear motion within the current calculation time range. Among them, small angle adjustments in the platform's motion direction are still counted as linear motion, such as lane changes by the vehicle-mounted platform.

[0056] Design calculation time range T, platform movement speed (V E , V N , V S ) is the northeast celestial velocity of the platform, and the platform heading angle A H , platform pitch angle A P , the condition for judging whether it is linear motion is:

[0057]

[0058] Among them, THA H , THA P Set thresholds for heading angle and pitch angle respectively; ΔA His the change in platform heading angle within time T, ΔA P is the change in the platform pitch angle within the time T.

[0059] S2: According to the platform motion state, determine the selection method of the weight coefficient and select relative distance or relative time as the weight coefficient.

[0060] If the platform moves in a straight line, the platform movement distance corresponding to each instantaneous wind is selected as the calculation weight. If the platform moves in other movements other than straight line motion, the relative moment corresponding to each instantaneous wind is selected as the calculation weight.

[0061] If the platform moves in a straight line, the weight coefficient is calculated according to the platform moving distance. It is designed that there are N groups of instantaneous wind data within the time T, and the total distance moved within the time T is L. The platform moving distances corresponding to each group of instantaneous wind data are L1, L2, L3, ... L N ,in:

[0062] L=L1+L2+L3+…+L N

[0063] The corresponding weights are:

[0064]

[0065] If the platform is in non-linear motion, the weight coefficient is calculated according to the time corresponding to each group of instantaneous wind. There are N groups of instantaneous wind data in the design calculation time T, and the time interval corresponding to each group of instantaneous wind data is T1, T2, T3, ...T N ,in:

[0066] T=T1+T2+T3+…+T N

[0067] The corresponding weights are:

[0068]

[0069] S3: Based on the platform posture information, determine whether the platform has stopped moving within the calculation time range.

[0070] According to the present invention, after selecting the weight coefficient according to the platform motion state, it is necessary to determine whether the platform is in a stopped state within the time period based on the platform posture information within the calculation time range, such as the moving platform's own speed, and if so, go to step S6, otherwise go to step S5.

[0071] The judgment conditions for the platform stop status are:

[0072]

[0073] S4: The platform keeps moving within the calculation time range, and the weighted average wind is calculated.

[0074] If the platform is in motion during this time period, all instantaneous wind data within the time range are weighted averaged according to the calculated weight coefficient to finally obtain the average wind result; the instantaneous wind speed of each group is V1, V2, V3, ... V N , the instantaneous wind direction is A1, A2, A3, ...A N , then the components u and v projected onto the x-axis and y-axis are:

[0075]

[0076] Calculate the u and v components corresponding to the average wind:

[0077]

[0078] Then the horizontal wind speed V H and the horizontal wind direction α is:

[0079]

[0080] And in trigonometric coordinates, the angle value α calculated directly by the inverse tangent function is not the wind direction angle value in meteorology, and the following conversion is required:

[0081] when hour,

[0082] when hour,

[0083] α 气象 It is the horizontal wind direction angle value in meteorology.

[0084] S5: If the platform stops moving within the calculation time range, the average wind in the stopped state is calculated first. If the platform stops midway during this time period, the traditional vector average calculation method is used to calculate the average wind in the stopped time period. There are M groups of instantaneous wind data in this time period. The average wind V in this time period is T The corresponding u T 、v T Serving size:

[0085]

[0086] S6: According to the platform stop time, the selected weight coefficient is corrected, and after the correction is completed, the average wind speed in the entire time range is calculated.

[0087] After the calculation is completed, the weight coefficient is revised according to the time when the platform stops. If the relative distance is selected as the weight coefficient, the distance corresponding to the instantaneous wind before stopping is used as V T If time is selected as the weight coefficient, then the total time corresponding to the M group of data is used as V T The weight is corrected; finally, the average wind in the stop time period and the instantaneous wind at other times are weighted averaged according to the formula described in S4 corresponding to the corrected weight coefficients, and finally the average wind calculation result is obtained.

[0088] The calculation method provided by the present invention can overcome the problem that the instantaneous wind measured by the moving platform laser wind measuring radar does not correspond to the same spatial area, and improve the calculation accuracy of the average wind of the wind measuring radar.

[0089] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for calculating the average wind under a high-precision moving platform, characterized in that: The following steps are involved: S1: Determine the platform motion state through the platform posture information; S2: According to the platform motion state, determine the selection method of the weight coefficient and select relative distance or relative time as the weight coefficient; S3: judging whether the platform has stopped moving within the calculation time range according to the platform posture information, if yes, go to step S5, otherwise go to step S4; S4: The platform keeps moving within the calculation time range, and the weighted average wind is calculated; S5: If the platform stops moving within the calculation time range, the average wind in the stopped state is calculated first; S6: According to the platform stop time, the selected weight coefficient is corrected, and after the correction is completed, the average wind speed in the entire time range is calculated.

2. The method for calculating average wind speed under a high-precision moving platform according to claim 1, characterized in that: In step S1, the platform attitude information within the time range to be calculated is obtained, including the platform movement heading, movement speed, and the platform's own longitude and latitude. According to the change of the platform attitude within the set time range, it is determined whether the platform is performing linear motion within the current calculation time range.

3. The method for calculating average wind speed under a high-precision moving platform according to claim 2, characterized in that: In step S1, the time range T and platform movement speed (V E , V N , V S ) is the northeast celestial velocity of the platform, and the platform heading angle A H , platform pitch angle A P , the condition for judging whether it is linear motion is: Among them, THA H , THA P Set thresholds for heading angle and pitch angle respectively; ΔA H is the change in platform heading angle within time T, ΔA P is the change in the platform pitch angle within the time T.

4. The method for calculating average wind speed under a high-precision moving platform according to claim 3, characterized in that: In step S2, if the platform is moving in a straight line, the platform movement distance corresponding to each instantaneous wind is selected as the calculation weight; if the platform is moving in other movements other than straight line, the relative time corresponding to each instantaneous wind is selected as the calculation weight.

5. The method for calculating average wind speed under a high-precision moving platform according to claim 4, characterized in that: In step S2, if the platform moves in a straight line, the weight coefficient is calculated according to the platform moving distance. It is designed that there are N groups of instantaneous wind data within the time T, and the total distance moved within the time T is L. The platform moving distances corresponding to each group of instantaneous wind data are L1, L2, L3, ... L respectively. N ,in: <h2 style=";text-align:left;direction:ltr">L = L1 + L2 + L3 +… + L<h2 style=";text-align:left;direction:ltr"> N The corresponding weights are:

6. The method for calculating average wind speed under a high-precision moving platform according to claim 5, characterized in that: In step S2, if the platform is in non-linear motion, the weight coefficient is calculated according to the time corresponding to each group of instantaneous wind. It is designed that there are N groups of instantaneous wind data within the time T, and the time interval corresponding to each group of instantaneous wind data is T1, T2, T3, ...T N ,in: T=T1+T2+T3+…+T N The corresponding weights are:

7. The method for calculating average wind speed under a high-precision moving platform according to claim 6, characterized in that: In step S3, after selecting the weight coefficient according to the platform motion state, the platform posture information within the calculation time range is used to determine whether the platform is in a stopped state within the time period. The judgment condition for the platform stopped state is:

8. The method for calculating average wind speed under a high-precision moving platform according to claim 7, characterized in that: In step S4, when the weighted average wind is calculated, all instantaneous wind data within the time range are weighted averaged according to the calculated weight coefficient, and finally the average wind result is obtained; the average wind result calculation process is: The instantaneous wind speed of each group is V1, V2, V3, ... V N , the instantaneous wind direction is A1, A2, A3, ...A N , then the components u and v projected onto the x-axis and y-axis are: Calculate the u and v components corresponding to the average wind: Then the horizontal wind speed V H and the horizontal wind direction α is: The angle value α is converted as follows: when hour, when hour, α 气象 It is the horizontal wind direction angle value in meteorology.

9. The method for calculating average wind speed under a high-precision moving platform according to claim 6, characterized in that: In step S5, if the platform stops moving within the calculation time range, the average wind speed during the stop time period is calculated. There are M groups of instantaneous wind data in this time period. The average wind speed V in this time period is calculated. T The corresponding u T 、v T Serving size:

10. The method for calculating average wind speed under a high-precision moving platform according to claim 9, characterized in that: In step S6, after the calculation is completed, the weight coefficient is corrected according to the time when the platform stops. If the relative distance is selected as the weight coefficient, the distance corresponding to the instantaneous wind before the stop is used as V T If time is selected as the weight coefficient, then the total time corresponding to the M group of data is used as V T The weight is corrected; finally, the average wind in the stop time period and the instantaneous wind at other times are weighted averaged according to the formula described in S4 corresponding to the corrected weight coefficients, and finally the average wind calculation result is obtained.

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