A method for filtering and interpolating single-line laser radar isolated point data

Abstract

The invention relates to the technical field of laser radar data processing, and discloses a single-line laser radar isolated point data filtering and interpolation method, comprising: executing a spot area comparison strategy; obtaining laser radar single-circle scanning distance data at each angle; calculating the angle formed by the current angle data point, the previous angle position point, and the origin in sequence, except for the first and last data points; comparing the angle calculated in the previous step with a set threshold value, if it is less than the threshold value, dividing the point into a data cluster with the same value as the previous position point, if it is greater than or equal to the threshold value, constructing a new data cluster, and comparing each point in sequence until the current circle of data ends; scanning the constructed data clusters in sequence, for a cluster with 1 data in the data cluster, determining that the point is an isolated point or a trailing point; comparing the data clusters before and after the isolated point cluster, if the isolated point is convex outward, filtering it out and performing interpolation processing on the isolated point according to the state of the previous and previous data clusters, and if the isolated point is concave inward, the point can be selected not to be processed or data interpolation is performed.

Description

Technical Field

[0001] The present invention relates to the technical field of laser radar data processing, and in particular to a single-line laser radar isolated point data filtering and interpolation method. Background Art

[0002] Laser radar is a radar system that emits laser beams to detect the position, speed and other characteristic quantities of the target. In terms of working principle, there is no fundamental difference from microwave radar: a detection signal (laser beam) is emitted to the target, and then the received signal reflected from the target (target echo) is compared with the emitted signal. After appropriate processing, relevant information about the target can be obtained, such as target distance, direction, height, speed, attitude, and even shape parameters, so as to detect, track and identify targets such as aircraft and missiles. Laser radar is a device that uses the principle of diffuse reflection of light for real-time ranging. Under ideal conditions, the laser pulse is a point when it contacts the surface of a reflective object, and part of the light signal is reflected back according to the reflectivity of the surface of the object. The distance between the object and the laser radar is calculated using the time of flight method.

[0003] Ideally, the pulse hitting the surface of the object is an ideal light spot, but because the actual pulse has a certain divergence angle, it will hit the object as a surface, and this surface will become larger as the distance increases. However, when there are two objects in front and behind, for the light spot hitting the edge of the front object, part of the laser energy will hit the rear object, causing a tailing phenomenon. If the reflectivity of the object surface is low and the object to be measured is far away from the radar, there will be a jump in the ranging data at this angle, forming an isolated point (outlier). The existence of these abnormal points reduces the accuracy of ranging and modeling, and brings difficulties to subsequent point cloud processing. Summary of the invention

[0004] The present invention provides a single-line laser radar isolated point data filtering and interpolation method, which is not limited to the application in the data preprocessing stage of the MCU inside the laser radar or the industrial computer ROS laser radar driver. It can quickly filter out isolated points or trailing points and perform effective interpolation processing, effectively reducing the jump problem of ranging data.

[0005] The present invention provides the following technical solution: a single-line laser radar isolated point data filtering and interpolation method, comprising:

[0006] Step 1: Execute the spot area comparison strategy;

[0007] Step 2: According to the laser radar ranging accuracy, set the angle threshold β for determining outlier trailing points at different distances j ;

[0008] Step 3: The laser radar uses the time-of-flight ranging method to obtain real-time angle ranging information, and forms a complete data cluster with a complete circle of data, which is then passed into the proposed processing method;

[0009] Step 4: Scan the incoming original data cluster, exclude the first and last points in the data cluster, and calculate the currently selected point P for other points in the data cluster. m , the previous angle position point P m-1 , the angle θ formed by the origin O i ;

[0010] Step 5: According to the angle threshold β set in step 2 j The angle θ calculated in step 4 i Make comparisons;

[0011] If the angle θ i Less than the angle threshold β j , then the angle θ i The corresponding position point is divided into the same data cluster as the previous position point;

[0012] If the angle θ i Greater than the angle threshold β j , then create a new data cluster;

[0013] Compare each point in turn until the data of this circle ends, forming a data cluster group C consisting of N data clusters N ;

[0014] Step 6: Scan data cluster group C in sequence N If C k The number of data contained is 1, then the data cluster C is determined k The points P included m It is an isolated point, a trailing point or an outlier point;

[0015] Step 7: Compare the point P m Data cluster C k The data clusters before and after, namely C k-1 and C k+1 ;

[0016] If the isolated point is convex outward, it will be filtered out and interpolated according to the state of the previous and next data clusters;

[0017] If the isolated point is concave inward, the point can be selected without processing or data interpolation;

[0018] As an optional solution of the single-line laser radar isolated point data filtering and interpolation method of the present invention, the execution of the spot area comparison strategy includes:

[0019] Get the number of echoes received by the laser radar, recorded as N;

[0020] If the number N = 2, the spot area formed by the pulse emitted by the laser radar hitting the surface of the front object is obtained and is defined as the front spot area;

[0021] Obtain the spot area formed when the pulse emitted by the laser radar hits the surface of the rear object, which is defined as the rear spot area;

[0022] Sort the front spot area and the rear spot area from large to small according to the numerical value;

[0023] The area with the largest value is defined as the maximum spot area, and the area with the smallest value is defined as the minimum spot area;

[0024] If the maximum spot area ≥ the minimum spot area × (1 + 20%), the object corresponding to the maximum spot area is determined to be the measurement object;

[0025] Then the echo length returned by the object corresponding to the maximum spot area is the measurement distance;

[0026] If the maximum spot area is less than the minimum spot area × (1 + 20%), the distance from the laser radar to the front object and the distance from the laser radar to the rear object are obtained, which are recorded as d1 and d2 respectively;

[0027] Calculate the difference between distance d2 and distance d1, recorded as D, difference D = distance d2 - distance d1;

[0028] If the difference D ≥ distance d1×(1+50%), the rear object is determined to be the measurement object;

[0029] Then the length of the echo returned by the object behind is the measured distance;

[0030] If the difference D is less than the distance d1×(1+50%), then execute step 2-7.

[0031] As an optional scheme for the single-line laser radar isolated point data filtering and interpolation method described in the present invention, wherein: in step 2, different trailing point comparison thresholds are set according to different distances, and the number of threshold settings is determined according to the radar ranging accuracy and angular resolution.

[0032] As an optional solution to the single-line laser radar isolated point data filtering and interpolation method described in the present invention, wherein: in step 3, the laser radar single-circle scanning distance data at each angle is obtained to form a raw data cluster, and the distance data is not limited to the raw data collected in the MCU or the ranging data received by the ROS laser radar driver in the industrial computer.

[0033] As an optional solution of the single-line laser radar isolated point data filtering and interpolation method of the present invention, wherein: the angle θ in step 4 is iIt can be calculated based on the front and back distance values ​​using the cosine theorem.

[0034] As an optional solution to the single-line laser radar isolated point data filtering and interpolation method described in the present invention, the interpolation method described in step 7 is not limited to the linear interpolation method using the front and back data clusters.

[0035] As an optional scheme for the single-line laser radar isolated point data filtering and interpolation method described in the present invention, wherein: an angle comparison threshold is set according to the actual performance of the laser radar, and the set threshold is used to screen isolated points.

[0036] As an optional solution to the single-line laser radar isolated point data filtering and interpolation method described in the present invention, the original ranging data of the laser radar scanning device is obtained and used to calculate relevant parameters.

[0037] As an optional solution to the single-line laser radar isolated point data filtering and interpolation method described in the present invention, point cloud data clusters and data cluster groups are constructed, and the constructed isolated point data clusters are filtered and interpolated.

[0038] As an optional scheme for the single-line laser radar isolated point data filtering and interpolation method described in the present invention, the MCU or industrial computer implements the above-mentioned data filtering and interpolation process when executing the program, and the processed data is not limited to isolated points, tailing points, and outliers. The process can be repeated once or multiple times depending on the effect.

[0039] The present invention has the following beneficial effects:

[0040] 1. The single-line laser radar isolated point data filtering and interpolation method improves the conventional laser radar trailing point judgment method, adds the concept of data clustering, and clusters the original data according to the threshold method. It can effectively distinguish continuous data from isolated point data, which is beneficial to screening isolated point data and interpolating the position.

[0041] 2. The single-line lidar isolated point data filtering and interpolation method identifies and analyzes the data clusters before and after the isolated point cluster position, and resets the isolated point data by comparing the cluster data continuity and linear interpolation, thereby ensuring data integrity while reducing data jump problems.

[0042] 3. The single-line laser radar isolated point data filtering and interpolation method is not limited to the preprocessing stage in the MCU and industrial computer ROS laser radar driver. It can perform one or more data processing according to the effect to improve the precision and accuracy of the point cloud and provide reliable guarantee for subsequent point cloud processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a block diagram of the single-line laser radar isolated point data filtering and interpolation method of the present invention;

[0044] Figure 2 It is a schematic diagram of the front spot area and the rear spot area of ​​the present invention;

[0045] Figure 3 This is a schematic diagram of the angle of the selected point according to the present invention;

[0046] Figure 4 This is a schematic diagram of data filtering and linear interpolation according to the present invention;

[0047] Figure 5 This is the test result 1 of the example described in the present invention;

[0048] Figure 6 This is the test result 2 of the example described in the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] like Figure 1 As shown, the single-line laser radar isolated point data filtering and interpolation method in this embodiment includes:

[0051] Step 1: Execute the spot area comparison strategy;

[0052] Among them, the spot area comparison strategy is executed, specifically including:

[0053] Get the number of echoes received by the laser radar, recorded as N;

[0054] If the number N = 2, such as Figure 2 As shown, the spot area formed when the pulse emitted by the laser radar hits the surface of the front object is obtained and is defined as the front spot area;

[0055] Obtain the spot area formed when the pulse emitted by the laser radar hits the surface of the rear object, which is defined as the rear spot area;

[0056] Sort the front spot area and the rear spot area from large to small according to the numerical value;

[0057] The area with the largest value is defined as the maximum spot area, and the area with the smallest value is defined as the minimum spot area;

[0058] If the maximum spot area ≥ the minimum spot area × (1 + 20%), it means that there is a certain difference between the spot area formed on the surface of the front object and the spot area formed on the surface of the rear object, then the object corresponding to the maximum spot area is determined to be the measurement object;

[0059] Then the echo length returned by the object corresponding to the maximum spot area is the measurement distance;

[0060] If the maximum spot area is less than the minimum spot area × (1 + 20%), it means that the spot area formed on the surface of the front object and the spot area formed on the surface of the rear object are small and negligible or have no difference, then the distance from the laser radar to the front object and the distance from the laser radar to the rear object are obtained, which are recorded as d1 and d2 respectively;

[0061] Calculate the difference between distance d2 and distance d1, recorded as D, difference D = distance d2 - distance d1;

[0062] If the difference D ≥ distance d1×(1+50%), it indicates that the distance between the front object and the rear object is greatly different, and the rear object is determined to be the measurement object;

[0063] Then the length of the echo returned by the object behind is the measured distance;

[0064] If the difference D is less than the distance d1×(1+50%), it indicates that the distance difference between the front object and the rear object is small, then execute step 2-7;

[0065] Step 2: According to the laser radar ranging accuracy and angular resolution, set the angle threshold β for determining outlier trailing points at different distances j In this example, two groups of detection upper and lower thresholds are set, as shown in the following table:

[0066]

[0067] Step 3: The laser radar uses the time-of-flight ranging method to obtain real-time angle ranging information, and forms a complete data cluster with a complete circle of data, which is passed into the proposed processing method. The host computer driver receives the real-time ranging data sent by the laser radar. The laser radar scanning angle is 200° and the scanning angle interval is 0.5°.

[0068] Step 4: Scan the incoming original data cluster, exclude the first and last points in the data cluster, and calculate the currently selected point P for other points in the data cluster. m , the previous angle position point P m-1 , the angle θ formed by the origin O i , where m represents the currently selected position point, and i represents the angle position formed, such as Figure 3 As shown;

[0069] Step 5: According to the angle threshold β set in step 2 j The angle θ calculated in step 4 i Make comparisons;

[0070] If the angle θ i Less than the angle threshold β j , then the angle θ i The corresponding position point is divided into the same data cluster as the previous position point;

[0071] If the angle θ i Greater than the angle threshold β j , then create a new data cluster;

[0072] Compare each point in turn until the data of this circle ends, forming a data cluster group C consisting of N data clusters N ;

[0073] Step 6: Scan data cluster group C in sequence N If C k The number of data contained is 1, then the data cluster C is determined k The points P included m It is an isolated point, a trailing point or an outlier point;

[0074] Step 7: Compare the point P m Data cluster C k The data clusters before and after, namely C k-1 and C k+1 ;

[0075] If the isolated point is convex outward, it will be filtered out and interpolated according to the state of the previous and next data clusters;

[0076] If the isolated point is concave inward, you can choose not to process the point or interpolate the data, such as Figure 4 As shown, P, m are the values ​​interpolated based on the previous and next data clusters using linear processing;

[0077] Step 8: According to steps 2-7, encapsulate it into a callable algorithm and deploy it in the receiving and display host computer.

[0078] Test results such as Figure 5 , Figure 6As shown, the present invention improves the commonly used trailing point judgment method of laser radar, adds the concept of data clustering, and performs clustering processing on the original data according to the threshold method, which can effectively distinguish continuous data from isolated point data, which is beneficial to screening isolated point data and identifying and processing the position; by identifying and analyzing the data clusters before and after the isolated point cluster position, the isolated point data is reset by using cluster data continuity comparison and linear interpolation, thereby ensuring data integrity while reducing data jump problems; the present invention is not limited to the preprocessing stage in the MCU and industrial computer ROS laser radar driver, and can perform one or more data processing according to the effect, so as to improve the precision and accuracy of the point cloud, and provide a reliable guarantee for subsequent point cloud processing.

[0079] The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as laptop computers, PADs (tablet computers), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and the like, as well as fixed terminals.

[0080] Electronic devices may include processing devices (e.g., central processing units, graphics processing units, etc.), which may perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) or programs loaded from a storage device into a random access memory (RAM). In RAM, various programs and data required for the operation of the electronic device are also stored. The processing device, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0081] Typically, the following devices may be connected to the I / O interface: input devices including, for example, a touch screen, a touch pad, an image sensor, a microphone, etc.; output devices including, for example, a liquid crystal display (LCD), a speaker, etc.; storage devices including, for example, a magnetic tape, a hard disk, etc.; and communication devices. The communication devices may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data.

[0082] The embodiments of the present disclosure also provide a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute the single-line laser radar isolated point data filtering and interpolation method in the aforementioned method embodiment.

[0083] It should be noted that more specific examples of computer-readable storage media may include portable computer disks, hard disks, erasable programmable read-only memories (EPROMs or flash memories), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present disclosure, computer-readable storage media may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device, and the computer-readable medium may be contained in the electronic device; or it may exist independently without being assembled into the electronic device.

[0084] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device can implement the solution provided by the method embodiment.

[0085] Computer program code for performing operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, and may be executed entirely on a user's computer, partially on a user's computer, as a stand-alone software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0086] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0087] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A single-line laser radar isolated point data filtering and interpolation method, the laser scanner raw data is input, and the isolated point tailing data filtering and interpolation method is used to process the data. The proposed processing method is characterized by: include: Step 1: Execute the spot area comparison strategy; The implementation of the spot area comparison strategy includes: Get the number of echoes received by the laser radar, recorded as N; If the number N=2, the spot area formed by the pulse emitted by the laser radar hitting the surface of the front object is obtained and is defined as the front spot area; Obtain the spot area formed when the pulse emitted by the laser radar hits the surface of the rear object, which is defined as the rear spot area; Sort the front spot area and the rear spot area from large to small according to the numerical value; The area with the largest value is defined as the maximum spot area, and the area with the smallest value is defined as the minimum spot area; If the maximum spot area ≥ the minimum spot area × (1 + 20%), the object corresponding to the maximum spot area is determined to be the measurement object; Then the echo length returned by the object corresponding to the maximum spot area is the measurement distance; If the maximum spot area is less than the minimum spot area × (1 + 20%), the distance from the laser radar to the front object and the distance from the laser radar to the rear object are obtained, which are recorded as d1 and d2 respectively; Calculate the difference between distance d2 and distance d1, recorded as D, difference D = distance d2 - distance d1; If the difference D ≥ distance d1×(1+50%), the object behind is determined to be the measurement object; Then the length of the echo returned by the object behind is the measured distance; If the difference D < distance d1×(1+50%), execute steps 2-7; Step 2: According to the laser radar ranging accuracy, set the angle threshold β for determining outlier trailing points at different distances j ; Step 3: The laser radar uses the time-of-flight ranging method to obtain real-time angle ranging information, and forms a complete data cluster with a complete circle of data, which is then passed into the proposed processing method; Step 4: Scan the incoming original data cluster, exclude the first and last points in the data cluster, and calculate the currently selected point P for other points in the data cluster. m , the previous angle position point P m-1 , the angle θ formed by the origin O i ; Step 5: According to the angle threshold β set in step 2 j The angle θ calculated in step 4 i Make comparisons; If the angle θ i Less than the angle threshold β j , then the angle θ i The corresponding position point is divided into the same data cluster as the previous position point; If the angle θ i Greater than the angle threshold β j , then create a new data cluster; Compare each point in turn until the data of this circle ends, forming a data cluster group C consisting of N data clusters N ; Step 6: Scan data cluster group C in sequence N If C k The number of data contained is 1, then the data cluster C is determined k The points P included m It is an isolated point, a trailing point or an outlier point; Step 7: Compare the point P m Data cluster C k The data clusters before and after, namely C k-1 and C k+1 ; If the isolated point is convex outward, it will be filtered out and interpolated according to the state of the previous and next data clusters; If the isolated point is concave inward, you can choose not to process the point.

2. The single-line laser radar isolated point data filtering and interpolation method according to claim 1, characterized in that: In step 2, different trailing point comparison thresholds are set according to different distances, and the number of threshold settings is determined according to the radar ranging accuracy and angular resolution.

3. The single-line laser radar isolated point data filtering and interpolation method according to claim 1, characterized in that: In step 3, the distance data of the laser radar single-circle scanning at each angle is obtained to form a raw data cluster. The distance data is not limited to the raw data collected in the MCU or the ranging data received by the ROS laser radar driver in the industrial computer.

4. The single-line laser radar isolated point data filtering and interpolation method according to claim 3, characterized in that: The angle θ described in step 4 i It can be calculated based on the front and back distance values ​​using the cosine theorem.

5. The single-line laser radar isolated point data filtering and interpolation method according to claim 1, characterized in that: The interpolation method described in step 7 is not limited to the linear interpolation method using the previous and next data clusters.

6. The single-line laser radar isolated point data filtering and interpolation method according to claim 2, characterized in that: The angle comparison threshold is set according to the actual performance of the lidar, and the set threshold is used to screen out isolated points.

7. The single-line laser radar isolated point data filtering and interpolation method according to claim 4, characterized in that: The original ranging data of the laser radar scanning device is obtained and used to calculate relevant parameters.

8. The single-line laser radar isolated point data filtering and interpolation method according to claim 5, characterized in that: Construct point cloud data clusters and data cluster groups, and perform filtering and interpolation processing on the constructed isolated point data clusters.

9. The single-line laser radar isolated point data filtering and interpolation method according to any one of claims 1 to 8, characterized in that: The MCU or industrial computer implements the above data filtering and interpolation process when executing the program. The processed data is not limited to isolated points, tailing points, and outliers. The process can be repeated once or multiple times depending on the effect.

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