Collinear target searching method and device based on spatial transformation, medium and product

Abstract

The invention provides a collinear target searching method and device based on spatial transformation, a medium and a product. The method comprises the following steps: calculating a first distance between any two target points in a plurality of target points; dividing the plurality of target points into m groups of adjacent points according to a first distance between any two target points in the plurality of target points; performing spatial transformation on each group in the m groups of adjacent points, and determining a collinear target search area in a polar coordinate system; aiming at each of the collinear target searching areas, obtaining all mapping points corresponding to a first straight line under a rectangular coordinate system contained in the area, determining a polar radius average value # imgabs0 # and a polar angle coordinate value # imgabs1 # of all the mapping points in the area, and determining a target point under the rectangular coordinate system corresponding to a curve passing through a point # imgabs2 # as a collinear target point, the same straight line is a straight line under a rectangular coordinate corresponding to a point # imgabs3 # under a polar coordinate system. By means of the technical scheme, the calculation complexity of collinear target searching can be reduced.

Description

Technical Field

[0001] The present invention relates to the field of collinear target searching, and in particular to a method, device, medium and product for searching collinear targets based on space transformation. Background Art

[0002] Collinear target search is the process of finding a straight line as close as possible to a set of target points. The existing collinear target search methods based on spatial transformation, such as Hough transform, map the coordinates of plane space points to parameter space and search for collinear targets by traversing the intersections of all straight lines in the entire parameter space. The calculation complexity is high and its accuracy is easily affected by the fine-grained sampling of the parameter space. Summary of the invention

[0003] The embodiments of the present invention provide a method, device, medium and product for searching collinear targets based on space transformation, so as to reduce the complexity of calculation while ensuring a certain collinear target searching accuracy.

[0004] In order to achieve the above object, on the one hand, a method for finding collinear targets based on spatial transformation is provided, comprising:

[0005] S1, obtain the horizontal and vertical coordinates of multiple target points in a rectangular coordinate system;

[0006] S2, calculating a first distance between any two target points among the multiple target points according to the obtained horizontal and vertical coordinates;

[0007] S3, dividing the multiple target points into m groups of adjacent points according to the first distance between any two target points among the multiple target points, wherein the first distance between any two target points included in each group of adjacent points is less than a predetermined first distance threshold;

[0008] S4, performing polar coordinate system spatial transformation for each of the m groups of adjacent points, and determining a collinear target search area in the polar coordinate system, including:

[0009] S41, performing the following processing on each of the m groups of adjacent points:

[0010] Determine the first straight line formed by all target points in the group of adjacent points, and obtain n first straight lines l1 to l n ;

[0011] Each first straight line l among the n first straight lines i Perform spatial transformation from rectangular coordinate system to polar coordinate system. The first straight line l i The mapping point in the polar coordinate system is: (r i ,θ i), i = 1, ..., n, where r i is the distance from the first straight line to the origin of the rectangular coordinate system, θ i is the angle θ between the normal of the first straight line and the positive direction of the horizontal axis of the rectangular coordinate system i ; Each target point is mapped into a set of curves passing through the point in polar coordinates;

[0012] According to the r corresponding to each first straight line i and θ i , calculate the average value of the n distances from the n first straight lines to the origin of the rectangular coordinate system and the average value of the n angles between the normal lines of the n first straight lines and the positive direction of the horizontal axis of the rectangular coordinate system

[0013] Calculating the difference in distances from each two of the n first straight lines to the origin of the rectangular coordinate system to obtain a plurality of distance differences and calculating the difference in angles between the normals of each two of the n first straight lines and the positive direction of the horizontal axis of the rectangular coordinate system to obtain a plurality of angle differences;

[0014] averaging the multiple distance differences to obtain an average distance difference; and averaging the multiple angle differences to obtain an average angle difference;

[0015] S42, calculating the median of the average distance difference and the median of the average angle difference of the m groups of adjacent points, and excluding a group of adjacent points that meets any one of the following conditions to obtain the remaining p groups of adjacent points, where p is less than or equal to m:

[0016] The difference between the average distance difference and the median of the average distance difference is greater than a predetermined average distance difference threshold;

[0017] The difference between the average angle difference and the median of the average angle difference is greater than a predetermined average angle difference threshold;

[0018] S43, for each of the remaining p groups of adjacent points, the average value corresponding to the group of adjacent points is calculated. is the polar diameter, the corresponding average value Determine the anchor point of this group of adjacent points in polar coordinates for the polar angle and determining the anchor point region corresponding to the group of adjacent points in polar coordinates by taking the anchor point as the center, the average distance difference corresponding to the group of adjacent points as the length, and the corresponding average angle difference as the width, to obtain p anchor point regions, and use the p anchor point regions as collinear target search regions;

[0019] S5, for each of the collinear target search areas, obtain all mapping points contained in the area corresponding to the first straight line in the rectangular coordinate system, and determine the average polar diameter of all mapping points in the area and polar coordinates And pass through the area The target point in the rectangular coordinate system corresponding to the curve is determined as the collinear target point passing through the same straight line, and the same straight line is the point in the polar coordinate system. The corresponding straight line in rectangular coordinates.

[0020] Preferably, in the collinear target searching method, step S6 further comprises:

[0021] When there are multiple center points whose distances between the center points are less than a second distance threshold among the p center points corresponding to the p anchor point areas, the anchor point area containing the largest number of mapping points among the multiple anchor point areas corresponding to the multiple center points is retained, and the other anchor point areas among the multiple anchor point areas are deleted to obtain the remaining q anchor point areas, and the q anchor point areas are used as the collinear target search areas, where q is less than or equal to p.

[0022] Preferably, the collinear target searching method further comprises, after step S1 and before step S2, a step of normalizing the horizontal and vertical coordinates of the multiple target points in a rectangular coordinate system.

[0023] Preferably, the collinear target search method, normalizing the horizontal and vertical coordinates of the multiple target points in the rectangular coordinate system comprises: determining the smallest horizontal coordinate xmin and the smallest vertical coordinate ymin among the horizontal and vertical coordinates of the multiple target points in the rectangular coordinate system; and, respectively subtracting the xmin and ymin from the horizontal and vertical coordinates of the multiple target points in the rectangular coordinate system to obtain the relative coordinates of each target point;

[0024] Wherein, in the step S2, the first distance is calculated according to the relative coordinates of the target points.

[0025] On the other hand, a method for searching for collinear obstacles is provided, which uses any of the collinear target searching methods described above to search for collinear obstacles.

[0026] On the other hand, a method for searching for co-linear parking space numbers is provided, using the co-linear target searching method described in any one of the above texts to search for co-linear parking space numbers.

[0027] On the other hand, a collinear target searching device based on spatial transformation is provided, comprising a memory and a processor, wherein the memory stores at least one program, and the at least one program is executed by the processor to implement the steps of any collinear target searching method described above.

[0028] On the other hand, a computer-readable storage medium is provided, wherein at least one program is stored in the storage medium, and the at least one program is executed by a processor to implement the steps of any of the co-linear target search methods described above.

[0029] On the other hand, a computer program product is provided, comprising a computer program, characterized in that when the computer program is executed by a processor, the steps of any of the co-linear target searching methods described above are implemented.

[0030] On the other hand, a vehicle is provided for searching for co-linear targets using any of the co-linear target searching methods described above.

[0031] The above technical solution has the following technical effects:

[0032] The technical solution of the embodiment of the present invention performs spatial transformation on the points and lines of the rectangular coordinate system and maps them to the polar coordinate space, determines adjacent points, groups the adjacent points and then determines the collinear target search area, i.e., the anchor point area, that is, calculates the target search range of the parameter space through the straight line features under the rectangular coordinate system, thereby avoiding the decrease in the straight line search accuracy or the increase in the calculation complexity and the consumption of excessive computing resources due to unreasonable search parameter settings; avoiding the defect of the existing Hough algorithm that traverses the entire parameter space to search for the target straight line, optimizing the search complexity, and reducing the calculation complexity and resource consumption while ensuring a certain collinear target search accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a flowchart of a method for searching for collinear targets based on space transformation according to an embodiment of the present invention;

[0034] Figure 2 is a schematic diagram of target point coordinates in an exemplary rectangular coordinate system;

[0035] Figure 3 for Figure 2 Schematic diagram of multiple groups of target point curves corresponding to the target points in the polar coordinate system;

[0036] Figure 4 An example of the distance r from a straight line to the origin and the angle θ between the normal of the straight line and the positive direction of the horizontal axis in a rectangular coordinate system;

[0037] Figure 5 An example of a collinear search area determined by using the method of an embodiment of the present invention in a target point curve in a polar coordinate system;

[0038] Figure 6 Based on Figure 5 The three collinear search areas determined in , and the three straight lines found in the rectangular coordinate system. DETAILED DESCRIPTION

[0039] To further illustrate the various embodiments, the present invention provides drawings. These drawings are part of the disclosure of the present invention, which are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, a person of ordinary skill in the art should be able to understand other possible implementations and advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0040] The present invention will now be further described with reference to the accompanying drawings and specific implementation methods.

[0041] Embodiment 1:

[0042] Figure 1 FIG. 1 is a flow chart of a method for searching collinear targets based on spatial transformation according to an embodiment of the present invention. Figure 1 The collinear target search method based on space transformation in this embodiment includes:

[0043] S1, obtaining the horizontal and vertical coordinates of a plurality of target points in a rectangular coordinate system; wherein the plurality of target points are the plurality of target points from which collinear target points are to be found;

[0044] Figure 2 is a schematic diagram of target point coordinates in an exemplary rectangular coordinate system; Figure 2 The white dots in the figure are the multiple target points from which collinear targets are to be found; the units of the horizontal and vertical coordinates are the selected distance units;

[0045] S2, calculating a first distance between any two target points among the multiple target points according to the obtained horizontal and vertical coordinates; in a specific implementation, the first distance is a Euclidean distance in a rectangular coordinate system;

[0046] Preferably, after step S1 and before step S2, the step of normalizing the horizontal and vertical coordinates of the multiple target points in the rectangular coordinate system is further included; in a specific implementation, normalizing the horizontal and vertical coordinates of the multiple target points in the rectangular coordinate system includes: determining the smallest horizontal coordinate xmin and the smallest vertical coordinate ymin among the horizontal and vertical coordinates of the multiple target points in the rectangular coordinate system; and, respectively subtracting xmin and ymin from the horizontal and vertical coordinates of the multiple target points in the rectangular coordinate system to obtain the relative coordinates of each target point; in step S2, each first distance is calculated according to the relative coordinates of each target point;

[0047] The normalization step allows only relative coordinates to be calculated without calculating absolute coordinates, thus avoiding coordinates that are too large and simplifying the calculation;

[0048] S3, dividing the multiple target points into m groups of adjacent points according to the first distance between any two target points among the multiple target points, wherein the first distance between any two target points included in each group of adjacent points is less than a predetermined first distance threshold;

[0049] In a specific implementation, the first distance threshold is selected according to the actual application scenario; for example, in searching for collinear parking spaces in a parking lot, the first distance threshold can be set to the width of the vehicle, such as 2 meters; in searching for collinear obstacles, such as searching for collinear pillars in a parking lot, the first distance threshold can be the distance between two pillars, such as 3 meters; according to the actual application scenario, the first distance threshold can be set to an appropriate value;

[0050] S4, performing polar coordinate system spatial transformation for each of the m groups of adjacent points, and determining a collinear target search area in the polar coordinate system, including:

[0051] S41, performing the following processing on each of the m groups of adjacent points:

[0052] Determine the first straight line formed by all target points in the group of adjacent points, and obtain n first straight lines l1 to l n ; In a specific implementation, the number of first straight lines corresponding to different groups of adjacent points is the same or different; when determining the first straight line formed between all target points in the group of adjacent points, the target points may be selected repeatedly or not;

[0053] Each first straight line l among the n first straight lines i Perform spatial transformation from rectangular coordinate system to polar coordinate system. The first straight line l i The mapping point in the polar coordinate system is: (r i ,θ i ), i = 1, ..., n, where r i is the distance from the first straight line to the origin of the rectangular coordinate system, θ i is the angle θ between the normal of the first straight line and the positive direction of the horizontal axis of the rectangular coordinate system i ; The angle is the normal angle of the first straight line; wherein each target point is mapped into a set of curves passing through the point in polar coordinates; in a specific implementation, the n first straight lines contained in the set of adjacent points in the rectangular coordinate system correspond to the n points in the polar coordinate system;

[0054] Figure 3 for Figure 2 Schematic diagram of multiple groups of target point curves corresponding to the target points in the polar coordinate system; wherein each point in the rectangular coordinate system corresponds to a group of curves passing through the target point in the polar coordinate system;

[0055] Figure 4This is an example of the distance r from a straight line to the origin and the angle θ between the normal line of the straight line and the positive direction of the horizontal axis in a rectangular coordinate system; r and θ are used as examples to illustrate the calculation of the distance from a straight line to the origin and the angle between the normal line and the positive direction of the horizontal axis, that is, the calculation of the normal angle:

[0056] in:

[0057]

[0058] Among them, the straight line is a straight line passing through the points (x1, y1) and (x2, y2);

[0059] r i and θ i The calculation of is similar and will not be repeated here;

[0060] According to the r corresponding to each first straight line i and θ i , calculate the average of the n distances from the first n straight lines to the origin of the rectangular coordinate system The average value of the n angles between the normal lines of the n first straight lines and the positive direction of the horizontal axis of the rectangular coordinate system The average value of the distance and the average value of the angle are used as anchor points for subsequent collinear search areas;

[0061] Calculate the difference between the distances of each two of the n first straight lines to the origin of the rectangular coordinate system to obtain a plurality of distance differences and calculate the difference between the angles between the normals of each two of the n first straight lines and the positive direction of the horizontal axis of the rectangular coordinate system to obtain a plurality of angle differences;

[0062] averaging multiple distance differences to obtain an average distance difference; and averaging multiple angle differences to obtain an average angle difference;

[0063] S42, calculating the median of the average distance difference and the median of the average angle difference of the m groups of adjacent points, and excluding a group of adjacent points that meets any one of the following conditions to obtain the remaining p groups of adjacent points, where p is less than or equal to m;

[0064] The difference between the average distance difference and the median of the average distance difference is greater than a predetermined average distance difference threshold; preferably, the absolute difference, i.e., the absolute value of the difference, is used to compare with the predetermined average distance difference threshold;

[0065] The difference between the average angle difference and the median of the average angle difference is greater than a predetermined average angle difference threshold; preferably, the absolute difference, i.e., the absolute value of the difference, is used to compare with the predetermined average angle difference threshold;

[0066] In a specific implementation, the average distance difference and average angle corresponding to each group of adjacent points are sorted in ascending order to obtain the corresponding median, which is used as the length and width of the subsequent collinear search area; and the groupings with a large difference between the average difference and the corresponding difference median are excluded and will not be used later; in this way, the adjacent point groups that are basically not collinear can be excluded first, reducing the subsequent calculation burden;

[0067] S43, for each of the remaining p groups of adjacent points, the average value corresponding to the group of adjacent points is calculated. is the polar diameter, the corresponding average value Get the anchor point of this group of adjacent points in polar coordinates for the polar angle And determine the anchor point region corresponding to the group of adjacent points in polar coordinates by taking the anchor point as the center, the average distance difference corresponding to the group of adjacent points as the length and the corresponding average angle difference as the width, obtain p anchor point regions, and use the p anchor point regions as collinear target search regions; in a specific implementation, the anchor point region is a rectangular region;

[0068] S5, for each of the collinear target search areas, obtain all mapping points contained in the area corresponding to the first straight line in the rectangular coordinate system, and determine the average polar diameter of all mapping points in the area and polar coordinates And pass through the area The target point in the rectangular coordinate system corresponding to the curve is determined as the collinear target point passing through the same straight line, and the same straight line is the point in the polar coordinate system. The corresponding straight line in rectangular coordinates.

[0069] The straight line is:

[0070]

[0071] Figure 5 This is an example of a collinear search area determined in a target point curve in a polar coordinate system using the method of an embodiment of the present invention. Figure 5 and Figure 3 correspond, Figure 5 It contains 3 collinear search areas, where the collinear search areas are schematically shown by small rectangular boxes. Figure 6 Based on Figure 5 The three collinear search areas determined in the above example are the three straight lines found in the rectangular coordinate system. Figure 2 After searching for collinear targets for the target points in , three straight lines are determined by the collinear target points found.

[0072] In the embodiment of the present invention, m and n are positive integers, and p and q are integers greater than or equal to 0.

[0073] Preferably, the embodiment of the present invention further includes a step of de-duplication and fusion of the collinear target search area; in a specific implementation, step S4 includes:

[0074] When there are multiple center points whose distances between the center points are less than a second distance threshold among the p center points corresponding to the p anchor point areas, the anchor point area containing the largest number of mapping points among the multiple anchor point areas corresponding to the multiple center points is retained, and the other anchor point areas among the multiple anchor point areas are deleted to obtain the remaining q anchor point areas, and the q anchor point areas are used as collinear target search areas, where q is less than or equal to p.

[0075] In a specific implementation, the number of mapping points contained in the anchor point area is used as the voting value of the area; when the distance between multiple anchor points is less than a predetermined second distance threshold, the anchor point area with the highest voting value is selected as the collinear target search area, and the other anchor point areas are removed, so as to avoid repeated judgment of collinear target points.

[0076] Embodiment 2:

[0077] The present invention also provides a collinear target search device based on spatial transformation, which includes a processor and a memory, wherein the memory stores at least one program, and the at least one program is executed by the processor to implement the steps of the collinear target search method embodiment as described above.

[0078] In a specific implementation, the above-mentioned co-linear target searching device is a controller, such as a vehicle-mounted controller.

[0079] Embodiment three:

[0080] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method in the embodiment of the present invention are implemented.

[0081] If the module / unit integrated in the computer unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory) and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction.

[0082] Embodiment 4:

[0083] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the method described above are implemented.

[0084] Embodiment five:

[0085] The present invention also provides a method for searching for collinear obstacles, which uses the collinear target searching method described above to search for collinear obstacles; for example, searching for collinear obstacles in a parking lot or on a road.

[0086] Embodiment six:

[0087] The present invention also provides a method for searching for co-linear parking space numbers, characterized in that it uses the co-linear target searching method described above to search for co-linear parking space numbers; for example, searching for co-linear parking space numbers in a parking lot.

[0088] Embodiment seven:

[0089] The present invention also provides a vehicle that uses any of the above-mentioned methods for searching for collinear targets to search for collinear targets.

[0090] Although the present invention has been specifically shown and described in conjunction with the preferred embodiments, it should be understood by those skilled in the art that various changes may be made to the present invention in form and details without departing from the spirit and scope of the present invention as defined by the appended claims, all of which are within the scope of protection of the present invention.

Claims

1. A method for finding collinear targets based on spatial transformation, characterized in that: include: S1, obtain the horizontal and vertical coordinates of multiple target points in a rectangular coordinate system; S2, calculating a first distance between any two target points among the multiple target points according to the obtained horizontal and vertical coordinates; S3, dividing the multiple target points into m groups of adjacent points according to the first distance between any two target points among the multiple target points, wherein the first distance between any two target points included in each group of adjacent points is less than a predetermined first distance threshold; S4, performing polar coordinate system spatial transformation for each of the m groups of adjacent points, and determining a collinear target search area in the polar coordinate system, including: S41, performing the following processing on each of the m groups of adjacent points: Determine the first straight line formed by all target points in the group of adjacent points, and obtain n first straight lines l1 to l n ; Each first straight line l among the n first straight lines i Perform spatial transformation from rectangular coordinate system to polar coordinate system. The first straight line l i The mapping point in the polar coordinate system is: (r i ,θ i ), i = 1, ..., n, where r i is the distance from the first straight line to the origin of the rectangular coordinate system, θ i is the angle θ between the normal of the first straight line and the positive direction of the horizontal axis of the rectangular coordinate system i ; Each target point is mapped into a set of curves passing through the point in polar coordinates; According to the r corresponding to each first straight line i and θ i , calculate the average value of the n distances from the n first straight lines to the origin of the rectangular coordinate system and the average value of the n angles between the normal lines of the n first straight lines and the positive direction of the horizontal axis of the rectangular coordinate system Calculating the difference in distances from each two of the n first straight lines to the origin of the rectangular coordinate system to obtain a plurality of distance differences and calculating the difference in angles between the normals of each two of the n first straight lines and the positive direction of the horizontal axis of the rectangular coordinate system to obtain a plurality of angle differences; averaging the multiple distance differences to obtain an average distance difference; and averaging the multiple angle differences to obtain an average angle difference; S42, calculating the median of the average distance difference and the median of the average angle difference of the m groups of adjacent points, and excluding a group of adjacent points that meets any one of the following conditions to obtain the remaining p groups of adjacent points, where p is less than or equal to m: The difference between the average distance difference and the median of the average distance differences is greater than a predetermined average distance difference threshold; The difference between the average angle difference and the median of the average angle difference is greater than a predetermined average angle difference threshold; S43, for each of the remaining p groups of adjacent points, the average value corresponding to the group of adjacent points is calculated. is the polar diameter, the corresponding average value Determine the anchor point of this group of adjacent points in polar coordinates for the polar angle and determining the anchor point region corresponding to the group of adjacent points in polar coordinates by taking the anchor point as the center, the average distance difference corresponding to the group of adjacent points as the length, and the corresponding average angle difference as the width, to obtain p anchor point regions, and use the p anchor point regions as collinear target search regions; S5, for each of the collinear target search areas, obtain all mapping points contained in the area corresponding to the first straight line in the rectangular coordinate system, and determine the average polar diameter of all mapping points in the area and polar coordinates And pass through the area The target point in the rectangular coordinate system corresponding to the curve is determined as the collinear target point passing through the same straight line, and the same straight line is the point in the polar coordinate system. The corresponding straight line in rectangular coordinates.

2. The method for finding collinear targets according to claim 1, characterized in that: The step S6 further comprises: When there are multiple center points whose distances between the center points are less than a second distance threshold among the p center points corresponding to the p anchor point areas, the anchor point area containing the largest number of mapping points among the multiple anchor point areas corresponding to the multiple center points is retained, and the other anchor point areas among the multiple anchor point areas are deleted to obtain the remaining q anchor point areas, and the q anchor point areas are used as the collinear target search areas, where q is less than or equal to p.

3. The method for finding collinear targets according to claim 1, characterized in that: After step S1 and before step S2, the method further includes a step of normalizing the horizontal and vertical coordinates of the plurality of target points in a rectangular coordinate system.

4. The method for finding collinear targets according to claim 1, characterized in that: Normalizing the horizontal and vertical coordinates of the multiple target points in the rectangular coordinate system includes: determining the smallest horizontal coordinate xmin and the smallest vertical coordinate ymin among the horizontal and vertical coordinates of the multiple target points in the rectangular coordinate system; and subtracting the xmin and ymin from the horizontal and vertical coordinates of the multiple target points in the rectangular coordinate system, respectively, to obtain the relative coordinates of each target point; Wherein, in the step S2, the first distance is calculated according to the relative coordinates of the target points.

5. A method for searching for collinear obstacles, characterized in that: The collinear object searching method according to any one of claims 1 to 4 is used to search for collinear obstacles.

6. A method for searching for a parking space number on a same line, characterized in that: The co-linear target searching method according to any one of claims 1 to 4 is used to search for co-linear parking space numbers.

7. A collinear target search device based on spatial transformation, characterized in that: It comprises a memory and a processor, wherein the memory stores at least one program, and the at least one program is executed by the processor to implement the steps of the co-linear target searching method as claimed in any one of claims 1 to 4.

8. A computer-readable storage medium, characterized in that: The storage medium stores at least one program, and the at least one program is executed by a processor to implement the steps of the co-linear target searching method as described in any one of claims 1 to 4.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the co-linear target searching method as claimed in any one of claims 1 to 4 are implemented.

10. A means of transport, characterized in that: Use the collinear target searching method described in any one of claims 1 to 4 to perform collinear target searching.

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