A method for calculating mean wind under a high-precision dynamic platform

Abstract

This invention discloses a method for calculating the average wind under a high-precision moving platform, comprising the following steps: S1: Determine the platform's motion state based on the platform's attitude information; S2: Determine the selection method for weighting coefficients based on the platform's motion state, selecting relative distance or relative time as the weighting coefficients; S3: Determine whether the platform has stopped moving within the calculation time range based on the platform's attitude information; if so, proceed to step S5; otherwise, proceed to step S4; S4: If the platform remains in motion throughout the calculation time range, calculate the average wind using weighted averages; S5: If the platform has stopped moving within the calculation time range, first calculate the average wind under the stopped state; S6: Correct the selected weighting coefficients based on the platform's stopping time, and then calculate the average wind over the entire time range. This invention overcomes the problem that instantaneous wind measured by a moving platform laser wind radar does not correspond to the same spatial region, thus improving the calculation accuracy of the average wind from the wind radar.

Description

Technical Field

[0001] This invention belongs to the field of wind field information calculation technology, and relates to a method for calculating the average wind under a high-precision dynamic platform. Background Technology

[0002] Acquiring wind field information is a major task in meteorology, aerodynamics, and other fields, and the accuracy of the measurement data is particularly important for meteorological research. Traditional wind field measurement methods mainly include radiosondes, cup anemometers, ultrasonic anemometers, and wind profiler radars, but most of them suffer from limitations in installation location, low measurement accuracy, and small measurement range. In recent years, with the development of laser technology, laser wind radar, with its high measurement accuracy, fast scanning speed, and convenient installation, has gradually become one of the important means of wind field remote sensing.

[0003] Laser wind-measuring radar, as an important means of remotely measuring wind fields, can acquire wind field information within a certain spatial range, including wind speed, wind direction, and vertical airflow. It can be installed near airport runways to monitor real-time wind field changes above the runways. In recent years, with the continuous development of radar technology, laser wind-measuring radar has gradually been developed and applied on various dynamic platforms. For example, it is used on meteorological observation vehicles to acquire wind field information at different geographical locations, on ships to acquire three-dimensional wind field information around ships, and on airborne laser wind-measuring radar to acquire wind profile information below aircraft.

[0004] For wind-measuring radars installed on fixed platforms, their measurement range is relatively fixed, capable of measuring wind field information in the spatial area surrounding the radar installation location. The instantaneous wind measured by the radar in real time, due to its relatively rapid dynamic fluctuations, is not highly representative. Therefore, in the secondary processing and calculation of its measurement data, the average wind over a certain time range can be obtained by vector averaging the instantaneous wind, including average wind speed and average wind direction, to reflect the wind field changes in the airspace near the radar installation location.

[0005] For wind-measuring radars operating on moving platforms, the instantaneous data measured by the radar at different times correspond to wind field information in different spatial regions because the radar itself moves with the platform. If the traditional vector averaging method is still used to calculate the average wind, the calculated result cannot fully represent the wind field state of the area where the radar is located at the time of calculation. In addition, existing technologies often struggle to adapt to complex dynamic changes and the combined influence of multiple elements, and the accuracy of the calculation still needs to be improved. Summary of the Invention

[0006] (I) Purpose of the Invention

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

[0008] (II) Technical Solution

[0009] To address the aforementioned technical problems, this invention provides a method for calculating the average wind under a high-precision dynamic platform, comprising the following steps:

[0010] S1: Determine the platform's motion state based on the platform's attitude information;

[0011] S2: Based on the platform's motion state, determine the selection method for the weighting coefficient and choose relative distance or relative time as the weighting coefficient;

[0012] S3: Based on the platform attitude information, determine whether the platform has stopped moving within the calculation time range. If yes, proceed to step S5; otherwise, proceed to step S4.

[0013] S4: The platform remains in motion throughout the calculation timeframe, and the weighted average wind is calculated.

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

[0015] S6: Adjust the selected weighting coefficients based on the platform stop time, and calculate the average wind over the entire time range after adjustment.

[0016] In step S1, the platform attitude information within the time range to be calculated is obtained, including the platform's heading, speed, and latitude and longitude. Based on the changes in the platform attitude within the set time range, it is determined whether the platform is moving in a straight line within the current calculation time range.

[0017] In step S1, the time range T is calculated, and the platform's motion speed (V) is... E V N V S (A) represents the platform's northeast-facing velocity, and the platform's heading angle A. H Platform pitch angle A P The condition for determining whether the motion is linear is:

[0018]

[0019] Among them, THA H THA P Set threshold values ​​for the heading angle and pitch angle respectively; ΔA H Let ΔA be the change in the platform's heading angle over time T. P Let T be the change in the platform's pitch angle over 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 ways besides in a 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 weighting coefficient is calculated based on the platform's movement distance. It is designed that there are N sets of instantaneous wind data within time T, and the total distance traveled within time T is L. The platform movement distance corresponding to each set of instantaneous wind data is L1, L2, L3, ... L. N ,in:

[0022] L = L1 + L2 + L3 + ... + L N

[0023] The corresponding weights are as follows:

[0024]

[0025] In step S2, if the platform is in non-linear motion, the weighting coefficient is calculated based on the time corresponding to each group of instantaneous winds. There are N groups of instantaneous wind data within the calculation time T, with each group corresponding to a time interval of T1, T2, T3, ... T. N ,in:

[0026] T = T1 + T2 + T3 + ... + T N

[0027] The corresponding weights are as follows:

[0028]

[0029] In step S3, after selecting the weighting coefficients based on the platform's motion state, the system determines whether the platform is in a stopped state within the calculated time range based on the platform's attitude information. The criteria for determining whether the platform is in a stopped state are as follows:

[0030]

[0031] In step S4, when calculating the weighted average wind, the weighted average of all instantaneous wind data within the time range is calculated based on the weighted coefficients obtained, and the final average wind result is obtained.

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

[0033] The instantaneous wind speeds for each group are 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 mean wind:

[0036]

[0037] So the horizontal wind speed V H The horizontal wind direction α is:

[0038]

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

[0040] when hour,

[0041] when hour,

[0042] α 气象 This refers to the horizontal wind direction angle in meteorology.

[0043] In step S5, if the platform stops moving within the calculation time range, firstly, the average wind during the stop time period is considered. There are M sets of instantaneous wind data during this time period, and the average wind V during this time period is... T The corresponding u T v T The components are:

[0044]

[0045] In step S6, after the calculation is completed, the weighting coefficients are readjusted based on the platform's stopping time. If the relative distance has already been selected as the weighting coefficient, then the distance corresponding to the instantaneous wind at the moment before stopping is taken as V. T The weights are adjusted accordingly; if time has already been selected as the weight coefficient, then all times corresponding to the M sets of data are used as V. T The weights are adjusted; finally, the average wind during the stop time period and the instantaneous wind at other times are weighted and averaged according to the formula described in S4 to obtain the final average wind calculation result.

[0046] (III) Beneficial Effects

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

[0048] (1) High accuracy. This invention introduces a weighting coefficient in the process of calculating the average wind, taking into account the differences between the moving platform and the fixed platform. Instead of simply averaging all instantaneous data, it can reduce the error in the average wind calculation caused by changes in spatial location to a certain extent and improve the accuracy of the average wind calculation results of the laser wind radar on the moving platform.

[0049] (2) Adaptive. In view of the characteristics of the moving platform, the present invention adaptively selects the calculation method of the weight coefficient. By judging the attitude information of the moving platform itself, the optimal weight coefficient is selected for calculation, thereby further improving the accuracy of the calculation results. Attached Figure Description

[0050] Figure 1 This is a flowchart of the weight coefficient selection process involved in this invention.

[0051] Figure 2 This is a flowchart of the weighted average calculation involved in this invention. Detailed Implementation

[0052] To make the objectives, contents, and advantages of the present invention clearer, the specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples.

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

[0054] S1: Determine the platform's motion state based on the platform's attitude information.

[0055] The system acquires platform attitude information within the time range to be calculated, including platform heading, speed, and latitude and longitude. Based on the changes in platform attitude within the set time range, it determines whether the platform is moving in a straight line within the current calculation time range. Small-amplitude angular adjustments in the platform's direction of motion are still considered as straight-line motion, such as lane changes by a vehicle platform.

[0056] The design calculation time range is T, and the platform's motion speed (V) is... E V N V S (A) represents the platform's northeast-facing velocity, and the platform's heading angle A. H Platform pitch angle A P The condition for determining whether the motion is linear is:

[0057]

[0058] Among them, THA H THA P Set threshold values ​​for the heading angle and pitch angle respectively; ΔA HLet ΔA be the change in the platform's heading angle over time T. P Let T be the change in the platform's pitch angle over time T.

[0059] S2: Based on the platform's motion state, determine the selection method for the weighting coefficients and choose relative distance or relative time as the weighting coefficients.

[0060] If the platform is moving in a straight line, the distance the platform moves corresponding to each instantaneous wind is selected as the calculation weight. If the platform is moving in other ways besides straight line motion, the relative time corresponding to each instantaneous wind is selected as the calculation weight.

[0061] If the platform moves in a straight line, the weighting coefficient is calculated based on the platform's movement distance. The design assumes there are N sets of instantaneous wind data within time T, and the total distance traveled within time T is L. The platform movement distance corresponding to each set of instantaneous wind data is L1, L2, L3, ... L. N ,in:

[0062] L = L1 + L2 + L3 + ... + L N

[0063] The corresponding weights are as follows:

[0064]

[0065] If the platform is in non-linear motion, the weighting coefficient is calculated based on the time corresponding to each group of instantaneous winds. There are N groups of instantaneous wind data within the calculation time T, with each group corresponding to a time interval of T1, T2, T3, ... T. N ,in:

[0066] T = T1 + T2 + T3 + ... + T N

[0067] The corresponding weights are as follows:

[0068]

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

[0070] According to the present invention, after selecting the weighting coefficient based on 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 attitude information within the calculation time range, such as the platform's own speed. If so, proceed to step S6; otherwise, proceed to step S5.

[0071] The conditions for determining the platform's stopped state are as follows:

[0072]

[0073] S4: The platform remains in motion throughout the calculation timeframe, and the weighted average wind is calculated.

[0074] If the platform remains in motion throughout this time period, a weighted average is calculated based on the weighted coefficients for all instantaneous wind data within the time frame to obtain the final average wind result; the instantaneous wind speeds for each group are 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 mean wind:

[0077]

[0078] So the horizontal wind speed V H The horizontal wind direction α is:

[0079]

[0080] Furthermore, in triangular coordinates, the angle value α calculated directly from the arctangent function is not the meteorological wind direction angle value, and the following conversion is required:

[0081] when hour,

[0082] when hour,

[0083] α 气象 This refers to the horizontal wind direction angle in meteorology.

[0084] S5: If the platform stops moving within the calculation time range, first calculate the average wind under the stopped state. If the platform stops midway during this time period, then use the traditional vector averaging method to calculate the average wind during the stopped period. There are M sets of instantaneous wind data during this period, and the average wind V during this period is calculated. T The corresponding u T v T The components are:

[0085]

[0086] S6: Adjust the selected weighting coefficients based on the platform stop time, and calculate the average wind over the entire time range after adjustment.

[0087] After the calculation is completed, the weighting coefficients are readjusted based on the platform's stopping time. If relative distance has already been selected as the weighting coefficient, then the distance corresponding to the instantaneous wind at the moment before stopping is taken as V. T The weights are adjusted accordingly; if time has already been selected as the weight coefficient, then all times corresponding to the M sets of data are used as V. T The weights are adjusted; finally, the average wind during the stop time period and the instantaneous wind at other times are weighted and averaged according to the formula described in S4 to obtain the final average wind calculation result.

[0088] The calculation method provided by this invention can overcome the problem that the instantaneous wind measured by the dynamic platform laser wind radar does not correspond to the same spatial area, thus improving the calculation accuracy of the average wind of the wind radar.

[0089] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for calculating the mean wind under a high-precision moving platform, characterized in that, Comprising the following steps: S1: judging the platform motion state through platform attitude information; S2: judging the selection mode of weight coefficient according to the platform motion state, selecting relative distance or relative time as weight coefficient; S3: judging whether the platform exists stop motion condition in the calculation time range according to the platform attitude information, if yes, turning to step S5, otherwise, turning to step S4; S4: the platform keeps moving in the calculation time range, and the weighted average wind is calculated; S5: the platform exists stop motion condition in the calculation time range, and the average wind in the stop state is calculated first; 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.

2. The method of claim 1, wherein the high-precision moving platform mean wind is calculated by: In step S1, the platform attitude information in the calculation time range is obtained, including platform motion heading, motion speed, platform itself latitude and longitude, and whether the platform is in straight line motion in the calculation time range is judged according to the change of platform attitude in the set time range.

3. The method for calculating the average wind under a high-precision moving platform as described in claim 2, characterized in that, In step S1, a time range T is designed, a platform motion speed (V E , V N , V S ) is the northeast sky speed of the platform, a platform heading angle A H , a platform pitch angle A P , and a condition for judging whether it is a straight line motion is determined. Wherein, THA H , THA P are the heading angle and pitch angle setting thresholds respectively; ΔA H is the change in the platform heading angle in time T, and ΔA P is the change in the platform pitch angle in time T.

4. The method for calculating the average wind under a high-precision moving platform as described in claim 3, characterized in that, In step S2, if the platform is in straight line motion, the moving distance of each instantaneous wind corresponding to the platform is selected as the calculation weight, and if the platform is in other motion, the relative time corresponding to each instantaneous wind is selected as the calculation weight.

5. The method for calculating the average wind under a high-precision moving platform as described in claim 4, characterized in that, In step S2, if the platform is in linear motion, the weight coefficient is calculated according to the moving distance of the platform, and N groups of instantaneous wind data in a calculation time T are designed, the total distance of the motion in the time T is L, and the moving distances of the platform corresponding to each group of instantaneous wind data are L1, L2, L3, …, LN respectively. M wherein: L = L1+ L2+ L3+... + L N The respective corresponding weights are:

6. The method for calculating the average wind under a high-precision moving platform as described in claim 5, characterized in that, In step S2, if the platform is not in linear motion, the weight coefficient is calculated according to the time corresponding to each group of instantaneous wind. A total of N groups of instantaneous wind data are designed within the calculation time T, and each group of instantaneous wind data corresponds to a time interval of T1, T2, T3, … T N wherein: T = T1 + T2 + T3 +... + T N The respective corresponding weights are:

7. The method for calculating the average wind under a high-precision moving platform as described in claim 6, characterized in that, In step S3, after the weight coefficient is selected according to the platform motion state, whether the platform exists stop state in the calculation time range is judged according to the platform attitude information in the calculation time range, and the judgment condition of the platform stop state is:

8. The method for calculating the average wind under a high-precision moving platform as described in claim 7, characterized in that, In step S4, when the weighted average wind is calculated, all instantaneous wind data in the time range is weighted and averaged according to the calculated weight coefficient, and the average wind result is finally 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 The components u, v projected to the x-axis and y-axis are: The u, v components corresponding to the calculation of the average wind are: So the horizontal wind speed V H and the horizontal wind direction a are: The angle value α is converted as follows: a 气象 is the meteorological horizontal wind direction angle value.

9. The method for calculating the average wind under a high-precision moving platform as described in claim 6, characterized in that, In step S5, the platform exists the stop motion case in the calculation time range, first stop the average wind in the time period, the time period has M groups of instantaneous wind data, the average wind V T The corresponding u T , v T component is:

10. The method for calculating the average wind under a high-precision moving platform as described in claim 9, characterized in that, In step S6, 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 at the moment before stopping is taken as the weight of V T . If the time is selected as the weight coefficient, the total time corresponding to the M groups of data is taken as the weight of V T . Finally, the average wind in the stopping time period and the instantaneous wind at other times are weighted and averaged according to the revised weight coefficient to obtain the final average wind calculation result.

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