Method and device for extracting vector trajectory information for elevation terrain scanning area

Abstract

The invention provides a method and device for extracting vector trajectory information for an elevation terrain scanning area, and the method comprises the steps: 1, carrying out the processing of originally recorded time sequence trajectory / path data, obtaining the physical quantity data representing the azimuth change of a trajectory, and enabling the physical quantity data to comprise a trajectory data point and a trajectory azimuth angle; 2, calculating the gradient of the azimuth data according to the physical quantity data, and screening pre-selected data points meeting a turning change threshold value according to the gradient; 3, on the basis of the preselected data points, screening a coordinate point recPosi, an azimuth angle # imgabs0 # and a track distance recDisi which meet requirements by calculating an axial distance and a vertical distance between a vector track and an actual track; and step 4, taking the obtained coordinate point recPosi, the azimuth angle # imgabs1 # and the track distance recDisi as a data set, recalculating the final track azimuth angle # imgabs2 # and the final track distance newRecDisi of the track, and obtaining vector track information.

Description

Technical Field

[0001] The present invention relates to the field of flight control technology, and in particular to a method and device for extracting vector trajectory information for an elevation terrain scanning area. Background Art

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

[0003] Most of the existing open-source high-precision elevation terrain data have a resolution of about 1 arc second (about 30m). An aircraft flying at a speed of 100m / s moves about 1m in a period of 10ms. Directly using the coordinates of the trajectory points to interpolate the elevation data corresponding to the trajectory will consume a lot of computing power and storage space, especially in straight-line motion with little azimuth change. The two-dimensional trajectory can be represented by the starting point coordinates (two-dimensional), azimuth and displacement distance. All the data of this trajectory / path, the data size is reduced from 2n to 4 (n represents the number of times data is recorded).

[0004] However, the method of extracting vector trajectory information in the prior art can only represent the trajectory of straight line segments. For the case of curved motion, the method will be distorted, especially for the case of azimuth angle change distance. Summary of the invention

[0005] The present invention proposes a method and device for extracting vector trajectory information from an elevation terrain scanning area, performs numerical operations on a large amount of trajectory / path record data, calculates and determines feature points (trajectory / path change points) through mathematical methods, and automatically generates a simplified trajectory / path, thereby reducing the data size for storing the information, and reducing the data storage size as much as possible while ensuring that the trajectory / path is not distorted.

[0006] In a first aspect, the present application provides a method for extracting vector trajectory information for an elevation terrain scanning area, the method comprising:

[0007] Step 1: Processing the original recorded time series trajectory / path data to obtain physical quantity data representing trajectory azimuth changes, wherein 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 select pre-selected data points that meet the turning change threshold based on the gradient;

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

[0010] Step 4: Get the coordinate point recPos i , azimuth and track distance recDis i Recalculate the final track azimuth of the trajectory for the dataset and the final track distance newRecDis i , get the vector trajectory information.

[0011] Furthermore, step 1 includes:

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

[0013] Step 12: Read trajectory data points X = (x1, x2, ... x n ), Y=(y1,y2,…y n ), where X and Y represent the set of coordinate points in the east and north directions of the trajectory respectively; n and n is the coordinate value at a specific time;

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

[0015]

[0016] Among them, Ψ represents the set of trajectory azimuths, It is the trajectory azimuth value at a specific time.

[0017] Furthermore, step 2 includes:

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

[0019]

[0020] Among them, Λ represents the set of absolute values ​​of trajectory azimuth gradient, λ n It is the value of the absolute value of the trajectory azimuth gradient at a specific time;

[0021] Step 22: The absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n ) to sort and obtain the median λ of the gradient data median As a threshold for pre-screening data;

[0022] Step 23: According to the threshold λ median , filter the absolute value of trajectory azimuth gradient data Λ=(λ1,λ2,…λ n ) is 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 length R A , start the second data screening; among them, the vertical deviation threshold ERR V and axial growth step length R A The setting value can be set according to the width and distance of the scanning area. ERR V Less than 1 / 3 of the width of the scan area, R A Less than or equal to the scanning distance;

[0026] Step 32: Set the coordinate point recPos of pointer i and pointer j for filtering and calculating the data point number i , azimuth Track distance recDis i Initial value of:

[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 the axial distance r A <recDis i , then update the screening pointer j = j + 1; if the vertical deviation err V <ERR V And the 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 the axial distance r A <recDis i , then update the coordinate point recPos i , azimuth and track distance recDis i ;

[0030] Step 35: Record the track distance recDis i =r A +R A , store the coordinate point recPos i , azimuth and track distance recDis i ;

[0031] Step 36: If all pre-selected data have not been detected, update the storage coordinate point recPos i , azimuth and track distance recDis i , until all pre-selected data are detected.

[0032] Further, step 33 includes:

[0033] Step 331: Find the corresponding number id according to pointer j j , get the coordinate point

[0034] Step 332: According to the coordinate point Pos j 、recPos i and azimuth The first vector Vec1 and the second vector Vec2 are calculated, and the calculation formula is as follows:

[0035]

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

[0037] Step 334: According to vectors Vec1 and Vec2, dis Vec1 and dis Vec2 , calculate the vector angle θ, the formula 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] Further, step 36 includes:

[0042] Step 361: the pointer i of the data point number points to the next pointer, i.e., i=i+1 is executed;

[0043] Step 362: Update the recorded coordinate point recPos i , azimuth and track distance recDis i , the formula is as follows:

[0044]

[0045] Furthermore, step 4 includes:

[0046] Step 41: According to the acquired coordinate point recPos i , azimuth and track distance recDis i Coordinate point recPos i , get the data set

[0047] Step 42: Based on the data set, use the formula Calculate the final track bearing

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

[0049] In a second aspect, the present application provides a device for extracting vector trajectory information for an elevation terrain scanning area, comprising a physical quantity data acquisition unit, a screening unit and a trajectory calculation unit, wherein:

[0050] A physical quantity data acquisition unit, used for processing the original recorded time series trajectory / path data to obtain physical quantity data representing trajectory azimuth changes, wherein the physical quantity data includes trajectory data points and trajectory azimuth angles;

[0051] The screening unit is used to calculate the gradient of the azimuth data according to the physical quantity data, and screen the pre-selected data points that meet the turning change threshold according to the gradient; on the basis of the pre-selected data points, the axial distance and vertical distance between the vector trajectory and the actual trajectory are calculated to screen the coordinate points recPos that meet the requirements. i , azimuth and track distance recDis i ;

[0052] Trajectory calculation unit, used to obtain the coordinate point recPos i , azimuth and track distance recDis i Recalculate the final track azimuth of the trajectory for the dataset and the final track distance newRecDis i , get the vector trajectory information.

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

[0054] Set the vertical deviation threshold ERR V and axial growth step length R A , start the second data screening; among them, the vertical deviation threshold ERR V and axial growth step length R A The setting value can be set according to the width and distance of the scanning area. ERR V Less than 1 / 3 of the width of the scan area, R A Less than or equal to the scanning distance; set the coordinate points recPos of pointers i and j for filtering and calculating data point numbers i , azimuth Track distance recDis i Initial value of:

[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 the axial distance r A <recDis i , then update the screening pointer j = j + 1; if the vertical deviation err V <ERR V And the 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 the axial distance r A <recDis i , then update the coordinate point recPos i , azimuth and track distance recDis i ; Record the trajectory distance recDis i =r A +R A , store the coordinate point recPos i , azimuth and track distance recDis i ; If all pre-selected data have not been detected, update the storage coordinate point recPos i , azimuth and track distance recDis i , until all pre-selected data are detected.

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

[0058] According to the acquired coordinate point recPos i , azimuth and track distance recDis i Coordinate point recPos i , get the data set

[0059] According to the data set, using the formula Calculate the final track bearing

[0060] According to the data set, using the formula Calculate the final track distance newRecDis i .

[0061] In summary, the present invention proposes a method and device for extracting vector trajectory information for an elevation terrain scanning area. The advantages and effects of the present invention may be:

[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 screened by the data's own characteristics 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 original track information;

[0064] (3) The algorithm is universal, has low requirements on original trajectory / path data, and is suitable for processing different types of trajectory / path data. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0066] Figure 2 It is a flow chart of a method for extracting vector trajectory information from an elevation terrain scanning area according to an embodiment of the present invention;

[0067] Figure 3 It is a flowchart of a method for extracting vector trajectory information from an elevation terrain scanning area according to another embodiment of the present invention. DETAILED DESCRIPTION

[0068] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0069] like Figure 1 As shown, the present application provides a method for extracting vector trajectory information for an elevation terrain scanning area, comprising the following steps:

[0070] Step 1: Processing the original recorded time series trajectory / path data to obtain physical quantity data representing trajectory azimuth changes, wherein the physical quantity data includes trajectory data points and trajectory azimuth angles;

[0071] Specifically, step 1 includes:

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

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

[0074] Where X and Y represent the set of coordinate points in the east and north directions of the trajectory respectively; n and n is the coordinate value at a specific time;

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

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

[0077]

[0078] Among them, Ψ represents the set of trajectory azimuths, is the trajectory azimuth value at a specific time;

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

[0080] Specifically, step 2 includes:

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

[0082]

[0083] Among them, Λ represents the set of absolute values ​​of trajectory azimuth gradient, λ n It is the value of the absolute value of the trajectory azimuth gradient at a specific time;

[0084] Step 22: The absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n ) to sort and obtain the median λ of the gradient data median As a threshold for pre-screening data;

[0085] Step 23: According to the threshold λ median , filter the absolute value of trajectory azimuth gradient data Λ=(λ1,λ2,…λ n ) is 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, the axial distance and vertical distance between the vector trajectory and the actual trajectory are calculated to select the coordinate points recPos that meet the requirements. i , azimuth and track distance recDis i ;

[0088] Specifically, step 3 includes:

[0089] Step 31: Set the vertical deviation threshold ERR V and axial growth step length RA , start the second data screening;

[0090] Among them, the vertical deviation threshold ERR V and axial growth step length R A The setting value can be set according to the width and distance of the scanning area. ERR V Less than 1 / 3 of the width of the scan area, R A Less than or equal to the scanning distance.

[0091] Step 32: Set the coordinate point recPos of pointer i and pointer j for filtering and calculating the data point number i , azimuth Track distance recDis i Initial value of:

[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 number id according to pointer j j , get the coordinate point

[0096] Step 332: According to the coordinate point Pos j 、recPos i and azimuth The first vector Vec1 and the second vector Vec2 are calculated, and the calculation formula is as follows:

[0097]

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

[0099] Step 334: According to vectors Vec1 and Vec2, dis Vec1 and dis Vec2 , calculate the vector angle θ, the formula 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 the axial distance r A <recDis i , then update the screening pointer j = j + 1; if the vertical deviation err V <ERR V And the 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 the axial distance r A <recDis i , then update the coordinate point recPos i , azimuth and track distance recDis i ;

[0104] Step 35: Record the track distance recDis i =r A +R A , store the coordinate point recPos i , azimuth and track distance recDis i ;

[0105] Step 36: If all pre-selected data have not been detected, update the storage coordinate point recPos i , azimuth and track distance recDis i , until all pre-selected data are detected.

[0106] Specifically, step 36 includes:

[0107] Step 361: the pointer i of the data point number points to the next pointer, i.e., i=i+1 is executed;

[0108] Step 362: Update the recorded coordinate point recPos i , azimuth and track distance recDis i , the formula is as follows:

[0109]

[0110] Step 4: Get the coordinate point recPos i , azimuth and track distance recDis i Recalculate the final track azimuth of the trajectory for the dataset and the final track distance newRecDis i , get the vector trajectory information.

[0111] Specifically, step 4 includes:

[0112] Step 41: According to the acquired coordinate point recPos i , azimuth and track distance recDis i Coordinate point recPos i , get the data set

[0113] Step 42: Based on the data set, use the formula Calculate the final track bearing

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

[0115] Embodiment 1

[0116] Figure 2 FIG. 1 is a flow chart of a method for extracting vector trajectory information from an elevation terrain 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 trajectory data points X = (x1, x2, ... x n ), Y=(y1,y2,…y n ), if there is no track azimuth, execute step 3 to obtain the track azimuth, otherwise execute step 4;

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

[0120]

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

[0122]

[0123] Step 5: The absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n ) to sort and obtain the median λ of the gradient data median As a threshold for pre-screening data;

[0124] Step 6: Take λ median As the threshold of pre-screening data, the absolute value of the azimuth gradient data of the screening trajectory Λ=(λ1,λ2,…λ n ) is 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 length R A , start the second data screening.

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

[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 the axial distance r A <recDis i , then proceed to step 11, otherwise jump to step 12;

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

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

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

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

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

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

[0144] Step 17: Update the record value (for the next calculation). The update formula is as follows. After updating, jump to step 11;

[0145]

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

[0147] Step 19: Recalculate the track bearing based on the completed simplified data set and distance newRecDis i , the formula is as follows:

[0148] Original data:

[0149] New data:

[0150] New data:

[0151] Step 20: The program ends.

[0152] Embodiment 2

[0153] Figure 3 FIG. 1 is a flow chart of 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: Start and set the initial state of the parameters;

[0155] Step 2: Read trajectory data points Lng = (τ1, τ2, ... τ n ), Lat=(υ1,υ2,…υ n ), and convert it into rectangular coordinate system data X=(x1,x2,…x n ), Y=(y1,y2,…y n ), the formula is as follows. If there is no trajectory azimuth, execute step 3 to obtain the trajectory azimuth, otherwise execute step 4;

[0156]

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

[0158]

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

[0160]

[0161] Step 5: The absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n ) to sort and obtain the median λ of the gradient data median As a threshold for pre-screening data;

[0162] Step 6: Take λ median As the threshold of pre-screening data, the absolute value of the azimuth gradient data of the screening trajectory Λ=(λ1,λ2,…λ n ) is 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 length R A , start the second data screening.

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

[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 the axial distance r A <recDis i , then proceed to step 11, otherwise jump to step 12;

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

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

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

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

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

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

[0182] Step 17: Update the record value (for the next calculation). The update formula is as follows. After updating, jump to step 11;

[0183]

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

[0185] Step 19: Recalculate the track bearing based on the completed simplified data set and distance newRecDis i , the formula is as follows:

[0186] Original data:

[0187] New data:

[0188] New data:

[0189] Step 20: The program ends.

Claims

1. A method for extracting vector trajectory information from an elevation terrain scanning area, characterized in that: Methods include: Step 1: Processing the original recorded time series trajectory / path data to obtain physical quantity data representing trajectory azimuth changes, wherein 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 select pre-selected data points that meet the turning change threshold based on the gradient; Step 3: Based on the pre-selected data points, the axial distance and vertical distance between the vector trajectory and the actual trajectory are calculated to select the coordinate points recPos that meet the requirements. i , azimuth and track distance recDis i ; Step 4: To obtain the coordinate point recPos i , azimuth and track distance recDis i Recalculate the final track azimuth of the trajectory for the dataset and the final track distance newRecDis i , get the vector trajectory information.

2. The method according to claim 1, characterized in that: Step 1 includes: Step 11: Start and set the initial state of the parameters; Step 12: Read trajectory data points X = (x1, x2, ... x n ), Y=(y1,y2,…y n ), where X and Y represent the set of coordinate points in the east and north directions of the trajectory respectively; n and n is the coordinate value at a specific time; Step 13: Through the trajectory data points X = (x1, x2, ... x n ), Y=(y1,y2,…y n ), calculate the trajectory azimuth The calculation formula is as follows: Among them, Ψ represents the set of trajectory azimuths, It is the trajectory azimuth value at a specific time.

3. The method according to claim 1, characterized in that: Step 2 includes: Step 21: Calculate the trajectory azimuth The absolute value of the gradient data Λ=(λ1,λ2,…λ n ), the calculation formula is as follows: Among them, Λ represents the set of absolute values ​​of trajectory azimuth gradient, λ n It is the absolute value of the trajectory azimuth gradient at a specific time; Step 22: The absolute value of the trajectory azimuth gradient data Λ=(λ1,λ2,…λ n ) to sort and obtain the median λ of the gradient data median As a threshold for pre-screening data; Step 23: According to the threshold λ median , filter the absolute value of trajectory azimuth gradient data Λ=(λ1,λ2,…λ n ) is greater than λ median Data point ID sele =(id1,…,id m ), that is, satisfying:

4. The method according to claim 1, characterized in that: Step 3 includes: Step 31: Set the vertical deviation threshold ERR V and axial growth step length R A , start the second data screening; among them, the vertical deviation threshold ERR V and axial growth step length R A The setting value can be set according to the width and distance of the scanning area. ERR V Less than 1 / 3 of the width of the scan area, R A Less than or equal to the scanning distance; Step 32: Set the coordinate point recPos of pointer i and pointer j for filtering and calculating the data point number i , azimuth Track distance recDis i Initial value of: 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 ; Step 34: If the vertical deviation err is satisfied V <ERR V And the axial distance r A <recDis i , then update the screening pointer j = j + 1; if the vertical deviation err is satisfied V <ERR V And the 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 the axial distance r A <recDis i , then update the coordinate point recPos i , azimuth and track distance recDis i ; Step 35: Record the track distance recDis i =r A +R A , store the coordinate point recPos i , azimuth and track distance recDis i ; Step 36: If all pre-selected data have not been detected, update the storage coordinate point recPos i , azimuth and track distance recDis i , until all pre-selected data are detected.

5. The method according to claim 4, characterized in that Step 33 includes: Step 331: Find the corresponding number id according to pointer j j , get the coordinate point Step 332: According to the coordinate point Pos j 、recPos i and azimuth The first vector Vec1 and the second vector Vec2 are calculated, and the calculation formula is as follows: Step 333: Calculate the length of the first vector dis according to Vec1 and Vec2 Vec1 = |Vec1| and the length of the second vector dis Vec2 =|Vec2|=1; Step 334: According to vectors Vec1 and Vec2, dis Vec1 and dis Vec2 , calculate the vector angle θ, the formula is as follows: 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:

6. The method according to claim 4, characterized in that Step 36 includes: Step 361: the pointer i of the data point number points to the next pointer, i.e., i=i+1 is executed; Step 362: Update the recorded coordinate point recPos i , azimuth and track distance recDis i , the formula is as follows:

7. The method according to claim 1, characterized in that Step 4 includes: Step 41: According to the acquired coordinate point recPos i , azimuth and track distance recDis i Coordinate point recPos i , get the data set Step 42: Based on the data set, use the formula Calculate the final track bearing Step 43: Based on the data set, use the formula Calculate the final track distance newRecDis i .

8. A device for extracting vector trajectory information from an elevation terrain scanning area, characterized in that: It includes a physical quantity data acquisition unit, a screening unit and a trajectory calculation unit, wherein: A physical quantity data acquisition unit, used for processing the original recorded time series trajectory / path data to obtain physical quantity data representing trajectory azimuth changes, wherein the physical quantity data includes trajectory data points and trajectory azimuth angles; The screening unit is used to calculate the gradient of the azimuth data according to the physical quantity data, and screen the pre-selected data points that meet the turning change threshold according to the gradient; on the basis of the pre-selected data points, the axial distance and vertical distance between the vector trajectory and the actual trajectory are calculated to screen the coordinate points recPos that meet the requirements. i , azimuth and track distance recDis i ; Trajectory calculation unit, used to obtain the coordinate point recPos i , azimuth and track distance recDis i Recalculate the final track azimuth of the trajectory for the dataset and the final track distance newRecDis i , get the vector trajectory information.

9. The device according to claim 8, characterized in that Screening unit, specifically for: Set the vertical deviation threshold ERR V and axial growth step length R A , start the second data screening; among them, the vertical deviation threshold ERR V and axial growth step length R A The setting value can be set according to the width and distance of the scanning area. ERR V Less than 1 / 3 of the width of the scan area, R A Less than or equal to the scanning distance; set the coordinate point recPos of pointer i and pointer j for filtering and calculating the data point number i , azimuth Track distance recDis i Initial value of: 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 the axial distance r A <recDis i , then update the screening pointer j = j + 1; if the vertical deviation err is satisfied V <ERR V And the 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 the axial distance r A <recDis i , then update the coordinate point recPos i , azimuth and track distance recDis i ; Record the trajectory distance recDis i =r A +R A , store the coordinate point recPos i , azimuth and track distance recDis i ; If all pre-selected data have not been detected, update the storage coordinate point recPos i , azimuth and track distance recDis i , until all pre-selected data are detected.

10. The device according to claim 8, characterized in that The trajectory calculation unit is specifically used for: According to the acquired coordinate point recPos i , azimuth and track distance recDis i Coordinate point recPos i , get the data set According to the data set, using the formula Calculate the final track bearing According to the data set, using the formula Calculate the final track distance newRecDis i .

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