Radar simulation method and device in snowfall weather, computer equipment and storage medium

Abstract

The invention relates to a radar simulation method and device in snowfall weather, computer equipment and a storage medium. The method comprises the following steps: acquiring environment point cloud data obtained by performing point cloud data acquisition on an acquisition environment by a laser radar; wherein the collection environment is a target space environment in preset snowfall weather; acquiring reference receiving power of the simulation radar in a simulation snowfall environment corresponding to the acquisition environment; wherein the simulation radar is a simulation model of the laser radar; and according to the environment point cloud data and the reference receiving power, determining target point cloud data obtained by carrying out point cloud data acquisition on the acquisition environment by the laser radar. By adopting the method, data enhancement can be performed on the environmental point cloud data by simulating the reference receiving power of the radar in the simulated snowfall environment corresponding to the collection environment, and the accuracy of the environmental point cloud data is improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a radar simulation method, device, computer equipment and storage medium in snowy weather. Background Art

[0002] With the continuous advancement and development of science and technology, autonomous driving technology has become an important part of the intelligent transportation system. It can provide safer, more convenient and more efficient options for human travel. In the current automotive autonomous driving applications, lidar, as an active detection sensor, has become an indispensable part of today's high-level autonomous driving technology due to its accurate ranging accuracy and distance-based perception method. In severe weather conditions, it is challenging to locate targets from low-quality images. At the same time, collecting laser point cloud data in severe weather such as rain and snow requires waiting for suitable weather conditions. In addition, the annotation of noise points in the point cloud is also a labor-intensive and low-precision task. Therefore, the data of lidar point clouds under severe weather is relatively missing and is in urgent need of supplementation. Summary of the invention

[0003] Based on this, it is necessary to provide a radar simulation method, device, computer equipment and storage medium in snowy weather that can accurately measure radar data in snowy weather in response to the above technical problems.

[0004] In a first aspect, the present application provides a radar simulation method in snowy weather, comprising:

[0005] Acquire environmental point cloud data obtained by laser radar collecting point cloud data of a collection environment; wherein the collection environment is a target space environment in a preset snowy weather;

[0006] Obtaining a reference received power of a simulated radar in a simulated snowfall environment corresponding to a collection environment; wherein the simulated radar is a simulation model of a laser radar;

[0007] According to the environmental point cloud data and the reference receiving power, the target point cloud data obtained by the laser radar through point cloud data collection of the collection environment is determined.

[0008] In one of the embodiments, in a simulated snowfall environment, a plurality of simulated snow particles are used to simulate snowfall weather; accordingly, obtaining a reference received power of a simulated radar in a simulated snowfall environment corresponding to the acquisition environment includes:

[0009] Controlling the simulated radar to obtain the particle receiving power of each simulated snow particle in the simulated snowfall environment;

[0010] Determining the target received power of the corresponding simulated snow particles according to the preset initial received power and the particle received power of each simulated snow particle;

[0011] According to the received power of each target, the reference received power of the simulated radar is determined.

[0012] In one embodiment, obtaining the particle receiving power of each simulated snow particle in a simulated snowfall environment includes:

[0013] For each simulated snow particle, determining the particle receiving power of the snow particle according to the power impact data of the simulated snow particle;

[0014] Among them, the power impact data include reflectivity, reflection angle and detection distance; different simulated snow particles correspond to different detection distances.

[0015] In one embodiment, determining the particle receiving power of the snow particles according to the power impact data of the simulated snow particles includes:

[0016] Determine the reflection response time of the snow particles according to the reflectivity, reflection angle and detection distance of the simulated snow particles;

[0017] The particle receiving power of the snow particles is determined based on the reflection response time of the snow particles and the transmit power of the simulated radar.

[0018] In one embodiment, determining the reflection response time of snow particles according to the reflectivity, reflection angle and detection distance includes:

[0019] Determine the particle response time of the snow particles based on the reflectivity, reflection angle and detection distance;

[0020] The product value between the particle response time and the preset laser response time is used as the reflection response time of the snow particles.

[0021] In one embodiment, determining target point cloud data obtained by collecting point cloud data of a collection environment by a laser radar according to the environment point cloud data and the reference receiving power includes:

[0022] Obtain snow particle sampling data in the collection environment;

[0023] According to the snow particle sampling data and the reference receiving power, the snowfall point cloud data under the collection environment is determined;

[0024] The snowfall point cloud data and the environmental point cloud data are fused to obtain the target point cloud data obtained by the lidar collecting point cloud data of the collection environment.

[0025] In a second aspect, the present application also provides a radar simulation device in snowy weather, comprising:

[0026] A data acquisition module is used to acquire environmental point cloud data obtained by the laser radar performing point cloud data acquisition on the acquisition environment; wherein the acquisition environment is a target space environment in a preset snowy weather;

[0027] A power acquisition module is used to simulate the reference received power of the radar in a simulated snowfall environment corresponding to the acquisition environment; wherein the simulated radar is a simulation model of a laser radar;

[0028] The data determination module is used to determine the target point cloud data obtained by the laser radar through point cloud data collection on the collection environment according to the environmental point cloud data and the reference receiving power.

[0029] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0030] Acquire environmental point cloud data obtained by laser radar collecting point cloud data of a collection environment; wherein the collection environment is a target space environment in a preset snowy weather;

[0031] Obtaining a reference received power of a simulated radar in a simulated snowfall environment corresponding to a collection environment; wherein the simulated radar is a simulation model of a laser radar;

[0032] According to the environmental point cloud data and the reference receiving power, the target point cloud data obtained by the laser radar through point cloud data collection of the collection environment is determined.

[0033] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0034] Acquire environmental point cloud data obtained by laser radar collecting point cloud data of a collection environment; wherein the collection environment is a target space environment in a preset snowy weather;

[0035] Obtaining a reference received power of a simulated radar in a simulated snowfall environment corresponding to a collection environment; wherein the simulated radar is a simulation model of a laser radar;

[0036] According to the environmental point cloud data and the reference receiving power, the target point cloud data obtained by the laser radar through point cloud data collection of the collection environment is determined.

[0037] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0038] Acquire environmental point cloud data obtained by laser radar collecting point cloud data of a collection environment; wherein the collection environment is a target space environment in a preset snowy weather;

[0039] Obtaining a reference received power of a simulated radar in a simulated snowfall environment corresponding to a collection environment; wherein the simulated radar is a simulation model of a laser radar;

[0040] According to the environmental point cloud data and the reference receiving power, the target point cloud data obtained by the laser radar through point cloud data collection of the collection environment is determined.

[0041] The above radar simulation method, device, computer equipment and storage medium in snowy weather obtain environmental point cloud data obtained by laser radar collecting point cloud data of the collection environment; wherein the collection environment is a target space environment in preset snowy weather; obtain the reference receiving power of the simulated radar in the simulated snowfall environment corresponding to the collection environment; wherein the simulated radar is a simulation model of the laser radar; according to the environmental point cloud data and the reference receiving power, determine the target point cloud data obtained by the laser radar collecting point cloud data of the collection environment. This application enhances the environmental point cloud data by simulating the reference receiving power of the radar in the simulated snowfall environment corresponding to the collection environment, thereby improving the accuracy of the environmental point cloud data. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 A diagram showing an application environment of a radar simulation method in snowy weather provided by this embodiment;

[0044] Figure 2 A schematic diagram of the flow of the first radar simulation method in snowy weather provided in this embodiment;

[0045] Figure 3 A schematic diagram of the operation of a simulated radar in a simulated snowfall environment provided in this embodiment;

[0046] Figure 4 A schematic diagram of point cloud simulation visualization provided in this embodiment;

[0047] Figure 5 A structural block diagram of a radar simulation device in snowy weather provided in this embodiment;

[0048] Figure 6 This is a diagram of the internal structure of a computer device provided in this embodiment. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0050] The radar simulation method under snowy weather provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The computer device obtains the environmental point cloud data obtained by the laser radar for collecting point cloud data of the collection environment; wherein the collection environment is a target space environment in a preset snowfall weather; obtains the reference receiving power of the simulation radar in the simulated snowfall environment corresponding to the collection environment; wherein the simulation radar is a simulation model of the laser radar; according to the environmental point cloud data and the reference receiving power, the target point cloud data obtained by the laser radar for collecting point cloud data of the collection environment is determined. Among them, the computer device can be either a terminal or a server. The terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0051] In an exemplary embodiment, Figure 2 As shown, a radar simulation method under snowy weather is provided, and the method is applied to Figure 1 The computer device in the example is used to illustrate, including the following steps 201 to 203. Among them:

[0052] Step 201, obtaining environmental point cloud data obtained by laser radar collecting point cloud data of the collection environment.

[0053] Among them, the collection environment is the target space environment under preset snowy weather.

[0054] Specifically, the computer device communicates with the laser radar to obtain environmental point cloud data obtained by collecting point cloud data of the collection environment from the laser radar.

[0055] Step 202, obtaining a reference received power of the simulated radar in a simulated snowfall environment corresponding to the acquisition environment.

[0056] Among them, the simulated radar is a simulation model of the laser radar.

[0057] Specifically, the computer device sets a simulated radar and a simulated snowfall environment corresponding to the collection environment; the simulated radar is set in the simulated snowfall environment corresponding to the collection environment, and a reference received power of the simulated radar in the simulated snowfall environment corresponding to the collection environment is obtained.

[0058] It should be noted that the method for determining the simulated snowfall environment corresponding to the acquisition environment can be: pre-processing the environmental point cloud data (including: point cloud segmentation, point cloud coloring, etc.), obtaining the environmental characteristics of the target space environment (such as ground, buildings and vegetation, etc.), and constructing the scene terrain model corresponding to the environmental point cloud data according to the environmental characteristics; from the environmental point cloud data, find the area where the condensed snow is formed in the scene, and use a technology similar to object segmentation to separate it and generate a snow attachment model; based on the snow attachment model and the environmental point cloud data, generate a simulated snowfall environment corresponding to the acquisition environment. Finally, the movement and accumulation process of snow can be simulated by using a physical snow layer modeling method, such as the GPU-accelerated physics engine Avalanche and DEM (Digital Elevation Model) model, or by using a computational fluid dynamics method based on Euler solution, such as the SPH (Smoothed Particle Hydrodynamics) method.

[0059] Step 203, determining the target point cloud data obtained by the laser radar performing point cloud data collection on the collection environment according to the environmental point cloud data and the reference receiving power.

[0060] Specifically, reference point cloud data obtained by the laser radar through point cloud data collection on the collection environment is determined according to the reference receiving power; feature fusion is performed based on the environmental point cloud data and the reference point cloud data, and the feature fusion result is used as the target point cloud data obtained by the laser radar through point cloud data collection on the collection environment.

[0061] The above radar simulation method in snowy weather obtains environmental point cloud data obtained by laser radar collecting point cloud data of the collection environment; wherein the collection environment is a target space environment in preset snowy weather; obtains the reference receiving power of the simulated radar in the simulated snowfall environment corresponding to the collection environment; wherein the simulated radar is a simulation model of the laser radar; and determines the target point cloud data obtained by the laser radar collecting point cloud data of the collection environment according to the environmental point cloud data and the reference receiving power. The present application enhances the environmental point cloud data by simulating the reference receiving power of the radar in the simulated snowfall environment corresponding to the collection environment, thereby improving the accuracy of the environmental point cloud data.

[0062] In one embodiment, snowfall weather is simulated by using a number of simulated snow particles in a simulated snowfall environment; accordingly, a reference receiving power of a simulated radar in the simulated snowfall environment corresponding to the acquisition environment is obtained, including: controlling the simulated radar to obtain the particle receiving power of each simulated snow particle in the simulated snowfall environment; determining the target receiving power of the corresponding simulated snow particles based on a preset initial receiving power and the particle receiving power of each simulated snow particle; and determining the reference receiving power of the simulated radar based on each target receiving power.

[0063] In one embodiment, the particle receiving power of each simulated snow particle in a simulated snowfall environment is obtained, including: for each simulated snow particle, according to the power impact data of the simulated snow particle, the particle receiving power of the snow particle is determined; wherein the power impact data includes reflectivity, reflection angle and detection distance; different simulated snow particles correspond to different detection distances.

[0064] In one embodiment, the particle receiving power of snow particles is determined based on the power impact data of simulated snow particles, including: determining the reflection response time of snow particles based on the reflectivity, reflection angle and detection distance of the simulated snow particles; determining the particle receiving power of snow particles based on the reflection response time of snow particles and the transmission power of simulated radar.

[0065] In one embodiment, the reflection response time of snow particles is determined based on the reflectivity, reflection angle and detection distance, including: determining the particle response time of snow particles based on the reflectivity, reflection angle and detection distance; and taking the product value between the particle response time and the preset laser response time as the reflection response time of the snow particles.

[0066] Specifically, the particle response time of snow particles can be determined according to the reflectivity, reflection angle and detection distance by the following formula (1-1). Figure 3 The top image shows snow particles interfering with a single lidar beam. The bottom image shows the corresponding received power echo. Note how the received powers of individual targets overlap with each other. H ≈3m, τ H = 10ns. We model the snow particle j as having a reflectivity ρ s A spherical object with a diameter D j Following the introduced snow particle distribution, the distance from the sensor , uniformly and randomly placed around the sensor without intersecting with any other particles. The number of snow particles is selected based on the snowfall rate, which is set between 0 and 2.5 mm / h. Particles can occlude each other and the specified target. Assume that the snow particles j < <cτ H :

[0067] (1-1)

[0068] Among them, H T (R) represents the particle response time; Θ represents the opening angle of the reflected light beam corresponding to particle j, where, ; ρ0 represents the reflectivity of the simulated radar; ρ s represents the reflectivity corresponding to the simulated snow particle j; θ0 represents the reflection angle of the simulated radar; θ j represents the reflection angle of the simulated snow particle j; R represents the detection distance of the simulated radar; R j represents the detection distance of the simulated snow particle j; δ() represents the Dirac function.

[0069] Specifically, the preset laser response time can be determined by the following formula (1-2):

[0070] (1-2)

[0071] Among them, H C (R) represents the laser response time; T(R) represents the transmittance of the medium, R represents the detection distance of the simulated radar, and ξ(R) represents the overlap rate.

[0072] Specifically, the product of the particle response time and the preset laser response time can be used as the reflection response time of the snow particles through the following formula (1-3):

[0073] (1-3)

[0074] Where H(R) represents the reflection response time of snow particles; H T (R) represents the particle response time; H C (R) Characterizes the laser response time.

[0075] Specifically, according to the preset initial received power and the particle received power of each simulated snow particle, the target received power of the corresponding simulated snow particle is determined by the following formula (1-4);

[0076] (1-4)

[0077] Among them, P R,snow (R) represents the target received power of simulated snow particles; Characterize the initial received power; Characterizes the particle received power of simulated snow particles.

[0078] Specifically, according to the received power of each target, the reference received power of the simulated radar is determined by the following formula (1-5).

[0079] (1-5)

[0080] in, represents the particle receiving power of the simulated snow particle; Θ represents the opening angle of the reflected beam corresponding to particle j; ρ0 represents the reflectivity of the simulated radar; ρ s represents the reflectivity corresponding to the simulated snow particle j; θ0 represents the reflection angle of the simulated radar; θ j represents the reflection angle of the simulated snow particle j; R represents the detection distance of the simulated radar; R j Characterizes the detection distance of the simulated snow particle j; δ() characterizes the Dirac function. System constant C A Not dependent on range or time, given by Given. R represents the aperture area of ​​the sensor optical receiver, and η represents the optical loss of the receiver. τ H Denotes the width of a half-power laser beam and is set to 10ns for the Velodyne HDL-S3D sensor.

[0081] It should be noted that the laser radar beam is relatively narrow, so the target is defined as a large target. From this, geometric optics can be used to model the received power to obtain the following formula (1-6):

[0082] (1-6)

[0083] Among them, P R (R) Characterization modeling received power; C A represents the system constant; P0 represents the laser pulse power; ρ0 represents the reflectivity of the simulated radar; α in Characterizes the angle of incidence.

[0084] The above method is applicable to targets whose diameter is larger than the beam diameter at distance R. In addition, this LiDAR received power formula also requires some additional information, including: the incident angle α of the laser in The system constant C is independent of distance and time A Due to the differences in optics and beam characteristics, the system constant C in each scan layer A Therefore, in order to make the laser power receiving value more accurate, a correction operation is usually required. The intensity calibration can be divided into four different levels. For the Velodyne HDL-S3D sensor used, when performing beam divergence correction, the definition needs to be corrected to the following formula (1-7):

[0085] (1-7)

[0086] Among them, R is the detection distance of the target, fs is the focal slope, f0 is the focal length, and R max According to the sensor model, it is 80m. The parameters of each laser are obtained from the factory side calibration. Before applying the proposed simulation method, we first retrieve the raw intensity by inverting this intensity calibration.

[0087] For LiDAR, the influence of atmospheric molecules on LiDAR can be basically ignored, but the influence of atmospheric aerosol on LiDAR needs to be considered. In snowfall, snow particles can be counted as atmospheric aerosols. Optical media contain tiny particles smaller than the diameter of the laser beam, which absorb and scatter the laser beam. Therefore, when considering the precise spatial distribution of particles, the scattering effect must also be considered. Scattering theory is a rigorous theory for the scattering effect of spherical particles on lasers. It is assumed that spherical particles are uniform and isotropic from an optical point of view. Under this condition, the theory of electromagnetics can be applied to solve the scattering effect of theoretical spherical particles on lasers: the results are derived using Maxwell's equations and boundary conditions. Theoretically, it is applicable to the scattering rules of any spherical particles on lasers.

[0088] At the same time, a linear model is used to describe the propagation process of the laser beam containing scattering particles. This model is applicable to the case of inelastic scattering characteristics. This model convolves the received power P that depends on the distance by convolving the time. R Expressed as the transmitted signal power P varying with time T The relationship between the laser beam response H of the optical system. This model can describe the attenuation characteristics of the optical signal over distance and the influence of the optical system. According to this model, the time convolution P R It can be written as shown in the following formula (1-8):

[0089] (1-8)

[0090] In addition, the time characteristic P of the transmitted laser beam T It can be written as shown in the following formula (1-9):

[0091] (1-9)

[0092] In this example, the simulated radar is controlled to obtain the particle receiving power of each simulated snow particle in the simulated snowfall environment; the target receiving power of the corresponding simulated snow particles is determined according to the preset initial receiving power and the particle receiving power of each simulated snow particle; according to each target receiving power, the reference receiving power of the simulated radar can be determined more accurately.

[0093] In one embodiment, target point cloud data obtained by laser radar through point cloud data collection of the collection environment is determined based on environmental point cloud data and reference receiving power, including: obtaining snow particle sampling data in the collection environment; determining snowfall point cloud data in the collection environment based on the snow particle sampling data and reference receiving power; and fusing the snowfall point cloud data with the environmental point cloud data to obtain target point cloud data obtained by laser radar through point cloud data collection of the collection environment.

[0094] For example, the snow particle sampling data in the collection environment is obtained; based on the snow particle sampling data (including the conversion between snowfall and rainfall), the snowflake particle size distribution when snowing is calculated (the input is the precipitation rate, in mm / h, and the output is 1 / cm); the input parameters simulate the particle sampling process, and output a particle sample array with a size of N rows and 3 columns; the empirical distribution between the trajectory of the sampling point and the intersection distance of a given single particle is calculated, and the splash of particles in the simulated precipitation process is simulated. According to the corresponding parameters of the Velodyne HDL-S3D sensor, the process of laser radar acquiring data is simulated in detail. This includes obtaining the calibration information of the sensor and the function of determining whether the point cloud object is within the camera's field of view; processing the received sensor data to eliminate the obscured part, increase the reflection intensity, reduce the error, etc.; calculating the particle cloud obstruction and using the sampling and calculated parameters to generate an enhanced point cloud. After reading the original data, the environmental point cloud data, the corresponding pixel coordinates of the point cloud, etc. are obtained and input. Then, according to the previously defined geometric relationship, snow particle information sampling and lidar simulation, we obtain the simulated information including the probability of snow hitting the ground, snowfall, etc., and store the information in the file. In addition, we randomly select a combination of rainfall rate and occupancy rate to generate a random selection list to carry out the simulation process, so that the original data can select parameters.

[0095] It should be noted that after completing the point cloud simulation modeling for snowfall weather, the simulation model can be visualized through Open3D, and a visualization graph of multi-frame point cloud simulation data sampled from [0, 0.5, ..., 2.5] mm / h under default rendering is obtained, as shown in the figure. Figure 4 A point cloud simulation visualization schematic diagram provided in this embodiment, Figure 4 (A) is the effect after rendering. Figure 4 (B) in the figure shows the unrendered effect.

[0096] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0097] Based on the same inventive concept, the embodiment of the present application also provides a radar simulation device for snowfall weather for implementing the radar simulation method for snowfall weather involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the radar simulation device for snowfall weather provided below can refer to the limitations of the radar simulation method for snowfall weather above, and will not be repeated here.

[0098] In an exemplary embodiment, Figure 5 As shown, a radar simulation device in snowy weather is provided, comprising: a data acquisition module 10, a power acquisition module 11 and a data determination module 12, wherein:

[0099] The data acquisition module 10 is used to acquire environmental point cloud data obtained by the laser radar performing point cloud data acquisition on the acquisition environment; wherein the acquisition environment is a target space environment in a preset snowy weather;

[0100] The power acquisition module 11 is used to simulate the reference received power of the radar in the simulated snowfall environment corresponding to the acquisition environment; wherein the simulated radar is a simulation model of the laser radar;

[0101] The data determination module 12 is used to determine the target point cloud data obtained by the laser radar performing point cloud data collection on the collection environment according to the environmental point cloud data and the reference receiving power.

[0102] In one embodiment, the power acquisition module 11 is also used to control the simulated radar to obtain the particle receiving power of each simulated snow particle in a simulated snowfall environment; determine the target receiving power of the corresponding simulated snow particles based on the preset initial receiving power and the particle receiving power of each simulated snow particle; and determine the reference receiving power of the simulated radar based on each target receiving power.

[0103] In one embodiment, the power acquisition module 11 is also used to determine the particle receiving power of each simulated snow particle according to the power impact data of the simulated snow particle; wherein the power impact data includes reflectivity, reflection angle and detection distance; different simulated snow particles have different corresponding detection distances.

[0104] In one embodiment, the power acquisition module 11 is also used to determine the reflection response time of the snow particles based on the reflectivity, reflection angle and detection distance of the simulated snow particles; and determine the particle receiving power of the snow particles based on the reflection response time of the snow particles and the transmission power of the simulated radar.

[0105] In one embodiment, the power acquisition module 11 is also used to determine the particle response time of the snow particles based on the reflectivity, reflection angle and detection distance; and the product value between the particle response time and the preset laser response time is used as the reflection response time of the snow particles.

[0106] In one embodiment, the data determination module 12 is also used to obtain snow particle sampling data in the collection environment; determine the snowfall point cloud data in the collection environment based on the snow particle sampling data and the reference received power; fuse the snowfall point cloud data and the environment point cloud data to obtain the target point cloud data obtained by the laser radar collecting point cloud data of the collection environment.

[0107] Each module in the above-mentioned radar simulation device under snowy weather can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0108] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 6As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a radar simulation method in snowy weather is implemented.

[0109] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0110] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0111] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0112] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0113] It should be noted that the data involved in this application (including but not limited to data used for analysis, stored data, displayed data, etc.) are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0114] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0115] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0116] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A radar simulation method in snowy weather, characterized in that: The method comprises: Acquire environmental point cloud data obtained by laser radar collecting point cloud data of a collection environment; wherein the collection environment is a target space environment in a preset snowy weather; Obtaining a reference received power of a simulated radar in a simulated snowfall environment corresponding to a collection environment; wherein the simulated radar is a simulation model of the laser radar; According to the environmental point cloud data and the reference received power, target point cloud data obtained by the laser radar through point cloud data collection on the collection environment is determined.

2. The method according to claim 1, characterized in that in, In the simulated snowfall environment, a plurality of simulated snow particles are used to simulate snowfall weather; accordingly, obtaining a reference received power of the simulated radar in the simulated snowfall environment corresponding to the acquisition environment includes: Controlling the simulated radar to obtain the particle receiving power of each simulated snow particle in the simulated snowfall environment; Determining the target received power of the corresponding simulated snow particles according to the preset initial received power and the particle received power of each simulated snow particle; According to each of the target received powers, a reference received power of the simulated radar is determined.

3. The method according to claim 2, characterized in that The step of obtaining the particle receiving power of each simulated snow particle in the simulated snowfall environment includes: For each simulated snow particle, determining a particle receiving power of the snow particle according to the power impact data of the simulated snow particle; The power impact data include reflectivity, reflection angle and detection distance; different simulated snow particles correspond to different detection distances.

4. The method according to claim 3, characterized in that The step of determining the particle receiving power of the snow particles according to the power impact data of the simulated snow particles comprises: Determining the reflection response time of the snow particles according to the reflectivity, reflection angle and detection distance of the simulated snow particles; The particle receiving power of the snow particles is determined according to the reflection response time of the snow particles and the transmission power of the simulated radar.

5. The method according to claim 4, characterized in that Determining the reflection response time of the snow particles according to the reflectivity, reflection angle and detection distance includes: determining a particle response time of the snow particles according to the reflectivity, reflection angle and detection distance; The product value between the particle response time and the preset laser response time is used as the reflection response time of the snow particle.

6. The method according to any one of claims 1 to 5, characterized in that: The step of determining target point cloud data obtained by collecting point cloud data of a collection environment by the laser radar according to the environment point cloud data and the reference received power comprises: Obtain snow particle sampling data in the collection environment; Determining snowfall point cloud data under a collection environment according to the snow particle sampling data and the reference received power; The snowfall point cloud data and the environment point cloud data are fused to obtain target point cloud data obtained by the laser radar collecting point cloud data of the collection environment.

7. A radar simulation device in snowy weather, characterized in that: The device comprises: A data acquisition module is used to acquire environmental point cloud data obtained by the laser radar for collecting point cloud data of a collection environment; wherein the collection environment is a target space environment in a preset snowy weather; A power acquisition module, used for simulating the reference received power of the radar in a simulated snowfall environment corresponding to the acquisition environment; wherein the simulated radar is a simulation model of the laser radar; The data determination module is used to determine the target point cloud data obtained by the laser radar collecting point cloud data on the collection environment according to the environmental point cloud data and the reference received power.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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