CN103809220A

CN103809220A - Low-level wind determining method

Info

Publication number: CN103809220A
Application number: CN201410069916.2A
Authority: CN
Inventors: 周率; 刘荟萃; 李黎; 陈定辉; 王镓; 史荟燕; 师明; 李勰; 曹建峰; 韩松涛
Original assignee: Beijing Aerospace Control Center
Current assignee: Beijing Aerospace Control Center
Priority date: 2014-02-28
Filing date: 2014-02-28
Publication date: 2014-05-21
Anticipated expiration: 2034-02-28
Also published as: CN103809220B

Abstract

The invention belongs to the technical field of atmospheric sciences and discloses a low-level wind determining method. The low-level wind determining method includes: laying low-level wind fields according to observation data characteristics through statistically analyzing low-level wind data provided by different observation stations, using an interpolation method for the layer lack of the low-level wind observation value to obtain the unmeasured data; when the layers of the low-level wind observation values of different observation stations are overlapped, correcting the low-level wind data of the overlapped layers, building continuous wind fields, and using a regression method to construct a low-level wind computing equation to obtain the low-level wind data. The low-level wind determining method guarantees the low-level wind solving accuracy and provides the technical support for the return of manned spacecrafts and other space flight and aviation activities.

Description

Low-altitude wind determination method

Technical Field

The invention belongs to the technical field of meteorology, and relates to a low-altitude wind determination method.

Background

The low-altitude wind in the range of 10-3000 m has important influence on the flight trajectory of manned spacecraft and the orbit of low-altitude aircrafts such as return satellites, missiles, airplanes and the like, and is a key meteorological element for precise orbit determination and orbit prediction.

At present, wind measuring towers and wind profile radars are built in space mission field areas such as launching fields and landing fields, and meteorological sites such as airports, and are two main devices for detecting low-altitude wind, but the detection heights, the detection accuracies, the data densities and the like of the two devices are different. The wind measuring tower measures a wind field with the distance of 100m below the ground, the measured heights are 5 layers including 10m, 25m, 50m, 75m and 100m, the measurement precision is 0.1m/s, and the measurement density is 1 minute; the wind profile radar can detect a wind field of 80-3253 m, the detected vertical layering is not less than 25 layers, the measurement precision is 1m/s, and the measurement density is 15 minutes; the two data are overlapped only in the vicinity of 100m in vertical height. Therefore, in the low-altitude wind guarantee, how to calculate the low-altitude wind by comprehensively utilizing the two different sources is a calculation problem. For example, in manned space engineering, the trajectory of the spacecraft, particularly the orbit during return, needs to be calculated to provide accurate low-altitude wind vector data, including low-altitude wind direction and wind speed. Therefore, the problem of how to match the anemometer tower with the wind profile radar data and calculate the low-altitude wind vector is solved.

In conventional low-altitude wind vector calculation, a linear interpolation method is conventionally used, in which wind tower data is used for low-altitude wind of 100m or less and wind profile radar data is used for low-altitude wind of 100m or more, based on wind tower and wind profile radar detection data. Because the detection height of the wind profile radar is not constant and the data lack is more, the calculation of a wind vector at a certain height by adopting a linear interpolation method can cause obvious errors; especially when there is a large difference between the two detection data at a height of 100m, it is difficult to provide an accurate low-altitude wind calculation result.

Disclosure of Invention

The invention aims to provide an accurate low-altitude wind calculation method to improve the flight trajectory determination and forecast accuracy of low-altitude aircrafts such as manned airships and the like.

In order to achieve the purpose, the low-altitude wind calculation method provided by the invention comprises the following steps:

step one, establishing a continuous low-altitude wind field

And (3) statistically analyzing low-altitude wind data provided by different observation stations, layering the low-altitude wind field according to the characteristics of the observation data, and solving the missing data of the layer missing the low-altitude wind observation value by adopting an interpolation method. And when the layers of the low-altitude wind observation values of different observation stations are overlapped, correcting and matching the low-altitude wind data of the overlapped layers. The method comprises the following specific steps:

1.1, low altitude wind field stratification

And (4) carrying out statistical analysis on low-altitude wind data provided by different observation stations, and layering the low-altitude wind field according to the characteristics of the observation data. The number of layers is proportional to the density and accuracy of the observed data, and the lower the height, the more dense the layers.

1.2 solving the lack-of-measurement data of the lack-of-measurement layer by adopting an interpolation method

According to the low-altitude wind observed values of the two heights between the height of the lacking measurement layer and the height difference of the lacking measurement layer, the lacking measurement data of the lacking measurement layer is solved by adopting an interpolation method, which specifically comprises the following steps:

if the low-altitude wind observed values of the two heights with the minimum height difference from the lacking detection layer are respectively positioned below and above the height of the lacking detection layer, the lacking detection low-altitude wind speed V of the layer_s0Wind direction V_x0Respectively as follows:

if the low-altitude wind observed values of the two heights with the minimum height difference from the lacking detection layer are both positioned below the height of the lacking detection layer, the lacking detection low-altitude wind speed V of the layer_s0Wind direction V_x0Respectively as follows:

if the low-altitude wind observed values at the two heights with the minimum height difference from the lacking detection layer are both positioned above the height of the lacking detection layer, the lacking detection low-altitude wind speed of the layerDegree V_s0Wind direction V_x0Respectively as follows:

wherein, V_s1、V_s2Low altitude wind speeds, Z, of two heights having the smallest difference in height from the missing measurement layer₁、Z₂Respectively two heights, Z, with the smallest difference in height from the missing measurement layer₀The height from the lacking detection layer is measured; v_x1、V_x2The two low-altitude wind directions with the minimum height difference from the lack detection layer are respectively.

1.3, acquiring the low-altitude wind speed and wind direction of the overlapped layer of low-altitude wind observation values of different observation stations

And performing low-altitude wind data correction on the overlapped layers of the low-altitude wind observation values of different observation stations to obtain the low-altitude wind speed and wind direction of the overlapped layers of the low-altitude wind observation values of different observation stations.

Correcting and matching the low-altitude wind speed of the overlapped layer of the low-altitude wind observation values of different observation stations as follows:

wherein, V_v-orderFor the low-altitude wind speed, V, of the overlapped layer after the pitch matching_{v measurement}The wind speed of the low-altitude wind with lower precision is measured,

is the difference of the annual average value of the low-altitude wind speed of different observation stations at the height of the overlapped layer,

the low-altitude wind speed with lower precision is at the height of the overlapped layerThe average value of the whole year,

the average value of the wind speed of the low-altitude wind with higher precision in the height of the overlapped layer all the year round.

Correcting and matching the wind directions of the low-altitude wind observed values of different observation stations in the overlapped layers as follows:

wherein, V_{d order}Correcting matched low-altitude wind direction, V, of overlapped layer_{d measurement}The wind direction of the low-altitude wind with lower precision is measured,is the difference of the annual average value of the low-altitude wind directions of different observation stations at the height of the superposed layer,

is the perennial average value of the low-altitude wind direction with lower precision at the height of the overlapped layer,

the average value of the wind direction of the low-altitude wind with higher precision in the height of the overlapped layer is the perennial average value.

Step two, solving low-altitude wind

And according to the established low-altitude wind field, establishing a regression equation to solve the low-altitude wind through deviation statistical analysis on the error between the calculated value and the measured value of the low-altitude wind of each layer.

Solving low-altitude wind direction

With wind speedThe details are as follows：

\hat{y_{d}} = a_{0} + a_{1} V_{d}

{\hat{y}}_{v} = b_{0} + b_{1} V_{v} + b_{2} {V_{v}}^{2}

Wherein,

for the solved low-altitude wind direction value, V_dThe low-altitude wind direction value, a, of the corresponding layer in the continuous low-altitude wind field established for the step one₀、a₁Is a regression coefficient of a unary linear regression equation₀And a₁Determining by using a least square method according to the historical observed value of the low-altitude wind direction of the corresponding layer and the corresponding historical calculated value;

for the value of the low-altitude wind speed, V, to be solved_vThe low-altitude wind speed value of the corresponding layer in the continuous low-altitude wind field established for the step one, b₀、b₁、b₂Is the regression coefficient of the regression equation, b₀、b₁、b₂And determining by using a least square method according to the historical observed value of the low-altitude wind speed of the corresponding layer and the corresponding historical calculated value.

The invention has the beneficial technical effects that:

according to the low-altitude wind data provided by different observation stations, the continuous low-altitude wind field is established, and an equation for solving the low-altitude wind is determined by adopting a regression method. The method achieves the purpose of comprehensively utilizing the low-altitude wind data provided by different observation stations with different detection heights, frequencies, densities and precisions, and ensures the solving precision of the low-altitude wind. The method has important application value in precise orbit determination of low-altitude aircrafts such as manned spaceships, missiles, airplanes and the like. The invention provides an important technical support in the important aerospace activities such as the return of manned spacecrafts to a drop point determination in China.

Drawings

FIG. 1 is a flow chart of a low altitude wind determination method of the present invention. 00:00: 31-03: 30:33, as follows: 18:45: 27-23: 15:35

FIG. 2 is a two-dimensional wind field map of low altitude wind detection data for a time period of 00:00: 31-03: 30: 33.

FIG. 3 is a two-dimensional wind field map of time period 00:00: 31-03: 30:33 after the low-altitude wind detection data is filled up by the method.

FIG. 4 is a two-dimensional wind field plot of low altitude wind detection data for time periods 18:45: 27-23: 15: 35.

FIG. 5 is a two-dimensional wind field diagram of time periods 18:45: 27-23: 15:35 after low-altitude wind detection data are supplemented by the method.

FIG. 6 is a comparison graph of the low-altitude wind calculated by the present invention and the low-altitude wind accuracy calculated by the linear interpolation method.

Detailed Description

The present invention will be further described with reference to the accompanying drawings, taking the determination of the one-time manned space mission return orbit as an example. As shown in fig. 1, the low-altitude wind determination method of the present invention includes the following steps:

step one, establishing a continuous low-altitude wind field

And (3) statistically analyzing low-altitude wind data provided by different observation stations, layering the low-altitude wind field according to the characteristics of the observation data, and solving the missing data of the layer missing the low-altitude wind observation value by adopting an interpolation method. And when the layers of the low-altitude wind observation values of different observation stations are overlapped, correcting the low-altitude wind data of the overlapped layers. The method comprises the following specific steps:

1.1, low altitude wind field stratification

For example: low-altitude wind data observed by wind measuring tower and profile radar through contrastive analysis

The anemometer tower detects 5 layers of wind fields of 10m, 25m, 50m, 75m and 100m, the measurement precision is 0.1m/s, and the measurement density is 1 minute; the wind profile radar detects and inverts a wind field of 80-3253 m, the vertical layering is not less than 25 layers, the measurement precision is 1m/s, and the measurement density is 15 minutes; there is an overlap of the two data only around a height of 100 m. The accuracy, density, continuity and stability of the anemometer tower data are superior to those of wind profile radar data. According to the measurement density, the data accuracy and the requirement of the manned spacecraft for returning to the track calculation, low-altitude wind below 3000m is layered into 20 layers, wherein the height below 100m is divided into 5 layers of 10m, 25m, 50m, 75m and 100m according to the detection height of a wind measuring tower; the interval of 100m to 300m is 50m, and the layer is divided into 4 layers (150m, 200m, 250m and 300 m); the height interval of 300 m-1000 m is 100m, and the film is divided into 7 layers (400m, 500m, 600m, 700m, 800m, 900m and 1000 m); the height of 1000 m-3000 m is 500m, and the film is divided into 4 layers (1500m, 2000m, 2500m, 3000 m). Through layering, basic low-altitude wind data of each height can be obtained.

if the low-altitude wind observed values of the two heights with the minimum height difference from the lacking detection layer are both positioned above the height of the lacking detection layer, the lacking detection low-altitude wind speed V of the layer_s0Wind direction V_x0Respectively as follows:

Two-dimensional wind fields before and after the method is adopted to solve the missing measurement data of the missing measurement layer in two detection periods (upper: 00:00: 31-03: 30:33, lower: 18:45: 27-23: 15:35) of 25 days in 6 months in 2013 are shown in fig. 2, 3, 4 and 5.

1.3, correcting the low-altitude wind speed and wind direction of the overlapped layer of low-altitude wind observed values of different observation stations

And correcting low-altitude wind data of the overlapped layers of the low-altitude wind observation values of different observation stations to obtain the low-altitude wind speed and wind direction of the overlapped layers of the low-altitude wind observation values of different observation stations.

The low-altitude wind speed of the overlapped layer of the low-altitude wind observation values of different observation stations is corrected as follows:

wherein, V_v-orderFor corrected low-altitude wind speed, V, of the overlapping layer_{v measurement}The wind speed of the low-altitude wind with lower precision is measured,is the difference of the annual average value of the low-altitude wind speed of different observation stations at the height of the overlapped layer,

the wind speed of low-altitude wind with lower precision is overlappedThe average value of the layer height over the year,

The low-altitude wind direction of the overlapped layer of the low-altitude wind observation values of different observation stations is corrected as follows:

wherein, V_{d order}Corrected low-altitude wind direction, V, of the overlapped layer_{d measurement}The wind direction of the low-altitude wind with lower precision is measured,

is the difference of the annual average value of the low-altitude wind directions of different observation stations at the height of the superposed layer,

Step two, solving low-altitude wind

Solving low-altitude wind direction

With wind speed

The method comprises the following specific steps:

\hat{y_{d}} = a_{0} + a_{1} V_{d}

{\hat{y}}_{v} = b_{0} + b_{1} V_{v} + b_{2} {V_{v}}^{2}

wherein,

for the solved low-altitude wind direction value, V_dThe low-altitude wind direction value, a, of the corresponding layer in the continuous low-altitude wind field established for the step one₀、a₁Is a regression coefficient of a unary linear regression equation₀And a₁Determining by using a least square method according to the historical observed value of the low-altitude wind direction of the corresponding layer and the corresponding historical calculated value;for the value of the low-altitude wind speed, V, to be solved_vThe low-altitude wind speed value of the corresponding layer in the continuous low-altitude wind field established for the step one, b₀、b₁、b₂Is the regression coefficient of the regression equation, b₀、b₁、b₂And determining by using a least square method according to the historical observed value of the low-altitude wind speed of the corresponding layer and the corresponding historical calculated value.

By utilizing the method of the invention, the low-altitude wind vector before the manned spacecraft returns is quantitatively calculated by comprehensively utilizing the low-altitude wind data of the anemometer tower and the low-altitude wind data of the wind profile radar, and the calculated low-altitude wind direction in 6 months is obtainedWith wind speed

The regression equation of (a) is as follows:

\hat{y_{d}} = 61.34 + 0.72 x_{d}

{\hat{y}}_{v} = 2.23 + 0.56 x_{v} + 0.01 {x_{v}}^{2}

wherein,

calculated value of low-altitude wind direction, x_dThe observed value of the low-altitude wind direction is obtained;

is at low altitudeCalculated value of wind speed, x_vThe observed value of the low-altitude wind speed is obtained.

And the accuracy of the low-altitude wind calculated by the method in 2013, 6, 25 and 25 is compared with the accuracy of the low-altitude wind calculated by the linear interpolation method, as shown in fig. 6, the low-altitude wind calculated by the method is obviously closer to actually measured low-altitude wind data, and the calculation accuracy of the low-altitude wind vector is remarkably improved.

Claims

1. A low-altitude wind determination method is characterized by comprising the following steps: the method comprises the following steps:

step one, establishing a continuous low-altitude wind field

The method comprises the steps of statistically analyzing low-altitude wind data provided by different observation stations, layering a low-altitude wind field according to observation data characteristics, solving missing data for layers lacking low-altitude wind observation values, and correcting the low-altitude wind data of a re-laminated layer when the layers of the low-altitude wind observation values of the different observation stations are overlapped;

step two, solving low-altitude wind

Solving low-altitude windWind direction

With wind speed

The method comprises the following specific steps:

\hat{y_{d}} = a_{0} + a_{1} V_{d}

{\hat{y}}_{v} = b_{0} + b_{1} V_{v} + b_{2} {V_{v}}^{2}

wherein, V_dThe low-altitude wind direction value, a, of the corresponding layer in the continuous low-altitude wind field established for the step one₀、a₁Is a regression coefficient of a unary linear regression equation₀And a₁Determining by using a least square method according to the historical observed value of the low-altitude wind direction of the corresponding layer and the corresponding historical calculated value; v_vThe low-altitude wind speed value of the corresponding layer in the continuous low-altitude wind field established for the step one, b₀、b₁、b₂Is the regression coefficient of the regression equation, b₀、b₁、b₂According to the historical observed value of the low-altitude wind speed of the corresponding layer and the corresponding history thereofCalculated values, determined using the least squares method.

2. The low altitude wind determination method according to claim 1, wherein: in the first step, the layer missing the low-altitude wind observation value is subjected to interpolation to solve missing data.

3. The low altitude wind determination method according to claim 1 or 2, characterized in that: the method for solving the defect data of the defect layer by adopting the interpolation method specifically comprises the following steps:

4. The low altitude wind determination method according to claim 1, wherein: in the first step, the low-altitude wind data of the overlapped layers of the low-altitude wind observation values of different observation stations are corrected as follows:

wherein, V_v-orderFor corrected low-altitude wind speed, V, of the overlapping layer_{v measurement}The wind speed of the low-altitude wind with lower precision is measured,

is the perennial average value of the low-altitude wind speed with lower precision in the height of the overlapped layer,

the average value of the low-altitude wind speed with higher precision in the height of the overlapped layer all year round;

is the perennial average value of the low-altitude wind direction with lower precision at the height of the overlapped layer,the average value of the wind direction of the low-altitude wind with higher precision in the height of the overlapped layer is the perennial average value.