A method and device for extracting vector trajectory information from an elevation terrain scanning area

Abstract

This application provides a method and apparatus for extracting vector trajectory information from an elevation topography scanning area. The method includes: Step 1: Processing the original recorded time-series trajectory / path data to obtain physical quantity data representing changes in trajectory orientation, wherein the physical quantity data includes trajectory data points and trajectory azimuth angles; Step 2: Calculating the gradient of the orientation data based on the physical quantity data, and filtering pre-selected data points that meet the turning change threshold based on the gradient; Step 3: Based on the pre-selected data points, filtering out qualified coordinate points recPos by calculating the axial distance and vertical distance between the vector trajectory and the actual trajectory. i Azimuth and trajectory distance recDis i Step 4: Obtain the coordinates recPos i Azimuth and trajectory distance recDis i For the dataset, recalculate the final track azimuth and final track distance newRecDis. i This yields vector trajectory information.

Description

Technical Field

[0001] This invention relates to the field of flight control technology, specifically to a method and apparatus for extracting vector trajectory information from an elevation terrain scanning area. Background Technology

[0002] When describing a path or track, the required data size increases linearly with the increase in distance and resolution. Especially under the 10ms operation cycle required by flight control, the resources for recording and processing tracks will increase dramatically with the increase in recording time. However, simply reducing the storage resolution will miss some key information, and the method of choosing the storage resolution is neither objective, scientific, nor accurate.

[0003] Most existing open-source high-precision elevation terrain data have a resolution of about 1 arcsecond (approximately 30m). However, an aircraft flying at 100m / s moves about 1m within a 10ms period. Directly interpolating the coordinates of the trajectory points to obtain the elevation data corresponding to the trajectory would consume a lot of computing power and storage space, especially in straight-line motion with little change in azimuth. A two-dimensional trajectory can represent all the data of this trajectory / path using four data points: the starting point coordinates (two dimensions), the azimuth angle, and the displacement distance. This reduces the data size from 2n to 4 (where n represents the number of times the data is recorded).

[0004] However, existing methods for extracting vector trajectory information can only represent straight line segments. When there is curvilinear motion, the method will be distorted, especially when the azimuth changes over distance. Summary of the Invention

[0005] This invention proposes a method and apparatus for extracting vector trajectory information from an elevation topography scanning area. It performs numerical calculations on a large amount of trajectory / path record data, calculates and judges feature points (trajectory / path transformation points) through mathematical methods, and automatically generates a simplified trajectory / path, reducing the data size for storing this information. While ensuring that the trajectory / path is not distorted, it minimizes the data storage size as much as possible.

[0006] Firstly, this application provides a method for extracting vector trajectory information from an elevation topography scanning area, the method comprising:

[0007] Step 1: Process the original time series trajectory / path data to obtain physical quantity data representing the change in trajectory orientation. The physical quantity data includes trajectory data points and trajectory azimuth angles.

[0008] Step 2: Calculate the gradient of the orientation data based on the physical quantity data, and filter the pre-selected data points that meet the turning change threshold according to the gradient;

[0009] Step 3: Based on the pre-selected data points, calculate the axial and vertical distances between the vector trajectory and the actual trajectory to filter out the coordinate points recPos that meet the requirements. i azimuth and trajectory distance recDis i ;

[0010] Step 4: Obtain the coordinates recPos i azimuth and trajectory distance recDis i For the dataset, recalculate the final azimuth angle of the trajectory. Distance from final trajectory to newRecDis i This yields vector trajectory information.

[0011] Furthermore, step 1 includes:

[0012] Step 11: Begin and set the initial state of the parameters;

[0013] Step 12: Read the trajectory data points X = (x1, x2, ... x n Y = (y1, y2, ... y) n ); where X and Y represent the sets of coordinate points in the eastward and northward directions of the trajectory, respectively; x n and y n These are coordinate values ​​for a specific time.

[0014] Step 13: Using trajectory data points X = (x1, x2, ... x n Y = (y1, y2, ... y) n ), calculate trajectory azimuth angle The calculation formula is as follows:

[0015]

[0016] Where Ψ represents the set of trajectory azimuth angles. It is the azimuth angle value of the trajectory at a specific time.

[0017] Furthermore, step 2 includes:

[0018] Step 21: Calculate the trajectory azimuth angle The absolute value of the gradient data Λ=(λ1,λ2,…λ n The calculation formula is as follows:

[0019]

[0020] Where Λ represents the set of absolute values ​​of the trajectory azimuth gradient, and λ n It is the numerical value of the absolute value of the trajectory azimuth gradient at a specific time.

[0021] Step 22: Calculate the absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n The median λ of the gradient data is obtained by sorting the data. median As a threshold for pre-screening data;

[0022] Step 23: Based on the threshold λ median Filter the absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n (in which) greater than λ median Data point ID sele =(id1,…,id m That is, satisfying:

[0023]

[0024] Furthermore, step 3 includes:

[0025] Step 31: Set the vertical deviation threshold ERR V and axial growth step size R A The second data filtering process begins; among which, the vertical deviation threshold ERR is... V and axial growth step size R A The settings can be configured based on the width and distance of the scanned area, and the ERR can be set. V The width of the scan area is less than 1 / 3, R A Less than or equal to the scan distance;

[0026] Step 32: Set the coordinates recPos of pointers i and j for filtering and calculating data point numbers. i azimuth Track Distance recDis i Initial value:

[0027]

[0028] Step 33: Calculate the axial distance r between the data point corresponding to pointer i and the data point corresponding to pointer j. A and vertical deviation err V ;

[0029] Step 34: If the vertical deviation err is satisfied V <ERR V And axial distance r A <recDis i Then update the filter pointer j = j + 1; if the vertical deviation err is satisfied... V <ERR V And axial distance r A >recDisi Then update the record value recDis. i =r A If the vertical deviation err is satisfied V ERR V And axial distance r A <recDis i Then update the coordinate point recPos i azimuth and trajectory distance recDis i ;

[0030] Step 35: Record the trajectory distance recDis i =r A +R A Store coordinate points recPos i azimuth and trajectory distance recDis i ;

[0031] Step 36: If not all pre-selected data has been detected, update the stored coordinate point recPos. i azimuth and trajectory distance recDis i This continues until all pre-selected data has been tested.

[0032] Furthermore, step 33 includes:

[0033] Step 331: Find the corresponding ID based on pointer j. j To obtain the coordinates of the point

[0034] Step 332: Based on coordinate point Pos j recPos i and azimuth The first vector Vec1 and the second vector Vec2 are calculated using the following formulas:

[0035]

[0036] Step 333: Calculate the length dis of the first vector based on Vec1 and Vec2. Vec1 =|Vec1| and the second vector length dis Vec2 =|Vec2|=1;

[0037] Step 334: Based on vectors Vec1 and Vec2, dis Vec1 and dis Vec2 The formula for calculating the angle θ between the vectors is as follows:

[0038]

[0039] Step 335: According to dis Vec1 and dis Vec2 And the vector angle θ, calculate the axial distance r A and vertical deviation err V The formula is as follows:

[0040]

[0041] Furthermore, step 36 includes:

[0042] Step 361: The pointer i for the data point number points to the next pointer, that is, i = i + 1 is executed;

[0043] Step 362: Update the recorded coordinates recPos i azimuth and trajectory distance recDis i The formula is as follows:

[0044]

[0045] Furthermore, step 4 includes:

[0046] Step 41: Based on the obtained coordinates recPos i azimuth and trajectory distance recDis i coordinate point recPos i Obtain the dataset

[0047] Step 42: Based on the dataset, use the formula Calculate the final azimuth angle

[0048] Step 43: Based on the dataset, use the formula Calculate the final track distance newRecDis i .

[0049] Secondly, this application provides an apparatus for extracting vector trajectory information from an elevation topography scanning area, comprising a physical quantity data acquisition unit, a filtering unit, and a trajectory calculation unit, wherein:

[0050] The physical quantity data acquisition unit is used to process the original recorded time series trajectory / path data to obtain physical quantity data representing the trajectory orientation change, wherein the physical quantity data includes trajectory data points and trajectory azimuth angles;

[0051] The filtering unit is used to calculate the gradient of the orientation data based on the physical quantity data, and filter pre-selected data points that meet the turning change threshold according to the gradient; based on the pre-selected data points, it filters the coordinate points recPos that meet the requirements by calculating the axial distance and vertical distance between the vector trajectory and the actual trajectory. i azimuth and trajectory distance recDis i ;

[0052] The trajectory calculation unit is used to obtain the coordinates recPos. i azimuth and trajectory distance recDis i For the dataset, recalculate the final azimuth angle of the trajectory. Distance from final trajectory to newRecDis i This yields vector trajectory information.

[0053] Furthermore, the filtering unit is specifically used for:

[0054] Set the vertical deviation threshold ERR V and axial growth step size R A The second data filtering process begins; among which, the vertical deviation threshold ERR is... V and axial growth step size R A The settings can be configured based on the width and distance of the scanned area, and the ERR can be set. V The width of the scan area is less than 1 / 3, R A Less than or equal to the scan distance; set the coordinates recPos of pointers i and j for filtering and calculating data point numbers. i azimuth Track Distance recDis i Initial value:

[0055]

[0056] Calculate the axial distance r between the data point corresponding to pointer i and the data point corresponding to pointer j. A and vertical deviation err V If the vertical deviation err is satisfied V <ERR V And axial distance r A <recDis i Then update the filter pointer j = j + 1; if the vertical deviation err is satisfied... V <ERR V And axial distance r A >recDis i Then update the record value recDis. i =rA If the vertical deviation err is satisfied V ERR V And axial distance r A <recDis i Then update the coordinate point recPos i azimuth and trajectory distance recDis i Record the trajectory distance recDis i =r A +R A Store coordinate points recPos i azimuth and trajectory distance recDis i If not all pre-selected data has been checked, update the stored coordinate point recPos. i azimuth and trajectory distance recDis i This continues until all pre-selected data has been tested.

[0057] Furthermore, the trajectory calculation unit is specifically used for:

[0058] Based on the obtained coordinates recPos i azimuth and trajectory distance recDis i coordinate point recPos i Obtain the dataset

[0059] Based on the dataset, using the formula Calculate the final azimuth angle

[0060] Based on the dataset, using the formula Calculate the final track distance newRecDis i .

[0061] In summary, this invention proposes a method and apparatus for extracting vector trajectory information from an elevation topography scanning area. The advantages and effects of this invention are as follows:

[0062] (1) The trajectory information simplification method based on numerical calculation can compress the data storage space, and the data feature points are accurate and objective, and are filtered by the characteristics of the data itself rather than extracted by subjective will.

[0063] (2) The simplified description method of track information is relatively simple and effective, and is very suitable for processing large amounts of raw track information;

[0064] (3) The algorithm is universal, has low requirements for the original trajectory / path data, and is suitable for processing different types of trajectory / path data. Attached Figure Description

[0065] Figure 1 This is a schematic diagram illustrating the principle of a method for extracting vector trajectory information from an elevation topography scanning area according to an embodiment of the present invention;

[0066] Figure 2 This is a flowchart illustrating a method for extracting vector trajectory information from an elevation topography scanning area according to an embodiment of the present invention.

[0067] Figure 3 This is a flowchart illustrating a method for extracting vector trajectory information from an elevation topography scanning area according to another embodiment of the present invention. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0069] like Figure 1 As shown, this application provides a method for extracting vector trajectory information from an elevation topography scanning area, including the following steps:

[0070] Step 1: Process the original time series trajectory / path data to obtain physical quantity data representing the change in trajectory orientation. The physical quantity data includes trajectory data points and trajectory azimuth angles.

[0071] Specifically, step 1 includes:

[0072] Step 11: Begin and set the initial state of the parameters;

[0073] Step 12: Read the trajectory data points X = (x1, x2, ... x n Y = (y1, y2, ... y) n );

[0074] Where X and Y represent the sets of coordinate points in the eastward and northward directions of the trajectory, respectively; x n and y n These are coordinate values ​​for a specific time.

[0075] It should be noted that the trajectory data points X and Y are in a rectangular coordinate system based on the northeast-southeast sky, where the positive direction of X points east and the positive direction of Y points north.

[0076] Step 13: Using trajectory data points X = (x1, x2, ... x n Y = (y1, y2, ... y) n ), calculate trajectory azimuth angle The calculation formula is as follows:

[0077]

[0078] Where Ψ represents the set of trajectory azimuth angles. It is the azimuth angle value of the trajectory at a specific time;

[0079] Step 2: Calculate the gradient of the orientation data based on the physical quantity data, and filter the pre-selected data points that meet the turning change threshold according to the gradient;

[0080] Specifically, step 2 includes:

[0081] Step 21: Calculate the trajectory azimuth angle The absolute value of the gradient data Λ=(λ1,λ2,…λ n The calculation formula is as follows:

[0082]

[0083] Where Λ represents the set of absolute values ​​of the trajectory azimuth gradient, and λ n It is the numerical value of the absolute value of the trajectory azimuth gradient at a specific time.

[0084] Step 22: Calculate the absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n The median λ of the gradient data is obtained by sorting the data. median As a threshold for pre-screening data;

[0085] Step 23: Based on the threshold λ median Filter the absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n (in which) greater than λ median Data point ID sele =(id1,…,id m That is, satisfying:

[0086]

[0087] Step 3: Based on the pre-selected data points, calculate the axial and vertical distances between the vector trajectory and the actual trajectory to filter out the coordinate points recPos that meet the requirements. i azimuth and trajectory distance recDis i ;

[0088] Specifically, step 3 includes:

[0089] Step 31: Set the vertical deviation threshold ERR V and axial growth step size RA Then, the second data filtering process begins;

[0090] Among them, the vertical deviation threshold ERR V and axial growth step size R A The settings can be configured based on the width and distance of the scanned area, and the ERR can be set. V The width of the scan area is less than 1 / 3, R A Less than or equal to the scanning distance.

[0091] Step 32: Set the coordinates recPos of pointers i and j for filtering and calculating data point numbers. i azimuth Track Distance recDis i Initial value:

[0092]

[0093] Step 33: Calculate the axial distance r between the data point corresponding to pointer i and the data point corresponding to pointer j. A and vertical deviation err V ;

[0094] Specifically, step 33 includes:

[0095] Step 331: Find the corresponding ID based on pointer j. j To obtain the coordinates of the point

[0096] Step 332: Based on coordinate point Pos j recPos i and azimuth The first vector Vec1 and the second vector Vec2 are calculated using the following formulas:

[0097]

[0098] Step 333: Calculate the length dis of the first vector based on Vec1 and Vec2. Vec1 =|Vec1| and the second vector length dis Vec2 =|Vec2|=1;

[0099] Step 334: Based on vectors Vec1 and Vec2, dis Vec1 and dis Vec2 The formula for calculating the angle θ between the vectors is as follows:

[0100]

[0101] Step 335: According to dis Vec1 and disVec2 And the vector angle θ, calculate the axial distance r A and vertical deviation err V The formula is as follows:

[0102]

[0103] Step 34: If the vertical deviation err is satisfied V <ERR V And axial distance r A <recDis i Then update the filter pointer j = j + 1; if the vertical deviation err is satisfied... V <ERR V And axial distance r A >recDis i Then update the record value recDis. i =r A If the vertical deviation err is satisfied V ERR V And axial distance r A <recDis i Then update the coordinate point recPos i azimuth and trajectory distance recDis i ;

[0104] Step 35: Record the trajectory distance recDis i =r A +R A Store coordinate points recPos i azimuth and trajectory distance recDis i ;

[0105] Step 36: If not all pre-selected data has been detected, update the stored coordinate point recPos. i azimuth and trajectory distance recDis i This continues until all pre-selected data has been tested.

[0106] Specifically, step 36 includes:

[0107] Step 361: The pointer i for the data point number points to the next pointer, that is, i = i + 1 is executed;

[0108] Step 362: Update the recorded coordinates recPos i azimuth and trajectory distance recDis i The formula is as follows:

[0109]

[0110] Step 4: Obtain the coordinates recPos i azimuth and trajectory distance recDis i For the dataset, recalculate the final azimuth angle of the trajectory. Distance from final trajectory to newRecDis i This yields vector trajectory information.

[0111] Specifically, step 4 includes:

[0112] Step 41: Based on the obtained coordinates recPos i azimuth and trajectory distance recDis i coordinate point recPos i Obtain the dataset

[0113] Step 42: Based on the dataset, use the formula Calculate the final azimuth angle

[0114] Step 43: Based on the dataset, use the formula Calculate the final track distance newRecDis i .

[0115] Example 1

[0116] Figure 2 This is a flowchart illustrating a method for extracting vector trajectory information from an elevation topography scanning area according to an embodiment of the present invention. Figure 2 As shown, the method may include the following steps:

[0117] Step 1: Start and set the initial state of the parameters;

[0118] Step 2: Read the trajectory data points X = (x1, x2, ... x n Y = (y1, y2, ... y) n If there is no trajectory azimuth angle, proceed to step 3 to obtain the trajectory azimuth angle; otherwise, proceed to step 4.

[0119] Step 3: Using trajectory data points X = (x1, x2, ... x n Y = (y1, y2, ... y) n ), calculate trajectory azimuth angle The calculation formula is as follows:

[0120]

[0121] Step 4: Calculate the trajectory azimuth angle The absolute value of the gradient data Λ=(λ1,λ2,…λ n The calculation formula is as follows:

[0122]

[0123] Step 5: Calculate the absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n The median λ of the gradient data is obtained by sorting the data. median As a threshold for pre-screening data;

[0124] Step 6: Using λ median As a threshold for pre-screening data, the absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ) is used to screen the data. n (in which) greater than λ median Data point ID sele =(id1,…,id m That is, satisfying:

[0125]

[0126] Step 7: Set simplified threshold parameters, vertical deviation threshold ERR V and axial growth step size R A Then, the second data filtering process began.

[0127] Step 8: Set the initial values ​​of the filter calculation pointers i and j, and the initial value for recording the filter result, i.e., the coordinate point recPos. i azimuth Track Distance recDis i Initial value:

[0128]

[0129] Step 9: Calculate the axial distance r between data point i and data point j. A and vertical deviation err V :

[0130]

[0131] Vec1 = Pos j -recPos i

[0132]

[0133] dis Vec1 =|Vec1|,dis Vec2 =|Vec2|=1

[0134]

[0135] r A =dis Vec1 ·sinθ

[0136] err V =dis Vec1 ·cosθ

[0137] Step 10: If the vertical deviation err is satisfied V <ERR V And axial distance r A <recDis i If yes, proceed to step 11; otherwise, skip to step 12.

[0138] Step 11: Update the filter pointer j = j + 1, and jump to step 18 to make a judgment;

[0139] Step 12: If the vertical deviation err is satisfied V <ERR V And axial distance r A >recDis i If yes, proceed to step 13; otherwise, skip to step 14.

[0140] Step 13: Update the record value recDis i =r A Proceed to step 11;

[0141] Step 14: If the vertical deviation err is satisfied V ERR V And axial distance r A <recDis i If yes, proceed to step 15; otherwise, skip to step 16.

[0142] Step 15: Store the recorded value (vector trajectory information data: recPos) i , recDis i Proceed to step 17;

[0143] Step 16: Record the value recDis i =r A +R A Stores recorded values ​​(vector trajectory information data: recPos) i , recDis i Proceed to step 17;

[0144] Step 17: Update the recorded value (for the next calculation). The update formula is shown below. After updating, jump to step 11.

[0145]

[0146] Step 18: Determine whether all pre-selected data has been detected. If not, proceed to step 9; otherwise, proceed to step 19.

[0147] Step 19: Recalculate the track azimuth angle based on the completed simplified dataset. and distance newRecDis i The formula is as follows:

[0148] Original data:

[0149] New data:

[0150] New data:

[0151] Step 20: Program ends.

[0152] Example 2

[0153] Figure 3 This is a flowchart illustrating a method for extracting vector trajectory information from an elevation terrain scanning area according to another embodiment of the present invention. The method may include the following steps:

[0154] Step 1: Begin and set the initial state of the parameters;

[0155] Step 2: Read the trajectory data points Lng = (τ1, τ2, ... τ n ), Lat=(υ1,υ2,…υ n ), and convert it to Cartesian coordinate system data X=(x1,x2,…x n Y = (y1, y2, ... y) n The formula is shown below. If the trajectory azimuth angle is not available, proceed to step 3 to obtain the trajectory azimuth angle; otherwise, proceed to step 4.

[0156]

[0157] Step 3: Using trajectory data points X = (x1, x2, ... x n Y = (y1, y2, ... y) n ), calculate trajectory azimuth angle The calculation formula is as follows:

[0158]

[0159] Step 4: Calculate the trajectory azimuth angle The absolute value of the gradient data Λ=(λ1,λ2,…λ n The calculation formula is as follows:

[0160]

[0161] Step 5: Calculate the absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n The median λ of the gradient data is obtained by sorting the data. median As a threshold for pre-screening data;

[0162] Step 6: Using λ median As a threshold for pre-screening data, the absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ) is used to screen the data. n (in which) greater than λ median Data point ID sele =(id1,…,id m That is, satisfying:

[0163]

[0164] Step 7: Set simplified threshold parameters, vertical deviation threshold ERR V and axial growth step size R A Then, the second data filtering process began.

[0165] Step 8: Set the initial values ​​of the filter calculation pointers i and j, and the initial value for recording the filter result, i.e., the coordinate point recPos. i azimuth Track Distance recDis i Initial value:

[0166]

[0167] Step 9: Calculate the axial distance r between data point i and data point j. A and vertical deviation err V :

[0168]

[0169] Vec1 = Pos j -recPos i

[0170]

[0171] dis Vec1 =|Vec1|,dis Vec2 =|Vec2|=1

[0172]

[0173] r A =dis Vec1 ·sinθ

[0174] err V =dis Vec1 ·cosθ

[0175] Step 10: If the vertical deviation err is satisfied V <ERR V And axial distance r A <recDis i If yes, proceed to step 11; otherwise, skip to step 12.

[0176] Step 11: Update the filter pointer j = j + 1, and jump to step 18 to make a judgment;

[0177] Step 12: If the vertical deviation err is satisfied V <ERR V And axial distance r A >recDis i If yes, proceed to step 13; otherwise, skip to step 14.

[0178] Step 13: Update the record value recDis i =r A Proceed to step 11;

[0179] Step 14: If the vertical deviation err is satisfied V ERR V And axial distance r A <recDis i If yes, proceed to step 15; otherwise, skip to step 16.

[0180] Step 15: Store the recorded value (vector trajectory information data: recPos) i , recDis i Proceed to step 17;

[0181] Step 16: Record the value recDis i =r A +R A Stores recorded values ​​(vector trajectory information data: recPos) i , recDis i Proceed to step 17;

[0182] Step 17: Update the recorded value (for the next calculation). The update formula is shown below. After updating, jump to step 11.

[0183]

[0184] Step 18: Determine whether all pre-selected data has been detected. If not, proceed to step 9; otherwise, proceed to step 19.

[0185] Step 19: Recalculate the track azimuth angle based on the completed simplified dataset. and distance newRecDis i The formula is as follows:

[0186] Original data:

[0187] New data:

[0188] New data:

[0189] Step 20: Program ends.

Claims

1. A method for extracting vector trajectory information from an elevation topographic scanning area, characterized in that, The methods include: Step 1: Process the original time series trajectory / path data to obtain physical quantity data representing the change in trajectory orientation. The physical quantity data includes trajectory data points and trajectory azimuth angles. Step 2: Calculate the gradient of the orientation data based on the physical quantity data, and filter the pre-selected data points that meet the turning change threshold according to the gradient; Step 3: Based on the pre-selected data points, calculate the axial and vertical distances between the vector trajectory and the actual trajectory to filter out the coordinate points that meet the requirements. azimuth and trajectory distance ; Step 4: Obtain the coordinates of the points. azimuth and trajectory distance For the dataset, recalculate the final azimuth angle of the trajectory. Distance to final flight path This yields vector trajectory information; Step 2 includes: Step 21: Calculate the trajectory azimuth angle absolute value of gradient data The calculation formula is as follows: in, This represents the set of absolute values ​​of the trajectory azimuth gradient. It is the numerical value of the absolute value of the trajectory azimuth gradient at a specific time. Step 22: Calculate the absolute value of the trajectory azimuth gradient data. Sort the gradient data to obtain the median. As a threshold for pre-screening data; Step 23: Based on the threshold Filter the absolute value of trajectory azimuth gradient data Medium to large Data point number That is, satisfying: ； Step 3 includes: Step 31: Set the vertical deviation threshold and axial growth step size The second data filtering process begins; among which, the vertical deviation threshold is... and axial growth step size The settings can be adjusted based on the width and distance of the scanning area. Less than The width of the scan area, Less than or equal to the scan distance; Step 32: Set the pointer for filtering the data point numbers and pointers coordinates azimuth Trajectory distance Initial value: ； Step 33: Calculate the pointer Corresponding data points and pointers Axial distance between corresponding data points and vertical deviation ; Step 34: If the vertical deviation is satisfied And axial distance Then update the filter pointer. If the vertical deviation is satisfied And axial distance Then update the record value. If the vertical deviation is satisfied And axial distance Then update the coordinates. azimuth and trajectory distance ; Step 35: Record the trajectory distance Store coordinates azimuth and trajectory distance ; Step 36: If not all pre-selected data has been checked, update the stored coordinate points. azimuth and trajectory distance This continues until all pre-selected data has been tested.

2. The method according to claim 1, characterized in that, Step 1 includes: Step 11: Begin and set the initial state of the parameters; Step 12: Read trajectory data points , ;in, , These represent the sets of coordinate points in the eastward and northward directions of the trajectory, respectively. and These are coordinate values ​​for a specific time. Step 13: Using trajectory data points , Calculate the azimuth angle of the trajectory The calculation formula is as follows: in, The set representing the azimuth angles of a trajectory. It is the azimuth angle value of the trajectory at a specific time.

3. The method according to claim 1, characterized in that, Step 33 includes: Step 331: Based on the pointer Find the corresponding number To obtain the coordinates of the point ; Step 332: Based on coordinate points , and azimuth The first vector is calculated. Second vector The calculation formula is as follows: ； Step 333: According to and Calculate the length of the first vector. Second vector length ; Step 334: Based on the vector and , and Calculate the angle between vectors The formula is as follows: ； Step 335: According to and and the angle between vectors Calculate axial distance and vertical deviation The formula is as follows: 。 4. The method according to claim 1, characterized in that, Step 36 includes: Step 361: Pointer for data point numbering Point to the next pointer, i.e., execute. ; Step 362: Update the obtained coordinates. azimuth and trajectory distance The formula is as follows: 。 5. The method according to claim 1, characterized in that, Step 4 includes: Step 41: Based on the obtained coordinates azimuth and trajectory distance coordinates Obtain the dataset ; Step 42: Based on the dataset, use the formula Calculate the final azimuth angle of the flight path. ; Step 43: Based on the dataset, use the formula Calculate the final track distance .

6. A device for extracting vector trajectory information from an elevation topography scanning area, characterized in that, It includes a physical quantity data acquisition unit, a filtering unit, and a trajectory calculation unit, wherein: The physical quantity data acquisition unit is used to process the original recorded time series trajectory / path data to obtain physical quantity data representing the trajectory orientation change, wherein the physical quantity data includes trajectory data points and trajectory azimuth angles; The filtering unit is used to calculate the gradient of the orientation data based on the physical quantity data, and filter pre-selected data points that meet the turning change threshold according to the gradient; based on the pre-selected data points, it filters coordinate points that meet the requirements by calculating the axial distance and vertical distance between the vector trajectory and the actual trajectory. azimuth and trajectory distance Specifically used to calculate the azimuth angle of a trajectory. absolute value of gradient data The calculation formula is as follows: in, This represents the set of absolute values ​​of the trajectory azimuth gradient. It is the numerical value of the absolute value of the trajectory azimuth gradient at a specific time. absolute value of trajectory azimuth gradient data Sort the gradient data to obtain the median. As a threshold for pre-screening data; According to the threshold Filter the absolute value of trajectory azimuth gradient data Medium to large Data point number That is, satisfying: ； And for: setting the vertical deviation threshold and axial growth step size The second data filtering process begins; among which, the vertical deviation threshold is... and axial growth step size The settings can be adjusted based on the width and distance of the scanning area. Less than The width of the scan area, Less than or equal to the scan distance; set the pointer to filter the calculated data point numbers. and pointers coordinates azimuth Trajectory distance Initial value: ； Calculate pointer Corresponding data points and pointers Axial distance between corresponding data points and vertical deviation If the vertical deviation is satisfied And axial distance Then update the filter pointer. If the vertical deviation is satisfied And axial distance Then update the record value. If the vertical deviation is satisfied And axial distance Then update the coordinates. azimuth and trajectory distance ; Record the trajectory distance Store coordinates azimuth and trajectory distance If not all pre-selected data has been checked, update the stored coordinate points. azimuth and trajectory distance This continues until all pre-selected data has been tested; Trajectory calculation unit, used to obtain coordinate points azimuth and trajectory distance For the dataset, recalculate the final azimuth angle of the trajectory. Distance to final flight path This yields vector trajectory information.

7. The apparatus according to claim 6, characterized in that, The filtering unit is specifically used for: Set vertical deviation threshold and axial growth step size The second data filtering process begins; among which, the vertical deviation threshold is... and axial growth step size The settings can be adjusted based on the width and distance of the scanning area. Less than The width of the scan area, Less than or equal to the scan distance; set the pointer to filter the calculated data point numbers. and pointers coordinates azimuth Trajectory distance Initial value: ； Calculate pointer Corresponding data points and pointers Axial distance between corresponding data points and vertical deviation If the vertical deviation is satisfied And axial distance Then update the filter pointer. If the vertical deviation is satisfied And axial distance Then update the record value. If the vertical deviation is satisfied And axial distance Then update the coordinates. azimuth and trajectory distance Record the distance of the trajectory. Store coordinates azimuth and trajectory distance If not all pre-selected data has been checked, update the stored coordinate points. azimuth and trajectory distance This continues until all pre-selected data has been tested.

8. The apparatus according to claim 6, characterized in that, The trajectory calculation unit is specifically used for: Based on the obtained coordinates azimuth and trajectory distance coordinates Obtain the dataset ; Based on the dataset, using the formula Calculate the final azimuth angle of the flight path. ; Based on the dataset, using the formula Calculate the final track distance .

Images