A millimeter wave radar simulation method and device for intelligent driving car simulation

Abstract

The embodiment of the application discloses a millimeter wave radar simulation method for intelligent driving car simulation, which comprises the following steps: acquiring environment data in a simulation scene; the environment data at least comprises material grid parameters of all objects in a millimeter wave radar sensing range; determining the emission intensity of the millimeter wave radar at the emission angle according to a radar directional diagram; converting the radar directional diagram into a gray scale diagram; emitting millimeter waves according to each pixel point in the gray scale diagram and the emission intensity of the millimeter wave radar; acquiring the structure body information of each hit point where the millimeter waves passing through the pixel points intersect with the objects in the simulation scene based on a ray tracing algorithm; acquiring the hit point information corresponding to each hit point according to the structure body information; obtaining the target information output by the simulated millimeter wave radar according to the hit point information; and the target information at least comprises target distance, target speed, target azimuth angle, target peak power, confidence and distance signal-to-noise ratio.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent driving car simulation, in particular to a millimeter wave radar simulation method and device for intelligent driving car simulation. BACKGROUND

[0002] In the advanced driver assistant system (ADAS) and intelligent driving system, the millimeter wave radar is an important environment perception sensor on the car. The millimeter wave radar can detect the relative distance, relative speed and azimuth angle of the road target to provide the road environment variables for the ADAS and intelligent driving system.

[0003] In the design and implementation process of the ADAS and intelligent driving system, the simulation scene software is usually used for testing, and the millimeter wave radar model can convert the scene information in the simulation software into sensor data close to the actual vehicle in real time. The intelligent driving algorithm receives the sensor data and outputs the car operation decision.

[0004] However, the above method has the following problems. Although the millimeter wave radar model can form a simulation result according to common vehicle, human and other target object information, it cannot form a simulation result according to the information of a new type of target object, resulting in low authenticity of the sensor data output by the millimeter wave radar model, and further affecting the accuracy of the ADAS and intelligent driving system testing. SUMMARY

[0005] The present application provides a millimeter wave radar simulation method and device for intelligent driving car simulation to improve the authenticity of the sensor data output by the millimeter wave radar model, and further improve the accuracy of the ADAS and intelligent driving system testing. The specific technical solutions are as follows.

[0006] In a first aspect, the present application provides a millimeter wave radar simulation method for intelligent driving car simulation, which comprises:

[0007] Obtaining environment data in a simulation scene; the environment data at least includes material grid parameters of all objects within the millimeter wave radar perception range;

[0008] According to the radar pattern, the transmission intensity of the millimeter wave radar at the transmission angle is determined;

[0009] Converting the radar pattern into a gray scale image; the gray scale image includes a plurality of pixel points;

[0010] According to each pixel point in the gray scale image and the transmission intensity of the millimeter wave radar, the millimeter wave is transmitted;

[0011] obtaining, based on a ray tracing algorithm, structure information of each hit point at which the millimeter wave passing through the pixel point intersects with an object in the simulation scene; the structure information at least includes millimeter wave intensity of the hit point, a millimeter wave transmission path, and a relative angle of the hit point;

[0012] obtaining, according to each structure information, hit point information corresponding to each hit point; the hit point information at least includes position information, speed information, angle information, and intensity information of the hit point;

[0013] obtaining, according to the hit point information, target information output by the simulated millimeter wave radar; the target information at least includes target distance, target speed, target azimuth, target peak power, confidence, and distance signal-to-noise ratio.

[0014] Optionally, the converting the radar pattern into a gray scale image comprises:

[0015] converting, according to a mapping relationship, a first horizontal angle range of a radar transmitting antenna in the radar pattern into a second horizontal angle range on an image plane, and converting a first vertical angle range of the radar transmitting antenna in the radar pattern into a second vertical angle range on the image plane;

[0016] performing normalization processing on the second horizontal angle range and the second vertical angle range to obtain the gray scale image.

[0017] Optionally, the obtaining, based on the ray tracing algorithm, the structure information of each hit point at which the millimeter wave passing through the pixel point intersects with the object in the simulation scene comprises:

[0018] generating, in the simulation scene, a plurality of hit points generated after multiple mirror reflections on the millimeter wave transmission path;

[0019] obtaining the relative angle of the millimeter wave at each hit point;

[0020] calculating, according to a mirror reflection millimeter wave intensity calculation formula, mirror reflection millimeter wave intensity generated by each hit point;

[0021] obtaining, according to the millimeter wave transmission path, the relative angle of the hit point, and the millimeter wave intensity, the structure information of the hit point.

[0022] Optionally, the obtaining, according to each structure information, the hit point information corresponding to each hit point comprises:

[0023] determining, according to the millimeter wave intensity in the structure information, millimeter wave return intensity returned from the corresponding hit point;

[0024] determine position information, speed information, angle information and intensity information of the corresponding hit point according to the millimeter wave return intensity;

[0025] determine the position information, speed information, angle information and intensity information of the hit point as the hit point information corresponding to the hit point.

[0026] Optionally, the target information simulated by the millimeter wave radar is obtained according to the hit point information, including:

[0027] generate a three-dimensional array with the data axes being relative distance, relative speed and azimuth sine according to the position information, speed information, angle information and intensity information of each hit point;

[0028] obtain a corresponding cell in the three-dimensional array to which the hit point belongs according to each hit point information;

[0029] perform millimeter wave intensity distribution for each cell in the three-dimensional array and a preset number of adjacent cells thereof;

[0030] calculate a weighted true value of the hit point in the corresponding cell by taking the millimeter wave intensity of the cell as a weight;

[0031] detect the three-dimensional matrix to obtain a cell with millimeter wave intensity greater than a preset threshold;

[0032] determine the hit point corresponding to the cell as a point target;

[0033] cluster the point target by using a clustering algorithm to obtain the target information.

[0034] Optionally, the transmission intensity of the millimeter wave radar at the transmission angle is determined according to the radar pattern, including:

[0035] find an antenna gain at the transmission angle according to the radar pattern;

[0036] determine the transmission intensity at the transmission angle according to the antenna gain.

[0037] Optionally, the millimeter wave intensity of the mirror reflection generated by each hit point is calculated according to a millimeter wave intensity of mirror reflection calculation formula, including:

[0038] the millimeter wave intensity of the mirror reflection generated by each hit point is calculated by the following millimeter wave intensity of mirror reflection calculation formula P reflection :

[0039] P reflection = P0×C reflection ×C material×C distance

[0040] Wherein, P0 is the energy incident to the current hit point from the last hit point or the emission end, C reflection is the proportion of the reflection intensity calculated by the Fresnel reflection formula in the total intensity, C material is the material reflectivity, C distance is the attenuation coefficient proportional to the square of the distance.

[0041] Optionally, the millimeter wave return intensity includes the millimeter wave intensity of specular reflection and the millimeter wave intensity of backscattering.

[0042] Optionally, the detecting the three-dimensional matrix to obtain a cell with millimeter wave intensity greater than a preset threshold value includes:

[0043] The three-dimensional matrix is detected by a constant false alarm rate detection algorithm to obtain a cell with millimeter wave intensity greater than a preset threshold value.

[0044] In a second aspect, an embodiment of the present application provides a millimeter wave radar simulation device for intelligent driving car simulation, the device comprising:

[0045] An acquisition module is configured to acquire environmental data in a simulation scene; the environmental data at least includes material grid parameters of all objects within a perception range of a millimeter wave radar;

[0046] A determination module is configured to determine a transmission intensity of the millimeter wave radar at a transmission angle according to the radar pattern;

[0047] A conversion module is configured to convert the radar pattern into a grayscale image; the grayscale image includes a plurality of pixel points;

[0048] A transmission module is configured to transmit millimeter waves according to each pixel point in the grayscale image and the transmission intensity of the millimeter wave radar;

[0049] The acquisition module is further configured to acquire, based on a ray tracing algorithm, structure information of each hit point where the millimeter waves pass through the pixel points and intersect with objects in the simulation scene; the structure information at least includes millimeter wave intensity of the hit point, a millimeter wave transmission path, and a relative angle of the hit point; according to each structure information, hit point information corresponding to each hit point is acquired; the hit point information at least includes position information, speed information, angle information, and intensity information of the hit point;

[0050] A processing module is configured to obtain target information output by a simulated millimeter wave radar according to the hit point information; the target information at least includes target distance, target speed, target azimuth, target peak power, confidence, and distance signal-to-noise ratio.

[0051] Optionally, the conversion module is specifically configured to:

[0052] convert, according to the mapping relationship, the first horizontal angle range of the radar transmitting antenna in the radar direction pattern into a second horizontal angle range on the image plane, and convert the first vertical angle range of the radar transmitting antenna in the radar direction pattern into a second vertical angle range on the image plane;

[0053] normalize the second horizontal angle range and the second vertical angle range to obtain the gray-scale image.

[0054] Optionally, the acquisition module is specifically configured to:

[0055] generate, in the simulation scene, a plurality of hit points generated after multiple mirror reflections on the millimeter wave transmission path;

[0056] acquire relative angles of the millimeter wave at each of the hit points;

[0057] calculate, according to a mirror reflection millimeter wave intensity calculation formula, mirror reflection millimeter wave intensities generated by each of the hit points;

[0058] obtain structure information of the hit points according to the millimeter wave transmission path, the relative angles of the hit points, and the millimeter wave intensities.

[0059] Optionally, the acquisition module is specifically configured to:

[0060] determine, according to the millimeter wave intensity in the structure information, a millimeter wave return intensity returned from a corresponding hit point;

[0061] determine, according to the millimeter wave return intensity, position information, velocity information, angle information, and intensity information of the corresponding hit point;

[0062] determine the position information, the velocity information, the angle information, and the intensity information of the hit point as hit point information corresponding to the hit point.

[0063] Optionally, the processing module is specifically configured to:

[0064] generate, according to the position information, the velocity information, the angle information, and the intensity information of each of the hit points, a three-dimensional array with a data axis of relative distance, relative velocity, and azimuth sine;

[0065] obtain, according to each of the hit point information, a cell in a three-dimensional array to which the corresponding hit point belongs;

[0066] performing millimeter wave intensity allocation for each cell in the three-dimensional array and a preset number of cells adjacent to each cell;

[0067] calculating a weighted true value of a hit point in the corresponding cell as a weight of millimeter wave intensity of the cell;

[0068] detecting the three-dimensional matrix to obtain a cell with millimeter wave intensity greater than a preset threshold;

[0069] determining the hit point corresponding to the cell as a point target;

[0070] performing clustering on the point target by using a clustering algorithm to obtain the target information.

[0071] Optionally, the determining module is specifically configured to:

[0072] finding an antenna gain at a transmission angle according to the radar direction pattern;

[0073] determining a transmission intensity at the transmission angle according to the antenna gain.

[0074] Optionally, the obtaining module is specifically configured to:

[0075] calculating a mirror surface reflected millimeter wave intensity P of each hit point by using the following mirror surface reflected millimeter wave intensity calculation formula reflection :

[0076] P reflection =P0×C reflection ×C material ×C distance

[0077] wherein P0 is energy incident to the hit point from a previous hit point or a transmission end, C reflection is a proportion of reflected intensity to total intensity calculated by using a Fresnel reflection formula, C material is a material reflectivity, and C distance is an attenuation coefficient proportional to square of distance.

[0078] Optionally, the millimeter wave return intensity includes mirror surface reflected millimeter wave intensity and backscattered millimeter wave intensity.

[0079] Optionally, the processing module is specifically configured to:

[0080] detecting the three-dimensional matrix by using a constant false alarm rate detection algorithm to obtain a cell with millimeter wave intensity greater than a preset threshold.

[0081] From the above, the millimeter wave radar simulation method and device for intelligent driving car simulation provided by the embodiment of the application can extract environment information from a simulation scene based on a millimeter wave radar model of simulation software, and convert the environment information into target information output close to real vehicle radar characteristics through processing of the environment information, and deliver the target information output to a perception layer and an intelligent driving decision layer to verify core functions of an intelligent driving system. The material information extracted by the millimeter wave radar model is not limited to common materials, but also includes material elements such as leather, glass and rubber, and is also reflected in signal strength, thereby improving the applicability of the millimeter wave radar model and the fidelity of output data.

[0082] The embodiment of the application calculates the transmission path of the millimeter wave by using the ray tracing algorithm, simulates the multiple reflection and backscattering characteristics of the millimeter wave. At the same time, the millimeter wave radar model can be configured as different radar models through parameter setting, and at the same time, multiple millimeter wave radars installed at different positions of the vehicle can be simulated to form relatively realistic data.

[0083] Of course, implementing any product or method of the application does not necessarily need to achieve all the advantages described above at the same time.

[0084] The innovation points of the embodiment of the application include:

[0085] 1. The millimeter wave transmission characteristics of the millimeter wave radar model close to the real vehicle are calculated by the millimeter wave tracking technology, the signal strength of the millimeter wave is generated according to different material grids, the application has the ability to calculate the echo strength of all grids within the sensor range, and the characteristics of reflection and backscattering are considered to form relatively realistic data.

[0086] 2. The material information extracted by the millimeter wave radar model is not limited to common materials, but also includes material elements such as leather, glass and rubber, and is also reflected in signal strength, thereby improving the applicability of the millimeter wave radar model and the fidelity of output data. BRIEF DESCRIPTION OF DRAWINGS

[0087] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the application. Those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0088] Figure 1 is a working flowchart of the intelligent driving system and the millimeter wave radar;

[0089] Figure 2 is an application flowchart of the millimeter wave radar model;

[0090] Figure 3 A flowchart of a millimeter wave radar simulation method for simulating a smart driving car is provided in an embodiment of the present application;

[0091] Figure 4 is a processing flowchart of a millimeter wave radar model;

[0092] Figure 5 is a schematic diagram of a gray scale image obtained by radar pattern conversion;

[0093] Figure 6 is a schematic diagram of millimeter wave emission using a ray tracing algorithm;

[0094] Figure 7 is a schematic diagram of millimeter wave reception using a ray tracing algorithm;

[0095] Figure 8 is a schematic diagram of the calculation of a weighted true value using intensity as a weight in the embodiment;

[0096] Figure 9 is a structural schematic diagram of a millimeter wave radar simulation device for simulating a smart driving car provided in an embodiment of the present application. DETAILED DESCRIPTION

[0097] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0098] It should be noted that the terms "include" and "have" and any variations thereof in the embodiments of the present application and the drawings are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but can optionally further include steps or units not listed, or can optionally further include other steps or units inherent to the process, method, product or device.

[0099] An embodiment of the present application discloses a millimeter wave radar simulation method and device for simulating a smart driving car, which can improve the authenticity of sensor data output by a millimeter wave radar model, and further improve the accuracy of ADAS and intelligent driving system testing. The embodiments of the present application will be described in detail below.

[0100] Figure 1 is a working flowchart of a smart driving system and a millimeter wave radar. As Figure 1As shown, the millimeter wave radar obtains the perception information of the surrounding environment through the processes of radar transceiving, raw data processing and target detection, and combines other intelligent driving sensor inputs into the perception layer for data fusion to obtain the perception information, the decision planning layer outputs the decision and planning path according to the perception information, and finally the control execution layer is responsible for the vehicle control of the vehicle in the current traffic scene. Therefore, the work of the intelligent driving system is a complex closed-loop working process. The millimeter wave radar is a necessary component of the intelligent driving system.

[0101] The key test items of the intelligent driving system include sensor fusion algorithms and decision planning algorithms. In the test process in the early development stage, a simulation environment is usually used to replace an actual vehicle scene. A millimeter wave radar model is used to replace the millimeter wave radar, so that the simulation technology is used to replace the actual road test. The simulation has the advantages of high data acquisition efficiency, high verification efficiency and high safety compared with the actual road test.

[0102] In the embodiment of the present application, as shown in Figure 2 The millimeter wave radar model can extract environment data from the simulation scene, calculate the transmission path of the millimeter wave through the millimeter wave tracking technology, simulate the characteristics of reflection and backscattering, and convert the results into a point target form close to the output of the real millimeter wave radar. As shown in Table 1, it is a parameterization list of the millimeter wave radar model:

[0103] Table 1

[0104]

[0105]

[0106] Figure 3 A flowchart of a millimeter wave radar simulation method for intelligent driving car simulation provided by the embodiment of the present application. The method specifically includes the following steps.

[0107] S110: Obtain environment data in the simulation scene; the environment data at least includes material mesh parameters of all objects in the perception range of the millimeter wave radar.

[0108] The environment data refers to the material mesh parameters of all objects appearing in the perception range of the millimeter wave radar in the simulation environment, such as the material of a person, the material of a vehicle, the material of a lane, etc., as shown in Table 2:

[0109] Table 2

[0110]

[0111]

[0112] As Figure 4The diagram shown illustrates the processing flow of a millimeter-wave radar model. This step involves acquiring environmental data from the simulation scenario, which can be obtained, for example, from the input module.

[0113] S120: Determine the transmission intensity of the millimeter-wave radar at the transmission angle based on the radar pattern.

[0114] This step can be, for example, by... Figure 4 The transmit antenna gain module performs this operation. After the input module receives environmental data, the transmit antenna gain module can adjust the signal based on the radar pattern. To find the antenna gain at the transmission angle, the radar pattern depicts the relationship between the electric field strength and the relative angle with respect to the direction of the transmitting antenna, where θ represents the relative horizontal angle. This indicates the relative vertical angle, which determines the emission intensity at a certain azimuth: Where P0 is the initial transmission strength of the radar, and P is the transmission strength multiplied by the antenna gain.

[0115] S130: Converts the radar pattern to a grayscale image; the grayscale image includes multiple pixels.

[0116] In this embodiment, to ensure compatibility with ray tracing algorithms, the colored radar pattern needs to be... The image is then converted to a grayscale representation. Specifically, based on the mapping relationship, the first horizontal angle range of the radar transmitting antenna in the radar pattern is converted to a second horizontal angle range under the image plane, and the first vertical angle range of the radar transmitting antenna in the radar pattern is converted to a second vertical angle range under the image plane; the second horizontal angle range and the second vertical angle range are then normalized to obtain a grayscale image.

[0117] like Figure 5 The diagram shown is a schematic of the grayscale image obtained from the radar pattern conversion. Taking W×H resolution as an example, it represents the first horizontal angle range of the radar transmitting antenna. Transformed to the second horizontal angle range [0, W] under the image plane, the first vertical angle range The second vertical angle range [0, H] is converted to the image plane, where W and H represent the resolution and can be set according to requirements. For example, if the resolution of a typical image is 800*600, then the horizontal angle range is [0, H]. Divided into 800 grids, vertical angle range It is divided into 600 squares.

[0118] After obtaining the second horizontal angle range and the second vertical angle range, normalization processing is performed to obtain the grayscale image G. transmit (w,h); where the mapping relationship can be expressed as:

[0119]

[0120]

[0121] wherein G max represents the maximum gain of the radar pattern, G min represents the minimum gain of the radar pattern, θ w represents the wth scale of the horizontal azimuth angle, θ w+1 represents the w+1th scale of the horizontal azimuth angle, represents the hth scale of the vertical azimuth angle, represents the h+1th scale of the vertical azimuth angle.

[0122] The above formula for determining the emission intensity can be approximated by a commonly used radar horizontal pattern, G horizontal (θ), and a radar vertical pattern G vertical (θ). The radar horizontal pattern gain and the radar vertical pattern gain can be measured, and in the design of the radar, the following considerations are taken into account:

[0123]

[0124]

[0125] wherein p is a normalization factor, is the horizontal angle corresponding to the wth column of the current pixel, is the vertical angle corresponding to the hth row of the current pixel, is the average gain of the radar horizontal azimuth pattern, is the average gain of the vertical radar azimuth pattern.

[0126] After obtaining the gray-scale pattern G transmit (w, h), the millimeter wave tracking technology can be used to simulate the transmission and intensity of the wave, and the emission intensity P emitted from each pixel point (w, h) is P = P0x G transmit (w, h).

[0127] S140: Emitting millimeter waves according to each pixel point in the gray-scale pattern and the emission intensity of the millimeter wave radar.

[0128] In this embodiment, the gray-scale pattern is used instead of the radar pattern, and in the actual simulation process, the millimeter wave emitted according to the gray-scale pattern can be used to simulate the reflection process of the millimeter wave by using the ray tracing algorithm.

[0129] S150: Obtaining structure information of each hit point where the millimeter wave passing through the pixel point intersects with an object in the simulation scene based on the ray tracing algorithm; the structure information at least includes the millimeter wave intensity of the hit point, the millimeter wave transmission path, and the relative angle of the hit point.

[0130] In this step, multiple impact points can be generated in the simulation scenario after multiple specular reflections along the millimeter wave transmission path; the relative angle of the millimeter wave at each impact point can be obtained; the millimeter wave intensity generated by the specular reflection at each impact point can be calculated according to the millimeter wave intensity calculation formula; and the structural information of the impact point can be obtained based on the millimeter wave transmission path, the relative angle of the impact point, and the millimeter wave intensity.

[0131] like Figure 6 The diagram shown illustrates the main process of millimeter-wave tracing, which can be derived from... Figure 4 The ray tracing module in the model executes the process. The ray tracing module can find the millimeter wave intensity based on the grayscale image above, and calculates the intersection point between the millimeter wave at each pixel and the object in the simulation scene. This intersection point is called the impact point. The model records the impact point structure information at each impact point, as shown in Table 3.

[0132] Table 3

[0133]

[0134] The intensity of millimeter waves reflected by the specular surface is:

[0135] P reflection =P0×C reflection ×C material ×C distance

[0136] Where P0 is the energy incident on this point of impact after passing through the previous point of impact or the transmitter, and the reflected energy P reflection Related to the following coefficient: C reflection C is the proportion of reflected energy to total energy calculated using Fresnel's reflection formula. material C represents the material's reflectivity. distance This is an attenuation coefficient proportional to the square of the distance, where the distance is from the previous impact point to the current impact point, simulating the attenuation of millimeter waves due to distance. The material reflection coefficient is defined as shown in Table 4. In this embodiment, to simulate the characteristics of electromagnetic waves, multiple impact points generated by multiple mirror reflections are produced. The calculation stops when the millimeter wave intensity decreases below the minimum intensity or the total path distance of the meter wave transmission path exceeds the maximum distance.

[0137] Table 4

[0138]

[0139] S160: Based on the information of each structure, obtain the impact point information corresponding to each impact point; the impact point information includes at least the position information, velocity information, angle information and intensity information of the impact point.

[0140] In this step, the millimeter wave return strength from the corresponding hit point can be determined according to the millimeter wave strength in the structure information; the position information, speed information, angle information and strength information of the corresponding hit point can be determined according to the millimeter wave return strength; and the position information, speed information, angle information and strength information of the hit point are determined as the hit point information corresponding to the hit point.

[0141] As shown in the millimeter wave receiving process diagram Figure 7 , the reception of millimeter waves is performed by the receiving antenna gain module as shown in Figure 4 . The receiving antenna gain module is responsible for calculating the millimeter wave strength returned from the hit point, which includes the mirror reflected millimeter wave strength and the backscattered millimeter wave strength. The return antenna gain is calculated using the formula of the above mapping relationship to obtain the received gray image G receiver (w, h). In this step, the incident angle attenuation coefficient C uBackWidth is calculated by Lambert formula, and the backscattered energy P backScatter is as follows:

[0142]

[0143] It can be understood that when the line between the hit point and the receiving antenna intersects with other objects, it means that the hit point to the receiving antenna is blocked, and its strength is 0.

[0144] Finally, the millimeter wave strength received by the receiving antenna depends on the way of returning to the receiving end:

[0145]

[0146] S170: obtaining target information simulated by millimeter wave radar output according to hit point information; the target information at least includes target distance, target speed, target azimuth, target peak power, confidence and distance signal-to-noise ratio.

[0147] In this step, the data encoding module as shown in Figure 4 can calculate the strength of each hit point and the position information, speed information and angle information of the hit point to generate a three-dimensional array with the data axes of relative distance, relative speed and azimuth sine; wherein the data axes are relative distance, relative speed, azimuth sine, and each grid contains strength, true value coordinates, true value relative horizontal angle and true value relative vertical angle. The specific calculation process is as follows:

[0148] The millimeter wave radar signal processing is generally sequentially Fourier transformed in the distance dimension, the speed dimension and the angle dimension. This step uses the millimeter wave tracking technology to generate the original data after the similar 3D Fourier transformation, and can obtain the corresponding cell in the three-dimensional array to which the hit point belongs according to the hit point information: that is, the distance-speed-azimuth angle sine cell to which the hit point belongs is calculated, wherein the distance-speed-azimuth angle analysis is a prior art of radar signal processing, and in this embodiment, the intensity addition is performed by collecting the backscattering intensities of different hit points, and the true value is recorded, so as to meet the algorithm requirement.

[0149] wherein the distance is the total distance in the millimeter wave propagation path, the speed is the projection sum of the speed of each hit point in the propagation path to the incident light path direction, the projection sum calculation method is that the current hit point has a speed v, the incident light path direction is the distance vector r from the last hit point to the current hit point, the projection is performed by using dot(v, r), and the azimuth sine is the sine of the relative angle of the last returned hit point.

[0150] Although the hit point is only one point, it belongs to a certain cell in the three-dimensional matrix, but the actual situation is that the adjacent cells should also have intensities, therefore, the millimeter wave intensity distribution needs to be performed for each cell and a preset number of adjacent cells in the three-dimensional array. For example, the intensity distribution is performed for the 2 3 cells containing the adjacent cells of the belonging cell, as shown in Figure 8 , the weights w r , w v , w a are calculated on the distance, speed and azimuth sine axes, in the three-dimensional grid, each hit point has 2 3 adjacent cells, and it is assumed that the r, v, a of a hit point are used to calculate the weight in each dimension. It is assumed that the current hit point has a distance x, if k is used as the interval to divide, x belongs to the interval A[A - , A + ], wherein It is compared whether the current x is close to the interval A - or A + , and the weight belonging to the A interval is obtained:

[0151]

[0152] wherein x-A - <A + -x represents that the point is in the left half of the A interval, and -A - >A + -x represents that the point is in the right half of the A interval.

[0153] It is compared whether the current x is close to the interval A - or A + , and the adjacent interval B is taken:

[0154]

[0155] The weights of those belonging to interval B are:

[0156]

[0157] Speed ​​weight w v Azimuth w θ The weights are calculated in the same way.

[0158] After calculating the weights of distance, velocity, and azimuth, they are combined into a total weight w, which is then used for intensity allocation:

[0159] w = w r ×w v ×w θ

[0160] 2 near the hit point 3 After calculating the weight w, the strength of the allocation is calculated using the following formula:

[0161] P i =P×w i i = {1, 2, ..., 8}

[0162] Where P is the millimeter wave intensity received at the point of impact and returning to the receiver, and i represents 2. 3 The i-th cell in the grid, P i For adjacent cells, calculate based on weight w i The intensity of the distribution.

[0163] After assigning intensity to cells, the weighted truth value of the hit point in the corresponding cell is calculated using the millimeter wave intensity of the cell as the weight. For example... Figure 8 As shown, when n hit points are assigned to the same cell, the formula for calculating the weighted truth value is:

[0164]

[0165] Among them, P i The intensity contributed to the i-th hit point, where the true value of x includes, but is not limited to, position, distance, velocity, horizontal angle, and vertical angle. i This represents the truth value of the i-th hit point.

[0166] The three-dimensional matrix generated through the above steps contains intensity information and true value information. However, in reality, in addition to the high-intensity signal returned by the target echo, there is also background noise caused by the external environment. In this embodiment, Gaussian white noise is introduced as background noise based on the actual situation, so that the generated data is suitable for the detection algorithm of millimeter-wave radar.

[0167] Specifically, by Figure 4 The detection module uses a constant false alarm rate (CFAR) detection algorithm to detect the three-dimensional matrix. Adjusting the number of detection units, protection units, and threshold factors can naturally generate false detections and missed detections, resulting in cells with millimeter wave intensity greater than a preset threshold. The hit point corresponding to the cell is then identified as a point target.

[0168] Figure 4 The target clustering module uses a clustering algorithm to cluster point targets to obtain target information. For example, the clustering condition can be: simultaneously satisfying Δr ≤ r res ,Δv≤v res ,Δθ≤θ res Δr is the distance difference between any two targets, Δv is the velocity difference between any two targets, Δθ is the azimuth difference between any two targets, and r res For distance resolution, v res For velocity resolution, θ res This refers to angular resolution.

[0169] Figure 4 The random disturbance module introduces noise into the true value of the hit point structure information storage. The magnitude of the introduced noise can be determined according to the sensor's ranging accuracy, velocity accuracy, and angle accuracy, and is not specifically limited here.

[0170] The final target information is provided by Figure 4 The millimeter-wave point cloud output module outputs the data. Specifically, this millimeter-wave point cloud output module uses the intensity of the point target as the peak power, sets a higher confidence level for targets with higher intensity, and calculates the range signal-to-noise ratio by dividing the point target intensity by the second-highest intensity within the nearest array grid, as shown in Table 5.

[0171] Table 5

[0172]

[0173]

[0174] As described above, this embodiment can extract environmental information from a simulated scenario based on a millimeter-wave radar model using simulation software. This environmental information is then processed and converted into target information output that closely resembles the characteristics of real vehicle radar, and transmitted to the perception layer and intelligent driving decision layer to verify the core functions of the intelligent driving system. Furthermore, by using ray tracing algorithms, the transmission path of millimeter waves is calculated, simulating the multiple reflections and backscattering characteristics of millimeter waves. Simultaneously, the millimeter-wave radar model can be configured with different radar models through parameter settings, and it can also simulate the installation of multiple millimeter-wave radars at different locations on the vehicle, generating relatively realistic data.

[0175] Figure 9A structural schematic diagram of a millimeter wave radar simulation device for intelligent driving car simulation is provided in an embodiment of the present application.

[0176] As shown in the figure, the millimeter wave radar simulation device for intelligent driving car simulation 900 in the embodiment can include an acquisition module 901, a determination module 902, a conversion module 903, a transmission module 904, and a processing module 905. Figure 9

[0177] The acquisition module 901 is configured to acquire environmental data in a simulation scene; the environmental data at least includes material mesh parameters of all objects within a perception range of a millimeter wave radar.

[0178] The determination module 902 is configured to determine a transmission intensity of the millimeter wave radar at a transmission angle according to a radar pattern.

[0179] The conversion module 903 is configured to convert the radar pattern into a grayscale image; the grayscale image includes a plurality of pixel points.

[0180] The transmission module 904 is configured to transmit millimeter waves according to each pixel point in the grayscale image and the transmission intensity of the millimeter wave radar.

[0181] The acquisition module 901 is further configured to acquire structure information of each hit point where the millimeter waves pass through the pixel points and intersect with objects in the simulation scene based on a ray tracing algorithm; the structure information at least includes millimeter wave intensity of the hit point, a millimeter wave transmission path, and a relative angle of the hit point; and to acquire hit point information corresponding to each hit point according to each structure information; the hit point information at least includes position information, speed information, angle information, and intensity information of the hit point.

[0182] The processing module 905 is configured to obtain target information output by the simulated millimeter wave radar according to the hit point information; the target information at least includes target distance, target speed, target azimuth, target peak power, confidence, and distance signal-to-noise ratio.

[0183] In one embodiment, the conversion module 903 is specifically configured to: convert a first horizontal angle range of a radar transmission antenna in the radar pattern into a second horizontal angle range under an image plane according to a mapping relationship, and convert a first vertical angle range of the radar transmission antenna in the radar pattern into a second vertical angle range under the image plane; and normalize the second horizontal angle range and the second vertical angle range to obtain the grayscale image.

[0184] ​In an embodiment, the obtaining module 901 is specifically configured to: in the simulation scene, generate a plurality of hit points generated after multiple specular reflections on the millimeter wave transmission path; obtain relative angles of the millimeter wave at each of the hit points; calculate millimeter wave intensity of specular reflection generated by each of the hit points according to a millimeter wave intensity calculation formula of specular reflection; and obtain structure information of the hit points according to the millimeter wave transmission path, the relative angles of the hit points and the millimeter wave intensity.

[0185] In an embodiment, the obtaining module 901 is specifically configured to: determine millimeter wave return intensity returned from a corresponding hit point according to millimeter wave intensity in the structure information; determine position information, velocity information, angle information and intensity information of the corresponding hit point according to the millimeter wave return intensity; and determine the position information, the velocity information, the angle information and the intensity information of the hit point as hit point information corresponding to the hit point.

[0186] In an embodiment, the processing module 905 is specifically configured to: generate a three-dimensional array with relative distance, relative velocity and azimuth sine as data axes according to the position information, the velocity information, the angle information and the intensity information of each of the hit points; obtain a cell in the three-dimensional array to which the corresponding hit point belongs according to each of the hit point information; perform millimeter wave intensity distribution for each cell in the three-dimensional array and a preset number of cells adjacent to the cell; calculate a weighted true value of a hit point in the corresponding cell by taking millimeter wave intensity of the cell as a weight; perform detection on the three-dimensional array by a constant false alarm rate detection algorithm to obtain a cell with millimeter wave intensity greater than a preset threshold; determine a hit point corresponding to the cell as a point target; and obtain the target information by clustering the point target by using a clustering algorithm.

[0187] In an embodiment, the determining module 902 is specifically configured to:

[0188] find an antenna gain at the transmission angle according to the radar pattern;

[0189] determine transmission intensity at the transmission angle according to the antenna gain.

[0190] In an embodiment, the obtaining module 901 is specifically configured to:

[0191] calculate millimeter wave intensity P of specular reflection generated by each of the hit points by the following millimeter wave intensity calculation formula of specular reflection reflection :

[0192] P reflection = P0×C reflection ×C material ×C distance

[0193] wherein P0 is the energy incident to the current hit point from the previous hit point or launch end, C reflection is the proportion of the reflection intensity calculated by the Fresnel reflection formula to the total intensity, C material is the material reflectivity, C distance is the attenuation coefficient which is proportional to the square of the distance.

[0194] In one embodiment, the millimeter wave return intensity includes a specularly reflected millimeter wave intensity and a backscattered millimeter wave intensity.

[0195] In one embodiment, the processing module 905 is specifically configured to:

[0196] detect the three-dimensional matrix by a constant false alarm rate detection algorithm to obtain a cell whose millimeter wave intensity is greater than a preset threshold.

[0197] The device embodiments correspond to the method embodiments and have the same technical effects as the method embodiments. For specific descriptions, refer to the method embodiments. The device embodiments are based on the method embodiments, and specific descriptions can be found in the method embodiments, which will not be repeated here.

[0198] Those skilled in the art can understand that the drawings are only schematic diagrams of an embodiment, and the modules or flows in the drawings are not necessarily required to implement the present application.

[0199] Those skilled in the art can understand that the modules in the device in the embodiments can be distributed in the device in the embodiments as described in the embodiments, or can be changed and located in one or more devices different from the embodiments. The modules in the above embodiments can be combined into one module, or can be further split into multiple sub-modules.

[0200] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A millimeter wave radar simulation method for intelligent driving car simulation, characterized by, The method comprises: acquiring environment data in a simulation scene; the environment data at least includes material grid parameters of all objects within a millimeter wave radar perception range; determining the transmission intensity of the millimeter wave radar at a transmission angle according to a radar pattern; converting the radar pattern into a gray scale image; the gray scale image includes a plurality of pixel points; the conversion of the radar pattern into the gray scale image includes: according to a mapping relationship, converting a first horizontal angle range of a radar transmission antenna in the radar pattern into a second horizontal angle range on an image plane, and converting a first vertical angle range of the radar transmission antenna in the radar pattern into a second vertical angle range on the image plane; performing normalization processing on the second horizontal angle range and the second vertical angle range to obtain the gray scale image; transmitting millimeter waves according to each pixel point in the gray scale image and the transmission intensity of the millimeter wave radar; acquiring, based on a ray tracing algorithm, structure information of each hit point where the millimeter waves passing through the pixel points intersect with objects in the simulation scene; the structure information at least includes millimeter wave intensity of the hit point, a millimeter wave transmission path, and a relative angle of the hit point; acquiring hit point information corresponding to each hit point according to each structure information; the hit point information at least includes position information, speed information, angle information, and intensity information of the hit point; obtaining target information output by a simulated millimeter wave radar according to the hit point information; the target information at least includes target distance, target speed, target azimuth, target peak power, confidence, and distance signal-to-noise ratio.

2. The method of claim 1, wherein, The acquisition of the structure information of each hit point where the millimeter waves passing through the pixel points intersect with objects in the simulation scene based on the ray tracing algorithm comprises: generating a plurality of hit points generated after multiple mirror reflections on the millimeter wave transmission path in the simulation scene; acquiring the relative angle of the millimeter wave at each hit point; calculating the millimeter wave intensity of mirror reflection generated by each hit point according to a millimeter wave intensity calculation formula of mirror reflection; obtaining the structure information of the hit point according to the millimeter wave transmission path, the relative angle of the hit point, and the millimeter wave intensity.

3. The method of claim 1, wherein, The acquisition of the hit point information corresponding to each hit point according to each structure information comprises: determining the millimeter wave return intensity returned from the corresponding hit point according to the millimeter wave intensity in the structure information; determining the position information, speed information, angle information, and intensity information of the corresponding hit point according to the millimeter wave return intensity; determining the position information, speed information, angle information, and intensity information of the hit point as the hit point information corresponding to the hit point.

4. The method according to any one of claims 1 to 3, characterized in that, The obtaining of the target information output by the simulated millimeter wave radar according to the hit point information comprises: generating a three-dimensional array with relative distance, relative speed, and azimuth sine as data axes according to the position information, speed information, angle information, and intensity information of each hit point; According to each of the hit point information, a cell in a three-dimensional array to which the hit point belongs is obtained; A millimeter wave intensity distribution is performed on each cell in the three-dimensional array and a preset number of adjacent cells thereof; A weighted true value of the hit point in the corresponding cell is calculated by taking the millimeter wave intensity of the cell as a weight; The three-dimensional matrix is detected to obtain a cell with a millimeter wave intensity greater than a preset threshold; The hit point corresponding to the cell is determined as a point target; The point targets are clustered by using a clustering algorithm to obtain the target information.

5. The method of claim 1, wherein, The method further comprises: According to the radar pattern, an antenna gain at the transmission angle is found; According to the antenna gain, the transmission intensity at the transmission angle is determined.

6. The method of claim 2, wherein, The method further comprises: The millimeter wave intensity of the mirror reflection P generated by each of the hit points is calculated by the following mirror reflection millimeter wave intensity calculation formula reflection : P reflection = P0 x C reflection x C material x C distance Wherein, P0 is the energy incident to the current hit point from the last hit point or the launching end, C reflection is the proportion of the reflection intensity calculated by the Fresnel reflection formula to the total intensity, C material is the material reflectivity, C distance is the attenuation coefficient proportional to the square of the distance.

7. The method of claim 3, wherein, The millimeter wave return intensity includes the specular reflection millimeter wave intensity and the backscattering millimeter wave intensity.

8. The method of claim 4, wherein, The method further comprises: The three-dimensional matrix is detected by using a constant false alarm rate detection algorithm to obtain a cell with a millimeter wave intensity greater than a preset threshold.

9. A millimeter wave radar simulation device for intelligent driving car simulation, characterized by, The device comprises: An acquisition module is configured to acquire environmental data in a simulation scene; the environmental data at least includes material grid parameters of all objects within a millimeter wave radar sensing range; A determination module is configured to determine, according to a radar pattern, a transmission intensity of the millimeter wave radar at a transmission angle; A conversion module is configured to convert the radar pattern into a grayscale image; the grayscale image includes a plurality of pixel points; the conversion module is specifically configured to: according to a mapping relationship, convert a first horizontal angle range of a radar transmission antenna in the radar pattern into a second horizontal angle range on an image plane, and convert a first vertical angle range of the radar transmission antenna in the radar pattern into a second vertical angle range on the image plane; and normalize the second horizontal angle range and the second vertical angle range to obtain the grayscale image; A transmission module is configured to transmit millimeter waves according to each of the pixel points in the grayscale image and a transmission intensity of the millimeter wave radar; The acquisition module is further configured to acquire, based on a ray tracing algorithm, structure information of each hit point at which the millimeter waves transmitted through the pixel points intersect with objects in the simulation scene; the structure information at least includes millimeter wave intensity of the hit point, a millimeter wave transmission path, and a relative angle of the hit point; according to each of the structure information, hit point information corresponding to each of the hit points is acquired; the hit point information at least includes position information, speed information, angle information, and intensity information of the hit point; A processing module is configured to obtain target information output by a simulated millimeter wave radar according to the hit point information; the target information at least includes target distance, target speed, target azimuth, target peak power, confidence, and distance signal-to-noise ratio.

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