Distance resolving method and device based on laser ranging, equipment and storage medium

Abstract

The application discloses a distance resolving method and device based on laser ranging, equipment and a storage medium, relates to the technical field of laser ranging, and the distance resolving method based on laser ranging comprises the following steps: acquiring sampling data of a laser reflection signal, obtaining a continuous data segment according to the sampling data; determining a pulse shape category according to the continuous data segment; and calculating a distance resolving result according to the pulse shape category and the continuous data segment. The distance resolving method of the application is applicable to both the cases that the laser reflection pulse is a Gaussian wave and the laser reflection pulse is saturated, and the distance resolving precision is improved.

Description

Technical Field

[0001] This application relates to the field of laser ranging technology, and in particular to a distance calculation method, apparatus, device, and storage medium based on laser ranging. Background Technology

[0002] Currently, distance calculation mainly uses centroid algorithms or edge detection algorithms. Centroid algorithms have high detection accuracy when the laser reflection pulse is a Gaussian wave, but their accuracy decreases when the laser reflection pulse energy is high and saturation occurs. Edge detection algorithms calculate distance by detecting the rise time of the rising edge when the laser reflection pulse energy is high and saturation occurs. However, since only the rising edge of the laser reflection pulse is used as the basis for distance detection, the detection results of edge detection algorithms are easily affected by interference. Furthermore, the accuracy of this algorithm decreases when the laser reflection pulse is a Gaussian wave. Therefore, how to improve the accuracy of distance calculation in laser ranging remains a problem that needs to be solved.

[0003] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main objective of this application is to provide a distance calculation method, apparatus, device, and storage medium based on laser ranging, aiming to solve the technical problem of how to improve the distance calculation accuracy in laser ranging.

[0005] To achieve the above objectives, this application proposes a distance calculation method based on laser ranging, the method comprising:

[0006] Acquire sampling data of the laser reflection signal, and obtain continuous data segments based on the sampling data;

[0007] The pulse pattern category is determined based on the continuous data segments;

[0008] The distance calculation result is calculated based on the pulse pattern category and the continuous data segment.

[0009] In one embodiment, the step of determining the pulse pattern category based on the continuous data segments includes:

[0010] Calculate the cumulative energy of the continuous data segments;

[0011] When the sum of the energy exceeds a preset threshold, it is determined to be a saturated pulse pattern.

[0012] When the sum of the energy is not greater than a preset threshold, it is determined to be a Gaussian pulse.

[0013] In one embodiment, after calculating the cumulative energy of the consecutive data segments, the method further includes:

[0014] Obtain the maximum sample value of the continuous data segment;

[0015] Multiply the preset coefficient by the maximum sample value to obtain the preset judgment threshold.

[0016] In one embodiment, the step of calculating the distance solution based on the pulse pattern category and the continuous data segment includes:

[0017] When the pulse pattern type is a saturated pulse pattern, the continuous data segment is reconstructed to obtain the target data segment, and the distance calculation result is calculated based on the target data segment.

[0018] When the pulse pattern type is Gaussian pulse pattern, the distance calculation result is calculated based on the continuous data segment.

[0019] In one embodiment, the step of reconstructing the continuous data segment to obtain the target data segment, and calculating the distance solution result based on the target data segment includes:

[0020] Locate the saturation start position of the first segment in the continuous data segment that reaches the maximum sampling value;

[0021] The rising edge sampling point in the continuous data segment is determined based on the saturation start position;

[0022] A falling edge sampling point is generated based on the rising edge sampling point;

[0023] The target data segment is obtained based on the rising edge sampling point, the saturation start position, and the falling edge sampling point;

[0024] The distance calculation result is obtained by summing the weighted positions of the target data segment and the total of the sampled values.

[0025] In one embodiment, the step of generating a falling edge sampling point based on the rising edge sampling point includes:

[0026] Calculate the difference between the maximum sampled value and the sampled value at the rising edge sampling point;

[0027] The falling edge sampling point is determined based on the number and location of the rising edge sampling points and the difference.

[0028] In one embodiment, the step of calculating the distance solution result based on the continuous data segment includes:

[0029] Calculate the weighted sum of the sampled values ​​of the continuous data segment;

[0030] Calculate the sum of the sampled values ​​of the continuous data segment;

[0031] The distance calculation result is obtained based on the weighted sum of sampled values ​​and the sum of sampled values.

[0032] Furthermore, to achieve the above objectives, this application also proposes a distance calculation device based on laser ranging, the laser ranging-based distance calculation device comprising:

[0033] The acquisition module is used to acquire sampled data of the laser reflection signal and obtain continuous data segments based on the sampled data;

[0034] The determining module is used to determine the pulse pattern category based on the continuous data segment;

[0035] The calculation module is used to calculate the distance solution based on the pulse pattern category and the continuous data segment.

[0036] In addition, to achieve the above objectives, this application also proposes a distance calculation device based on laser ranging, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the distance calculation method based on laser ranging as described above.

[0037] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the laser ranging-based distance calculation method described above.

[0038] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the laser ranging-based distance calculation method described above.

[0039] This application provides a distance calculation method based on laser ranging. The method involves acquiring sampling data of laser reflection signals, obtaining continuous data segments based on the sampling data, determining pulse pattern categories based on the continuous data segments, and calculating distance calculation results based on the pulse pattern categories and the continuous data segments.

[0040] In summary, this application employs different calculation methods for laser data with different pulse morphology types, which can maintain high-precision distance calculation results in both cases where the laser reflection pulse is Gaussian and the laser reflection pulse is saturated, thereby improving the distance calculation accuracy in laser ranging. Attached Figure Description

[0041] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0042] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart illustrating an embodiment of the distance calculation method based on laser ranging in this application.

[0044] Figure 2 This is a flowchart illustrating Embodiment 2 of the distance calculation method based on laser ranging in this application;

[0045] Figure 3 A simplified flowchart illustrating the distance calculation method based on laser ranging provided in Embodiment 1 of this application;

[0046] Figure 4 This is a schematic diagram of the module structure of the distance calculation device based on laser ranging according to an embodiment of this application;

[0047] Figure 5 This is a schematic diagram of the device structure of the hardware operating environment involved in the distance calculation method based on laser ranging in the embodiments of this application.

[0048] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0049] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0050] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0051] The main solution of this application is to acquire sampling data of laser reflection signals, obtain continuous data segments based on the sampling data, determine the pulse pattern category based on the continuous data segments, and calculate the distance solution result based on the pulse pattern category and the continuous data segments.

[0052] Currently, distance calculation mainly uses centroid algorithms or edge detection algorithms. Centroid algorithms have high detection accuracy when the laser reflection pulse is a Gaussian wave, but their accuracy decreases when the laser reflection pulse energy is high and saturation occurs. Edge detection algorithms calculate distance by detecting the rise time of the rising edge when the laser reflection pulse energy is high and saturation occurs. However, since only the rising edge of the laser reflection pulse is used as the basis for distance detection, the detection results of edge detection algorithms are easily affected by interference. Furthermore, the accuracy of this algorithm decreases when the laser reflection pulse is a Gaussian wave. Therefore, how to improve the accuracy of distance calculation in laser ranging remains a problem that needs to be solved.

[0053] This application employs different calculation methods for laser data with different pulse morphology categories, which can maintain high-precision distance calculation results in both cases where the laser reflection pulse is Gaussian and the laser reflection pulse is saturated, thereby improving the distance calculation accuracy in laser ranging.

[0054] Based on this, embodiments of this application provide a distance calculation method based on laser ranging, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the distance calculation method based on laser ranging in this application.

[0055] In this embodiment, the distance calculation method based on laser ranging includes steps S10 to S30:

[0056] Step S10: Obtain sampling data of the laser reflection signal, and obtain continuous data segments based on the sampling data;

[0057] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device capable of performing the above functions, such as a laser ranging-based distance calculation device. The following description uses a laser ranging-based distance calculation device as an example to illustrate this embodiment and the subsequent embodiments.

[0058] It should be noted that the lidar distance calculation algorithm in this embodiment is based on the time-of-flight (TOF) ranging method, with the input being samples of the laser reflection signal. The sampling frequency is f, the total number of sampling points is N, and the amplitude of each sampling point is y(n), where n∈[1,N]. The process of acquiring the sampled data of the laser reflection signal and obtaining a continuous data segment based on the sampled data first involves reading the analog-to-digital converter (ADC) sampling data from a segment of the laser reflection signal, finding the laser reflection signal from the sampled data, setting its length to M+1, and then assigning the positions m, m+1, ..., m+M in sequence. Therefore, the number of sampling points on the continuous data segment is M+1.

[0059] Step S20: Determine the pulse pattern category based on the continuous data segments;

[0060] Understandably, pulse patterns are categorized into Gaussian pulse patterns and saturated pulse patterns, and the pulse pattern category can be determined based on the maximum sampling value and total energy of the continuous data segment.

[0061] In one feasible approach, the step of determining the pulse pattern category based on the continuous data segment includes: calculating the cumulative energy of the continuous data segment; when the cumulative energy is greater than a preset threshold, determining it as a saturated pulse pattern; when the cumulative energy is not greater than the preset threshold, determining it as a Gaussian pulse pattern.

[0062] Understandably, calculating the cumulative energy of the continuous data segment involves calculating and summing the energy of each sampling point on the continuous data segment, using the following formula:

[0063] E = y(m) + y(m+1) + ... + y(m+M)

[0064] E represents the cumulative energy, and y(m) represents the energy at the sampling point at position m.

[0065] When the accumulated energy exceeds a preset threshold, it is determined to be a saturated pulse pattern; when the accumulated energy does not exceed the preset threshold, it is determined to be a Gaussian pulse pattern. The preset threshold is K*P, where K is a parameter, typically 5, 6, or 7 based on experience, and P is the maximum value sampled by the ADC. When E is greater than K*P, it is determined to be a saturated pulse pattern; when E is not greater than K*P, it is determined to be a Gaussian pulse pattern.

[0066] Step S30: Calculate the distance solution result based on the pulse pattern category and the continuous data segment.

[0067] Understandably, when the pulse pattern is Gaussian, the energy is not saturated, and the energy of the sampling points on the continuous data segment can be used directly to calculate the distance solution. However, when the pulse pattern is saturated, the saturated sampling point data is unusable and needs to be reconstructed. The reconstructed data is then used to calculate the distance solution.

[0068] This embodiment provides a distance calculation method based on laser ranging. This application acquires sampling data of laser reflection signals, obtains continuous data segments based on the sampling data, determines the pulse pattern category based on the continuous data segments, and calculates the distance calculation result based on the pulse pattern category and the continuous data segments.

[0069] In summary, this embodiment employs different calculation methods for laser data with different pulse morphology types, which can maintain high-precision distance calculation results in both cases where the laser reflection pulse is Gaussian and the laser reflection pulse is saturated, thereby improving the distance calculation accuracy in laser ranging.

[0070] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 Step S30 also includes steps S301 to S302:

[0071] Step S301: When the pulse pattern type is a saturated pulse pattern, the continuous data segment is reconstructed to obtain the target data segment, and the distance calculation result is calculated based on the target data segment;

[0072] Understandably, the reconstruction process can be performed based on unsaturated sample point data in a continuous data segment.

[0073] In one feasible approach, the step of reconstructing the continuous data segment to obtain a target data segment and calculating the distance solution result based on the target data segment includes: locating the first saturation start position in the continuous data segment that reaches the maximum sampling value; determining the rising edge sampling point in the continuous data segment based on the saturation start position; generating falling edge sampling points based on the rising edge sampling points; obtaining the target data segment based on the rising edge sampling points, the saturation start position, and the falling edge sampling points; and obtaining the distance solution result based on the weighted position sum and the sum of the sampling values ​​of the target data segment.

[0074] Understandably, the saturation starting position of the first sampled value reaching the maximum value in the continuous data segment is located, i.e., the first saturation point in the continuous data segment is found. Starting from this saturation point, all subsequent sampled points are discarded and reconstructed. The remaining sampled points are the rising edge sampled points. The formula for reconstructing the falling edge sampled points from the rising edge sampled points is:

[0075] y(m+K+W)=Py(m+W)

[0076] Where y(m+K+W) is the energy of the reconstructed falling edge sampling point, P is the maximum value of the ADC sampling, y(m+W) is the energy of the rising edge sampling point, K is the parameter mentioned in step S20, m is the position of the first sampling point, and W is an incrementing variable. Each time a falling edge sampling point is reconstructed, W is incremented by 1 until all falling edge sampling points are reconstructed. As can be seen from the formula, the difference between the maximum sampling value and the sampling value of the rising edge sampling point is calculated. Based on the number and position of the rising edge sampling points and the difference, the falling edge sampling point is determined. That is, the energy of the first falling edge sampling point is obtained by subtracting the energy of the first rising edge sampling point from the maximum energy value, and the energy of the second falling edge sampling point is obtained by subtracting the energy of the second rising edge sampling point from the maximum energy value, and so on, until all rising edge sampling points are used up, resulting in a complete set of falling edge sampling points. Therefore, the number of falling edge sampling points is the same as the number of rising edge sampling points.

[0077] Understandably, once the reconstructed target data segment is obtained, the distance calculation result can be obtained based on the weighted sum of the target data segment's positions and the sum of the sampled values. The formula is:

[0078] Z = y(m) + y(m+1) + ... + y(m+K+W)

[0079] z=m*y(m)+(m+1)*y(m+1)+…+(m+K+W))*y(m+K+W)

[0080] L = z / Z

[0081] Where Z is the sum of the sampled values, z is the weighted sum of the positions of the target data segment, and L is the centroid position of the pulse waveform. Once the centroid position L is known, the distance can be calculated using the Time-of-Flight (TOF) conversion principle.

[0082] Step S302: When the pulse pattern type is Gaussian pulse pattern, the distance calculation result is calculated based on the continuous data segment.

[0083] Understandably, when the pulse pattern type is a Gaussian pulse pattern, it can be calculated directly from the continuous data segments without reconstruction.

[0084] In one feasible approach, the step of calculating the distance solution result based on the continuous data segment includes: calculating the weighted sum of sampled values ​​of the continuous data segment; calculating the sum of sampled values ​​of the continuous data segment; and obtaining the distance solution result based on the weighted sum of sampled values ​​and the sum of sampled values.

[0085] Understandably, the calculation can be performed directly using the sampled data points from the continuous data segment, as shown in the formula:

[0086] Z = y(m) + y(m+1) + ... + y(m+M)

[0087] z=m*y(m)+(m+1)*y(m+1)+...+(m+M)*y(m+M)

[0088] L = z / Z

[0089] Where Z represents the total number of sampled values, z represents the weighted sum of sampled values, and L represents the centroid position of the pulse waveform. Once the centroid position L is known, the distance can be calculated using the Time-of-Flight (TOF) conversion principle.

[0090] In this embodiment, when the pulse pattern is a saturated pulse, the continuous data segment is reconstructed to obtain the target data segment, and the distance calculation result is calculated based on the target data segment. When the pulse pattern is a Gaussian pulse, the distance calculation result is calculated based on the continuous data segment. This embodiment reconstructs the saturated pulse to obtain more accurate falling edge sampling points, calculates a more accurate distance, and improves the distance calculation accuracy in laser ranging.

[0091] For example, to help understand the implementation process of the laser ranging-based distance calculation method obtained in this embodiment combined with the above embodiment one, please refer to... Figure 3 , Figure 3 A simplified flowchart of a distance calculation method based on laser ranging is provided. Specifically: First, read a segment of laser reflection signal ADC sampling data; Second, locate the laser reflection signal with length M+1 and position at m, m+1, ..., m+M; Third, calculate E = y(m) + y(m+1) + ... + y(m+M); Fourth, the maximum value of the ADC sampling is P, and parameter K is set (choose 5, 6, or 7), and V = 1; Fifth, determine whether E is greater than K*P. If it is, continue to the sixth step; otherwise, calculate Z = y(m) + y(m+1) + ... + y(m+M) and z = m*y(m) + (m+1)*y(m+1) + ... + (m+M)*y(m+M), and calculate z / Z. The process ends. Step 6: Read y(m+V); Step 7: Determine if y(m+V) equals P. If it does, continue to Step 8; otherwise, set V = V+1 and return to Step 6 to start executing again; Step 8: Set W = 1; Step 9: Set y(m+K+W) = Py(m+W); Step 10: Determine if W+1 equals V. If it does, continue to Step 11; otherwise, set W = W+1 and return to Step 9 to start executing again; Step 11: Calculate Z = y(m) + y(m+1) + ... + y(m+K+W); Step 12: Calculate z = m*y(m) + (m+1)*y(m+1) + ... + (m+K+W))*y(m+K+W); Step 13: Calculate z / Z, and the process ends.

[0092] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the distance calculation method based on laser ranging in this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0093] This application also provides a distance calculation device based on laser ranging, please refer to... Figure 4 The distance calculation device based on laser ranging includes:

[0094] The acquisition module 10 is used to acquire sampled data of the laser reflection signal and obtain continuous data segments based on the sampled data;

[0095] Determining module 20 is used to determine the pulse pattern category based on the continuous data segment;

[0096] The calculation module 30 is used to calculate the distance solution result based on the pulse pattern category and the continuous data segment.

[0097] This embodiment provides a distance calculation method based on laser ranging. This application acquires sampling data of laser reflection signals, obtains continuous data segments based on the sampling data, determines the pulse pattern category based on the continuous data segments, and calculates the distance calculation result based on the pulse pattern category and the continuous data segments.

[0098] In summary, this embodiment employs different calculation methods for laser data with different pulse morphology types, which can maintain high-precision distance calculation results in both cases where the laser reflection pulse is Gaussian and the laser reflection pulse is saturated, thereby improving the distance calculation accuracy in laser ranging.

[0099] In one embodiment, the determining module 20 is further configured to calculate the energy sum of the continuous data segments; when the energy sum is greater than a preset determination threshold, it is determined to be a saturated pulse pattern; when the energy sum is not greater than the preset determination threshold, it is determined to be a Gaussian pulse pattern.

[0100] In one embodiment, the determining module 20 is further configured to obtain the maximum sample value of the continuous data segment; and multiply the preset coefficient by the maximum sample value to obtain a preset judgment threshold.

[0101] In one embodiment, the calculation module 30 is further configured to reconstruct the continuous data segment to obtain a target data segment when the pulse pattern type is a saturated pulse pattern, and calculate the distance solution result based on the target data segment; when the pulse pattern type is a Gaussian pulse pattern, calculate the distance solution result based on the continuous data segment.

[0102] In one embodiment, the calculation module 30 is further configured to locate the first saturation start position in the continuous data segment that reaches the maximum sampling value; determine the rising edge sampling point in the continuous data segment based on the saturation start position; generate the falling edge sampling point based on the rising edge sampling point; obtain the target data segment based on the rising edge sampling point, the saturation start position, and the falling edge sampling point; and obtain the distance calculation result based on the weighted position sum and the sum of the sampling values ​​of the target data segment.

[0103] In one embodiment, the calculation module 30 is further configured to calculate the difference between the maximum sample value and the sample value of the rising edge sample point; and determine the falling edge sample point based on the number and position of the rising edge sample points and the difference.

[0104] In one embodiment, the calculation module 30 is further configured to calculate the weighted sum of sampled values ​​of the continuous data segment; calculate the sum of sampled values ​​of the continuous data segment; and obtain a distance calculation result based on the weighted sum of sampled values ​​and the sum of sampled values.

[0105] The laser ranging-based distance calculation device provided in this application employs the laser ranging-based distance calculation method described in the above embodiments, and can solve the technical problem of how to improve the distance calculation accuracy in laser ranging. Compared with the prior art, the beneficial effects of the laser ranging-based distance calculation device provided in this application are the same as those of the laser ranging-based distance calculation method provided in the above embodiments, and other technical features in the laser ranging-based distance calculation device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0106] This application provides a laser ranging-based distance calculation device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the laser ranging-based distance calculation method in the above embodiment 1.

[0107] The following is for reference. Figure 5This document illustrates a schematic diagram of a laser ranging-based distance calculation device suitable for implementing embodiments of this application. The laser ranging-based distance calculation device in these embodiments may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 5 The laser ranging-based distance calculation device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0108] like Figure 5 As shown, the laser ranging-based distance calculation device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the laser ranging-based distance calculation device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the laser-based distance calculation device to communicate wirelessly or wiredly with other devices to exchange data. Although laser-based distance calculation devices with various systems are shown in the figures, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0109] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0110] The laser ranging-based distance calculation device provided in this application, employing the laser ranging-based distance calculation method described in the above embodiments, can solve the technical problem of how to improve the distance calculation accuracy in laser ranging. Compared with the prior art, the beneficial effects of the laser ranging-based distance calculation device provided in this application are the same as those of the laser ranging-based distance calculation method provided in the above embodiments, and other technical features of this laser ranging-based distance calculation device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0111] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0112] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0113] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the laser ranging-based distance calculation method in the above embodiments.

[0114] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0115] The aforementioned computer-readable storage medium may be included in a laser ranging-based distance calculation device; or it may exist independently and not assembled into a laser ranging-based distance calculation device.

[0116] The aforementioned computer-readable storage medium carries one or more programs that, when executed by a laser ranging-based distance calculation device, cause the laser ranging-based distance calculation device to: acquire sampled data of a laser reflection signal; obtain continuous data segments based on the sampled data; determine pulse pattern categories based on the continuous data segments; and calculate distance calculation results based on the pulse pattern categories and the continuous data segments.

[0117] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0118] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0119] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0120] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned laser ranging-based distance calculation method, thereby solving the technical problem of how to improve the distance calculation accuracy in laser ranging. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the laser ranging-based distance calculation method provided in the above embodiments, and will not be repeated here.

[0121] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the laser ranging-based distance calculation method described above.

[0122] The computer program product provided in this application can solve the technical problem of how to improve the distance calculation accuracy in laser ranging. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the laser ranging-based distance calculation method provided in the above embodiments, and will not be repeated here.

[0123] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A distance calculation method based on laser ranging, characterized in that, The method includes: Acquire sampling data of the laser reflection signal, and obtain continuous data segments based on the sampling data; The pulse pattern category is determined based on the continuous data segments; The distance calculation result is calculated based on the pulse pattern category and the continuous data segment; The step of calculating the distance solution result based on the pulse pattern category and the continuous data segment includes: When the pulse pattern type is a saturated pulse pattern, the continuous data segment is reconstructed to obtain the target data segment, and the distance calculation result is calculated based on the target data segment. The steps of reconstructing the continuous data segment to obtain the target data segment and calculating the distance solution result based on the target data segment include: Locate the saturation start position of the first segment in the continuous data segment that reaches the maximum sampling value; The rising edge sampling point in the continuous data segment is determined based on the saturation start position; A falling edge sampling point is generated based on the rising edge sampling point; The target data segment is obtained based on the rising edge sampling point, the saturation start position, and the falling edge sampling point; The distance calculation result is obtained by summing the weighted positions of the target data segment and the total of the sampled values.

2. The method as described in claim 1, characterized in that, The step of determining the pulse pattern category based on the continuous data segment includes: Calculate the cumulative energy of the continuous data segments; When the sum of the energy exceeds a preset threshold, it is determined to be a saturated pulse pattern. When the sum of the energy is not greater than a preset threshold, it is determined to be a Gaussian pulse.

3. The method as described in claim 2, characterized in that, After calculating the cumulative energy of the continuous data segments, the method further includes: Obtain the maximum sample value of the continuous data segment; Multiply the preset coefficient by the maximum sample value to obtain the preset judgment threshold.

4. The method as described in claim 1, characterized in that, The step of calculating the distance solution result based on the pulse pattern category and the continuous data segment includes: When the pulse pattern type is Gaussian pulse pattern, the distance calculation result is calculated based on the continuous data segment.

5. The method as described in claim 1, characterized in that, The step of generating a falling edge sampling point based on the rising edge sampling point includes: Calculate the difference between the maximum sampled value and the sampled value at the rising edge sampling point; The falling edge sampling point is determined based on the number and location of the rising edge sampling points and the difference.

6. The method as described in claim 4, characterized in that, The step of calculating the distance solution result based on the continuous data segment includes: Calculate the weighted sum of the sampled values ​​of the continuous data segment; Calculate the sum of the sampled values ​​of the continuous data segment; The distance calculation result is obtained based on the weighted sum of sampled values ​​and the sum of sampled values.

7. A distance calculation device based on laser ranging, characterized in that, The device includes: The acquisition module is used to acquire sampled data of the laser reflection signal and obtain continuous data segments based on the sampled data; The determining module is used to determine the pulse pattern category based on the continuous data segment; The calculation module is used to calculate the distance solution result based on the pulse pattern category and the continuous data segment; The step of calculating the distance solution result based on the pulse pattern category and the continuous data segment includes: When the pulse pattern type is a saturated pulse pattern, the continuous data segment is reconstructed to obtain the target data segment, and the distance calculation result is calculated based on the target data segment. The steps of reconstructing the continuous data segment to obtain the target data segment and calculating the distance solution result based on the target data segment include: Locate the saturation start position of the first segment in the continuous data segment that reaches the maximum sampling value; The rising edge sampling point in the continuous data segment is determined based on the saturation start position; A falling edge sampling point is generated based on the rising edge sampling point; The target data segment is obtained based on the rising edge sampling point, the saturation start position, and the falling edge sampling point; The distance calculation result is obtained by summing the weighted positions of the target data segment and the total of the sampled values.

8. A distance calculation device based on laser ranging, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the laser ranging-based distance calculation method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the distance calculation method based on laser ranging as described in any one of claims 1 to 6.

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