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

Abstract

The invention discloses a distance calculation method and device based on laser ranging, equipment and a storage medium, and relates to the technical field of laser ranging, and the distance calculation method based on laser ranging comprises the steps: obtaining the sampling data of a laser reflection signal, and obtaining a continuous data segment according to the sampling data; determining a pulse form category according to the continuous data segments; and calculating a distance calculation result according to the pulse form category and the continuous data segment. The distance calculation method is suitable for the two conditions that the laser reflection pulse is Gaussian wave and the laser reflection pulse is saturated, and the distance calculation precision is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of laser ranging, and particularly relates to a distance solving method and device based on laser ranging, equipment and a storage medium. BACKGROUND

[0002] At present, distance solving mainly uses a centroid algorithm or an edge detection algorithm. The centroid algorithm has high detection precision when a laser reflection pulse is a Gaussian wave, but the precision decreases when the laser reflection pulse energy is large and saturation is formed. The edge detection algorithm realizes distance solving by detecting the rising time of a rising edge when the laser reflection pulse energy is large and saturation is formed. Since only the rising edge of the laser reflection pulse is used as a distance detection basis, the detection result of the edge detection algorithm is easily disturbed, and in addition, the precision of the algorithm decreases when the laser reflection pulse is a Gaussian wave. Therefore, how to improve the distance solving precision in laser ranging is still a problem to be solved.

[0003] The above content is only used to assist in understanding the technical solutions of the present application and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0004] The main purpose of the present application is to provide a distance solving method and device based on laser ranging, equipment and a storage medium, aiming at solving the technical problem of how to improve the distance solving precision in laser ranging.

[0005] To achieve the above purpose, the present application provides a distance solving method based on laser ranging, which comprises the following steps:

[0006] Obtaining sampling data of a laser reflection signal, and obtaining a continuous data segment according to the sampling data;

[0007] Determining a pulse form category according to the continuous data segment;

[0008] Calculating a distance solving result according to the pulse form category and the continuous data segment.

[0009] In an embodiment, the step of determining the pulse form category according to the continuous data segment comprises:

[0010] Calculating an energy cumulative sum of the continuous data segment;

[0011] When the energy cumulative sum is greater than a preset judgment threshold, it is determined as a saturated pulse form;

[0012] When the energy cumulative sum is not greater than the preset judgment threshold, it is determined as a Gaussian pulse form.

[0013] In an embodiment, after the step of calculating the energy cumulative sum of the continuous data segment, the method further comprises:

[0014] obtaining a maximum sampling value of the continuous data segment;

[0015] multiplying a preset coefficient with the maximum sampling value to obtain a preset determination threshold.

[0016] In an embodiment, the step of calculating a distance solution result according to the pulse shape category and the continuous data segment comprises:

[0017] when the pulse shape category is a saturated pulse shape, reconstructing the continuous data segment to obtain a target data segment, and calculating a distance solution result according to the target data segment;

[0018] when the pulse shape category is a Gaussian pulse shape, calculating a distance solution result according to the continuous data segment.

[0019] In an embodiment, the step of reconstructing the continuous data segment to obtain a target data segment, and calculating a distance solution result according to the target data segment comprises:

[0020] locating a saturated start position of the continuous data segment, at which a first sampling value reaches the maximum sampling value;

[0021] determining a rising edge sampling point in the continuous data segment according to the saturated start position;

[0022] generating a falling edge sampling point according to the rising edge sampling point;

[0023] obtaining a target data segment according to the rising edge sampling point, the saturated start position, and the falling edge sampling point;

[0024] calculating a distance solution result according to a weighted position of the target data segment and a sampling value total sum.

[0025] In an embodiment, the step of generating a falling edge sampling point according to the rising edge sampling point comprises:

[0026] calculating a difference value between the maximum sampling value and a sampling value of the rising edge sampling point;

[0027] determining a falling edge sampling point according to a number, a position of the rising edge sampling point, and the difference value.

[0028] In an embodiment, the step of calculating a distance solution result according to the continuous data segment comprises:

[0029] calculating a weighted sampling value total sum data of the continuous data segment;

[0030] calculating a sampling value total sum data of the continuous data segment;

[0031] The distance solution result is obtained according to the weighted sampling value sum data and the sampling value sum data.

[0032] In addition, to achieve the above object, the application further provides a distance solution device based on laser ranging, which comprises:

[0033] The acquisition module is configured to acquire sampling data of the laser reflection signal and obtain a continuous data segment according to the sampling data.

[0034] The determination module is configured to determine a pulse shape category according to the continuous data segment.

[0035] The calculation module is configured to calculate a distance solution result according to the pulse shape category and the continuous data segment.

[0036] In addition, to achieve the above object, the application further provides a distance solution device based on laser ranging, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the distance solution method based on laser ranging as described above.

[0037] In addition, to achieve the above object, the application further provides a storage medium, which is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executable by a processor to implement the steps of the distance solution method based on laser ranging as described above.

[0038] In addition, to achieve the above object, the application further provides a computer program product, which comprises a computer program, and the computer program is executable by a processor to implement the steps of the distance solution method based on laser ranging as described above.

[0039] The application provides a distance solution method based on laser ranging, which acquires sampling data of a laser reflection signal, obtains a continuous data segment according to the sampling data, determines a pulse shape category according to the continuous data segment, and calculates a distance solution result according to the pulse shape category and the continuous data segment.

[0040] As can be seen from the above, the application adopts different solution methods for laser data of different pulse shape categories, can maintain high-precision distance solution results in both cases of Gaussian wave and laser reflection pulse saturation, and improves the distance solution accuracy in laser ranging. BRIEF DESCRIPTION OF DRAWINGS

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

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings can also provide other drawings based on these drawings for those skilled in the art without any creative effort.

[0043] Figure 1 A flowchart provided by the first embodiment of the distance resolving method based on laser ranging of the present application;

[0044] Figure 2 A flowchart provided by the second embodiment of the distance resolving method based on laser ranging of the present application;

[0045] Figure 3 A brief flowchart of the distance resolving method based on laser ranging provided by the first embodiment of the present application;

[0046] Figure 4 A module structure diagram of the distance resolving device based on laser ranging of the present application;

[0047] Figure 5 A device structure diagram of the hardware running environment involved in the distance resolving method based on laser ranging in the embodiments of the present application.

[0048] The purpose implementation, functional features and advantages of the present application will be further explained with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0049] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application, and are not used to limit the present application.

[0050] In order to better understand the technical solutions of the present application, the following will be described in detail with reference to the drawings and specific embodiments in the specification.

[0051] The main solution of the present application is to obtain the sampling data of laser reflection signal, to obtain the continuous data segment according to the sampling data, to determine the pulse shape category according to the continuous data segment, and to calculate the distance resolving result according to the pulse shape category and the continuous data segment.

[0052] Currently, the distance calculation mainly uses the centroid algorithm or the edge detection algorithm. The centroid algorithm has high detection accuracy when the laser reflection pulse is a Gaussian wave, but the accuracy decreases when the laser reflection pulse energy is large and saturation is formed. The edge detection algorithm realizes distance calculation by detecting the rising time of the rising edge when the laser reflection pulse energy is large and saturation is formed. Since only the rising edge of the laser reflection pulse is used as the basis for distance detection, the detection result of the edge detection algorithm is easily disturbed, and in addition, the accuracy of the algorithm decreases when the laser reflection pulse is a Gaussian wave. Therefore, how to improve the distance calculation accuracy in laser ranging is still a problem to be solved.

[0053] The present application uses different solving methods for laser data of different pulse shape categories, which can maintain high-precision distance calculation results in both cases of Gaussian wave and laser reflection pulse saturation, and improves the distance calculation accuracy in laser ranging.

[0054] Based on this, the embodiment of the present application provides a distance calculation method based on laser ranging, referring to Figure 1 , Figure 1 The present application is a flowchart of the first embodiment of the distance calculation method based on laser ranging.

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

[0056] Step S10: Obtain the sampling data of the laser reflection signal, and obtain a continuous data segment according to the sampling data;

[0057] It should be noted that the execution subject of the present embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a distance calculation device based on laser ranging, etc. In the following, the distance calculation device based on laser ranging is taken as an example to explain the present embodiment and the following embodiments.

[0058] It should be noted that the laser radar distance calculation algorithm of the present embodiment is based on the time of flight (TOF) technology path, and the input is the sampling 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), n∈[1, N]. The process of obtaining the sampling data of the laser reflection signal and obtaining a continuous data segment according to the sampling data is first to read a segment of the laser reflection signal ADC sampling data, find the laser reflection signal from the sampling data, set the length to M+1, and the positions are m, m+1... m+M in turn, so the number of sampling points on the continuous data segment is M+1.

[0059] Step S20: determining a pulse shape category according to the continuous data segment;

[0060] It can be understood that the pulse shape category is divided into Gaussian pulse shape and saturated pulse shape, and the pulse shape category can be determined according to the maximum value and total energy of the sampling points in the continuous data segment.

[0061] In one possible implementation, the step of determining the pulse shape category according to the continuous data segment includes: calculating an energy cumulative sum of the continuous data segment; determining the saturated pulse shape when the energy cumulative sum is greater than a preset determination threshold; and determining the Gaussian pulse shape when the energy cumulative sum is not greater than the preset determination threshold.

[0062] It can be understood that the energy cumulative sum of the continuous data segment is calculated, that is, the energy of each sampling point in the continuous data segment is calculated and added, and the formula is:

[0063] E=y(m)+y(m+1)+…+y(m+M)

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

[0065] The saturated pulse shape is determined when the energy cumulative sum is greater than a preset determination threshold, and the Gaussian pulse shape is determined when the energy cumulative sum is not greater than the preset determination threshold. The preset determination threshold is K*P, where K is a parameter, and K is usually 5, 6 or 7 according to experience, and P is the maximum value of the ADC sampling. The saturated pulse shape is determined when E is greater than K*P, and the Gaussian pulse shape is determined when E is not greater than K*P.

[0066] Step S30: calculating a distance solution result according to the pulse shape category and the continuous data segment.

[0067] It can be understood that when the pulse shape category is the Gaussian pulse shape, the energy is not saturated, and the energy of the sampling points in the continuous data segment can be directly used to calculate the distance solution result. When the pulse shape category is the saturated pulse shape, the saturated sampling point data cannot be used, and needs to be reconstructed, and the reconstructed data is used to calculate the distance solution result.

[0068] The embodiment provides a distance solution method based on laser ranging. The application obtains sampling data of a laser reflection signal, obtains a continuous data segment according to the sampling data, determines a pulse shape category according to the continuous data segment, and calculates a distance solution result according to the pulse shape category and the continuous data segment.

[0069] In conclusion, the embodiment adopts different solving methods for laser data of different pulse shape categories, can keep high-precision distance solving results in both cases of Gaussian wave and laser reflection pulse saturation, and improves the distance solving precision in laser ranging.

[0070] Based on the first embodiment, in the second embodiment, the same or similar contents as the above-mentioned first embodiment can be referred to the above description, and the subsequent description will not be repeated. On this basis, please refer to Figure 2 , and the step S30 further includes steps S301-S302.

[0071] Step S301: when the pulse shape category is a saturated pulse shape, reconstructing the continuous data segment to obtain a target data segment, and calculating a distance solving result according to the target data segment.

[0072] It can be understood that the reconstruction process can be performed according to the unsaturated sampling point data in the continuous data segment.

[0073] In one possible way, the step of reconstructing the continuous data segment to obtain a target data segment and calculating a distance solving result according to the target data segment includes: locating a first saturated starting position in the continuous data segment that reaches a maximum sampling value; determining a rising edge sampling point in the continuous data segment according to the saturated starting position; generating a falling edge sampling point according to the rising edge sampling point; obtaining a target data segment according to the rising edge sampling point, the saturated starting position and the falling edge sampling point; and obtaining a distance solving result according to the weighted position of the target data segment and the total sum of sampling values.

[0074] It can be understood that the first saturated starting position in the continuous data segment that reaches the maximum sampling value is found, that is, the first saturated point in the continuous data segment is found, and from this saturated point, the subsequent sampling points are discarded and reconstructed, at this time, the remaining sampling points are the rising edge sampling points, and the formula for reconstructing the falling edge sampling points according to the rising edge sampling points is:

[0075] y(m+K+W)=P-y(m+W)

[0076] Wherein, 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 in step S20, m is the position of the first sampling point, and W is a self-increment variable, and each time a falling edge sampling point is reconstructed, W is added 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, and the falling edge sampling point is determined according to the number, position and difference of the rising edge sampling point, that is, the result of subtracting the first rising edge sampling point from the maximum energy is taken as the energy of the first falling edge sampling point, the result of subtracting the second rising edge sampling point from the maximum energy is taken as the energy of the second falling edge sampling point, and so on until all rising edge sampling points are used up, and the complete falling edge sampling point is obtained, so the number of falling edge sampling points is the same as the number of rising edge sampling points.

[0077] It can be understood that when the reconstructed target data segment is obtained, the distance calculation result can be obtained according to the weighted position sum of the target data segment and the sampling value sum. 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] Wherein, Z is the sampling value sum, z is the weighted position sum of the target data segment, and L is the centroid position of the pulse waveform. After the centroid position L is known, the distance can be calculated using the conversion principle of TOF.

[0082] Step S302: When the pulse form category is a Gaussian pulse form, the distance calculation result is calculated according to the continuous data segment.

[0083] It can be understood that when the pulse form category is a Gaussian pulse form, the continuous data segment can be directly calculated without reconstruction.

[0084] In a feasible manner, the step of calculating the distance calculation result according to the continuous data segment comprises: calculating the weighted sampling value sum data of the continuous data segment; calculating the sampling value sum data of the continuous data segment; and obtaining the distance calculation result according to the weighted sampling value sum data and the sampling value sum data.

[0085] It can be understood that the sampling point data of the continuous data segment can be directly used for calculation, and the formula is:

[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 is the total sampled value, z is the weighted sampled value, and L is the centroid of the pulse waveform. Once the centroid L is known, the distance can be calculated using the TOF conversion principle.

[0090] In this embodiment, when the pulse shape type is a saturated pulse shape, the continuous data segments are reconstructed to obtain a target data segment, and the distance solution result is calculated based on the target data segment. When the pulse shape type is a Gaussian pulse shape, the distance solution result is calculated based on the continuous data segments. This embodiment reconstructs the saturated pulse to obtain more accurate falling edge sampling points, calculate more accurate distance, and improve the distance solution accuracy in laser ranging.

[0091] For example, in order to help understand the implementation process of the distance calculation method based on laser ranging obtained by combining this embodiment with the above embodiment 1, please refer to Figure 3 , Figure 3 A brief flow chart of a distance calculation method based on laser ranging is provided. Specifically, the method comprises the following steps: first, reading a segment of ADC sampling data of a laser reflection signal; second, finding the laser reflection signal with a length of M+1 and positions at m, m+1..., m+M; third, calculating E=y(m)+y(m+1)+...+y(m+M); fourth, setting the maximum value of the ADC sampling to P, setting parameter K (selecting 5, 6, or 7), and setting V=1; fifth, judging whether E is greater than K*P; if so, proceeding to step 6; otherwise, calculating 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 calculating z / Z, and the process ends. Step 6, read y(m+V); Step 7, determine whether y(m+V) is equal to P, if so, continue to execute step 8, otherwise let V=V+1, and return to step 6 to restart execution; Step 8, set W=1; Step 9, let y(m+K+W)=Py(m+W); Step 10, determine whether W+1 is equal to V, if so, continue to execute step 11, otherwise let W=W+1, and return to step 9 to restart execution; 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 the present application and do not constitute a limitation on the distance calculation method based on laser ranging of the present application. Further simple transformations based on this technical concept are within the protection scope of the present application.

[0093] The present application also provides a distance calculation device based on laser ranging, which refers to Figure 4 The distance calculation device based on laser ranging comprises:

[0094] The acquisition module 10 is configured to acquire sampling data of a laser reflection signal, and obtain a continuous data segment according to the sampling data.

[0095] The determination module 20 is configured to determine a pulse shape category according to the continuous data segment.

[0096] The calculation module 30 is configured to calculate a distance calculation result according to the pulse shape category and the continuous data segment.

[0097] The present embodiment provides a distance calculation method based on laser ranging. The present application acquires sampling data of a laser reflection signal, and obtains a continuous data segment according to the sampling data. A pulse shape category is determined according to the continuous data segment. A distance calculation result is calculated according to the pulse shape category and the continuous data segment.

[0098] As can be seen from the above, the present embodiment adopts different calculation methods for laser data of different pulse shape categories, and can maintain high-precision distance calculation results in both cases of Gaussian wave and saturated laser reflection pulse, thereby improving the distance calculation precision in laser ranging.

[0099] In an embodiment, the determination module 20 is further configured to calculate an energy accumulation sum of the continuous data segment. When the energy accumulation sum is greater than a preset determination threshold, it is determined as a saturated pulse shape. When the energy accumulation sum is not greater than the preset determination threshold, it is determined as a Gaussian pulse shape.

[0100] In an embodiment, the determination module 20 is further configured to acquire a maximum sampling value of the continuous data segment. A preset coefficient is multiplied by the maximum sampling value to obtain a preset determination threshold.

[0101] In an embodiment, the calculation module 30 is further configured to, when the pulse shape category is a saturated pulse shape, reconstruct the continuous data segment to obtain a target data segment, and calculate a distance calculation result according to the target data segment. When the pulse shape category is a Gaussian pulse shape, a distance calculation result is calculated according to the continuous data segment.

[0102] In an embodiment, the computing module 30 is further configured to locate a saturation start position of a first sample value reaching a maximum sample value in the continuous data segment; determine a rising edge sampling point in the continuous data segment according to the saturation start position; generate a falling edge sampling point according to the rising edge sampling point; obtain a target data segment according to the rising edge sampling point, the saturation start position and the falling edge sampling point; and obtain a distance solution result according to a weighted position of the target data segment and a sample value sum.

[0103] In an embodiment, the computing module 30 is further configured to calculate a difference between the maximum sample value and a sample value of the rising edge sampling point; and determine a falling edge sampling point according to a number, a position of the rising edge sampling point and the difference.

[0104] In an embodiment, the computing module 30 is further configured to calculate a weighted sample value sum data of the continuous data segment; calculate a sample value sum data of the continuous data segment; and obtain a distance solution result according to the weighted sample value sum data and the sample value sum data.

[0105] The distance solution device based on laser ranging provided in the application adopts the distance solution method based on laser ranging in the above embodiments, and can solve the technical problem of how to improve the distance solution accuracy in laser ranging. Compared with the prior art, the distance solution device based on laser ranging provided in the application has the same beneficial effects as the distance solution method based on laser ranging provided in the above embodiments, and other technical features in the distance solution device based on laser ranging are the same as the features disclosed in the above embodiments, which will not be repeated here.

[0106] The application provides a distance solution device based on laser ranging, which comprises at least one processor and a memory connected with the at least one processor; 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 distance solution method based on laser ranging in the above embodiment one.

[0107] The following will be described with reference to the drawings Figure 5, which shows a schematic structural diagram of a distance calculation device based on laser ranging suitable for implementing the embodiments of the present application. The distance calculation device based on laser ranging in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The distance calculation device based on laser ranging shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0108] like Figure 5 As shown, the distance calculation device based on laser ranging may include a processing device 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 a ROM (Read Only Memory) 1002 or a program loaded from a storage device 1003 into a RAM (Random Access Memory) 1004. The RAM 1004 also stores various programs and data required for the operation of the distance calculation device based on laser ranging. The processing device 1001, ROM 1002, and RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. The communication devices 1009 can allow the laser ranging-based distance calculation device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a laser ranging-based distance calculation device with various systems, it should be understood that implementation or presence of all the illustrated systems is not required. More or fewer systems may alternatively be implemented or present.

[0109] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program codes for executing the method shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network through a communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiments disclosed in the present application are executed.

[0110] The distance resolving device based on laser ranging provided in the present application adopts the distance resolving method based on laser ranging in the above-mentioned embodiments, and can solve the technical problem of how to improve the distance resolving precision in laser ranging. Compared with the prior art, the distance resolving device based on laser ranging provided in the present application has the same beneficial effects as the distance resolving method based on laser ranging provided in the above-mentioned embodiments, and other technical features in the distance resolving device based on laser ranging are the same as the features disclosed in the above-mentioned embodiments, which will not be repeated here.

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

[0112] The above is merely specific embodiments of the present application, and the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0113] The present application provides a computer readable storage medium having stored thereon computer readable program instructions (i.e. computer program) for executing the distance resolving method based on laser ranging in the above-mentioned embodiments.

[0114] The computer readable storage medium provided in the application may, for example, be a U disk, but is not limited to an electric, magnetic, optical, electromagnetic, infrared, or semiconductor system, system, or device, or any combination thereof. More specific examples of the computer readable storage medium may include, but are not limited to, an electric connection with one or more conductive wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the embodiment, the computer readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system, or device. The program code contained on the computer readable storage medium can be transmitted by any suitable medium, including but not limited to an electric wire, an optical cable, an RF (Radio Frequency), and the like, or any suitable combination thereof.

[0115] The computer readable storage medium described above may be contained in a laser ranging-based distance resolving device, or may exist separately without being assembled into the laser ranging-based distance resolving device.

[0116] The computer readable storage medium described above carries one or more programs, when the one or more programs are executed by the laser ranging-based distance resolving device, the laser ranging-based distance resolving device is caused to: acquire sampling data of a laser reflection signal, obtain a continuous data segment according to the sampling data; determine a pulse shape category according to the continuous data segment; and calculate a distance resolving result according to the pulse shape category and the continuous data segment.

[0117] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can 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 the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0118] The flow diagrams and the block diagrams in the drawings are illustrations of architectures, functionalities, and operations of possible implementations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flow diagrams or block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may

[0119] The modules involved in the embodiments of the present application can be implemented in the form of software or in the form of hardware. In some cases, the name of the module does not constitute a limitation on the module itself.

[0120] The readable storage medium provided by the present application is a computer readable storage medium, which stores computer readable program instructions (i.e., a computer program) for executing the above-mentioned laser ranging-based distance calculation method, and can solve the technical problem of how to improve the distance calculation accuracy in laser ranging. Compared with the prior art, the computer readable storage medium provided by the present application has the same beneficial effects as the laser ranging-based distance calculation method provided by the above-mentioned embodiments, which will not be described here.

[0121] The application further provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the laser ranging-based distance resolving method as described above.

[0122] The computer program product provided by the application can solve the technical problem of how to improve the distance resolving accuracy in laser ranging. Compared with the prior art, the beneficial effects of the computer program product provided by the application are the same as those of the laser ranging-based distance resolving method provided by the above-described embodiments, and are not described herein.

[0123] The above only describes some embodiments of the application, and does not limit the patent scope of the application. Any equivalent structural transformation, direct / indirect application in other related technical fields, or the like made by using the content of the application specification and drawings is included in the patent protection scope of the application.

Claims

1. A distance calculation method based on laser ranging, characterized in that: The method includes: Acquiring sampling data of the laser reflection signal, and obtaining continuous data segments according to the sampling data; determining a pulse morphology category based on the continuous data segments; A distance solution result is calculated based on the pulse shape category and the continuous data segment.

2. The method according to claim 1, wherein The step of determining the pulse shape category according to the continuous data segments comprises: Calculating the cumulative energy of the continuous data segments; When the energy accumulation sum is greater than a preset judgment threshold, it is determined to be a saturation pulse form; When the energy accumulation sum is not greater than a preset determination threshold, it is determined to be a Gaussian pulse shape.

3. The method according to claim 2, wherein After calculating the energy accumulation sum of the continuous data segments, the method further includes: Obtaining the maximum sampling value of the continuous data segment; The preset coefficient is multiplied by the maximum sampling value to obtain a preset determination threshold.

4. The method according to claim 1, wherein The step of calculating the distance solution result according to the pulse shape category and the continuous data segment includes: When the pulse shape category is a saturated pulse shape, reconstructing the continuous data segment to obtain a target data segment, and calculating a distance solution result based on the target data segment; When the pulse shape category is a Gaussian pulse shape, the distance solution result is calculated based on the continuous data segments.

5. The method according to claim 4, wherein The step of reconstructing the continuous data segments to obtain target data segments and calculating the distance solution result according to the target data segments comprises: Locating the first saturation starting position that reaches the maximum sampling value in the continuous data segment; Determine a rising edge sampling point in the continuous data segment according to the saturation starting position; Generate a falling edge sampling point according to the rising edge sampling point; Obtain a target data segment according to the rising edge sampling point, the saturation starting position, and the falling edge sampling point; The distance calculation result is obtained according to the weighted position sum of the target data segment and the sum of the sampling values.

6. The method according to claim 5, wherein The step of generating a falling edge sampling point according to the rising edge sampling point comprises: Calculating the difference between the maximum sampling value and the sampling value of the rising edge sampling point; The falling edge sampling point is determined according to the number and position of the rising edge sampling points and the difference.

7. The method according to claim 4, wherein The step of calculating the distance solution result according to the continuous data segments comprises: Calculating weighted sampling value sum data of the continuous data segments; Calculating the sum of the sampling values ​​of the continuous data segments; A distance calculation result is obtained according to the weighted sampling value sum data and the sampling value sum data.

8. A distance calculation device based on laser ranging, characterized in that: The device comprises: an acquisition module, configured to acquire sampling data of the laser reflection signal and obtain continuous data segments according to the sampling data; a determination module, configured to determine a pulse shape category based on the continuous data segments; A calculation module is used to calculate a distance solution result according to the pulse shape category and the continuous data segment.

9. 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, wherein the computer program is configured to implement the steps of the distance calculation method based on laser ranging according to any one of claims 1 to 7.

10. 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, the distance calculation method based on laser ranging according to any one of claims 1 to 7 is implemented.

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