Real-time simulation of laser beam scanning of a composite of small objects

Abstract

To provide real-time simulation of laser beam scanning of a complex of small objects.SOLUTION: The device includes: a virtual environment including a monolithic 3D model of the complex of small objects; and a sensor simulation unit for simulating a sensor for measuring the distance by means of a laser beam. The sensor simulation unit includes a ray casting routine for simulating a laser beam, and a denoising routine. The denoising routine calculates an angle of incidence of the laser beam on a surface of the 3D model and selects an intensity distribution assigned to the calculated angle of incidence from a database including multiple intensity distributions. An intensity component of a reflection of the laser beam is read out of each of the intensity distributions as a function of a penetration depth of the laser beam into the complex of small objects. The denoising routine calculates a denoised distance measurement to simulate multiple reflections of the laser beam on multiple small objects considering the selected intensity distribution.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] Background Art A LIDAR sensor (LIDAR = Light Detection and Ranging) is a sensor that scans the environment using a light signal with a low wavelength in the near-infrared region. The LIDAR sensor can create a high-resolution three-dimensional image of its environment by detecting the reflection of the light signal and measuring its round-trip travel time. These characteristics make LIDAR interesting for use in highly automated vehicles that can move in unknown environments without human control and thus have to perceive their environment. Many LIDAR sensors use an oriented laser beam that is emitted in a spatial direction that changes at a high frequency so that a point cloud representing the environment based on reflections is calculated to scan the environment.

[0002] For several years, it has become common to test safety-critical electronic control systems in a virtual environment before mass production. Depending on the configuration of the object under test, this type of test method is known, for example, as Software in the Loop (SIL), Hardware in the Loop (HIL) or Vehicle in the Loop (VIL). The virtual environment is calculated in real time on a simulation computer and includes a sensor simulation unit that calculates sensor signals adapted to the virtual environment and supplies them to the object under test, i.e., the control system being tested, so that it can be examined whether the control system properly evaluates the sensor signals and responds appropriately to them.

[0003] For the testing of a LIDAR system, a corresponding sensor simulation device that mimics the functions of a LIDAR and can generate sensor signals of a given LIDAR sensor by synthesis can be commercially obtained. In particular, in the simulation of a LIDAR sensor that operates with an oriented laser beam, it is useful to utilize the ray casting method for such simulation. This is because the ray casting method so to speak corresponds to the natural operation mode of an actual sensor. In this case, the laser beam can be modeled by a single straight line within a virtual environment that emanates from a simulated sensor in order to calculate the incident point of the laser beam on the surface of a virtual object within the virtual environment. Here, the incident point is modeled as a simulated reflection source of the laser beam.

[0004] The method can provide satisfactory results as long as the laser beam can be approximated as an ideal geometric beam having no beam cross-sectional area. This is generally the case where the laser beam interacts with an object having dimensions that are at least one order of magnitude greater than the beam cross-sectional area in at least a first approximation. Examples of such objects are buildings, signs, vehicles, humans, and the ground. Problems arise with the method when the virtual environment includes a complex of small objects. By "complex of small objects" is meant a local accumulation of objects in a narrow range that are each on the order of or smaller than the beam diameter of the laser beam in at least one spatial direction. In particular, vegetation elements often form such complexes. That is, for example, a cereal field becomes a complex of ears, a meadow becomes a complex of grass (and possibly other plants), and a leafy plant, thicket, or coniferous forest becomes a complex of leaves. When the laser beam impinges on such small objects, the beam cross-sectional area becomes non-negligible. Generally, small objects reflect only a part of the beam intensity, and another part of the laser beam passes through the small object. Thus, a laser beam incident on a complex of small objects penetrates into the complex and loses intensity as the penetration depth increases due to multiple collisions with various small objects. In this case, the LIDAR sensor records a temporally distorted reflected signal composed of multiple reflections from various small objects having different round-trip times instead of a single well-defined reflection.

[0005] To physically simulate such a reflection process by classical ray casting or ray tracing in a physically valid form, a high-resolution 3D model that models individual small objects in detail is required, combined with a ray casting model that considers thousands of beams to adequately resolve the expanded laser beam. Such simulations cannot be performed at an acceptable cost quickly enough in hard real-time.

[0006] Regarding computer graphics, it is basically known to use probabilistic methods for reliable simulation of distorted light reflection executed in real time when the computational cost of physically accurate simulation based on ray casting or ray tracing is too high. As an example, the technical paper "Simulation of Realistic Water on 3D Game Scene" (Xiang Xu, Kun Zou, Procedia Engineering 29, 2012) describes a method for real-time simulation of reflection on a rippling water surface.

[0007] A further example from the field of sensor simulation is described in the technical paper "A 3-D Model for Millimeter-Wave Propagation Through Vegetation Media Using Ray-Tracing" (Nuno R. Leonor et al., IEEE Transactions on Antennas and Propagation 67(6), 2019). The paper describes problems in performing a reasonable simulation of radar echoes of vegetation elements in front of a background of fine structures formed by leaves. However, the approach of the proposed solution based on fixed-position point-like scattering centers is not applicable to the simulation of LIDAR operating with a laser beam that is oriented and strongly collimated.

[0008] A general introduction in the prior art of the simulation of vehicle imaging sensors for testing a control system by simulation is described in the technical paper "Development of Full Speed Range ACC with SiVIC, a virtual platform for ADAS Prototyping, Test and Evaluation" (Dominique Gruyer et al., IEEE Intelligent Vehicles Symposium, 2013).

Summary of the Invention

Problems to be Solved by the Invention

[0009] From these backgrounds, the problem of the present invention is to accelerate the computer simulation of laser beam scanning of a composite of small objects, and in particular to accelerate it sufficiently to enable real-time simulation at the operating speed of a sensor that measures distance using a laser beam.

Means for Solving the Problems

[0010] To solve the problem, an apparatus for performing real-time simulation of laser beam scanning of a composite of small objects is proposed. The apparatus includes a virtual environment and a monolithic 3D model of the composite of small objects as a part of the virtual environment.

[0011] The monolithic 3D model preferably does not have a structure on the order of small objects and is configured in particular not to include modeling of individual small objects. Particularly preferably, the 3D model of the composite models the composite only by the surface enclosing the composite. For example, a cereal field, i.e., a composite of ears in the physical world, can be modeled only by a rectangular parallelepiped bounding box enclosing the cereal field. Of course, the bounding box can be provided with a texture adapted to the cereal field for visualization, but does not include a three-dimensional structure simulating individual ears.

[0012] The device further includes a sensor simulation unit configured for the simulation of a sensor that performs distance measurement using a laser beam. The sensor simulation unit calculates the point of incidence of the laser beam emerging from the sensor on the surface within the virtual environment, calculates the Euclidean distance from the point of incidence to the sensor, and based on the Euclidean distance, simulates the distance measurement performed by the sensor, and in particular includes a ray casting routine configured to generate a synthetic sensor signal. The synthetic sensor signal can be supplied to a control system, such as a LIDAR system, that evaluates the sensor signal and is being tested in order to mimic the presence of the sensor by the test for the control system.

[0013] Furthermore, a part of the sensor simulation unit is a database in which a plurality of intensity distributions are stored. Each intensity distribution from the plurality of intensity distributions is associated with one angle of incidence of the laser beam. The intensity distribution is configured to be readable from each intensity distribution from the plurality of intensity distributions depending on the penetration depth of the laser beam into the complex of small objects for the intensity component of the reflection of the laser beam.

[0014] Furthermore, the sensor simulation unit includes a noise attenuation routine configured to calculate the angle of incidence of the laser beam on the surface of the 3D model and select the intensity distribution associated with the calculated angle of incidence from the plurality of intensity distributions. The noise attenuation routine calculates a noise-attenuated distance measurement taking into account the Euclidean distance and the selected intensity distribution. In other words, the noise attenuation routine accesses the data stored in the intensity distribution and based on this data, simulates the multiple reflections of the laser beam penetrating into the complex at multiple small objects of the complex with different round-trip travel times.

[0015] The sensor simulation unit is configured to record the collision of the simulated laser beam with the surface of the 3D model of the complex of small objects and to call the noise attenuation routine when the point of incidence of the laser beam is on the surface of the 3D model.

[0016] The number of possible incident angles of the laser beam is infinite. Therefore, of course, it is impossible to associate one intensity distribution with each possible incident angle. Therefore, the feature of the present invention, "selecting the intensity distribution associated with the calculated incident angle from a plurality of intensity distributions", means selecting one intensity distribution from the finite number of intensity distributions stored in the database, whose associated incident angle is sufficiently similar to the calculated incident angle, particularly one intensity distribution that is as similar as possible. In the development stage of the present invention, it is also possible to adapt the selected intensity distribution to the calculated incident angle by interpolating the selected intensity distribution to form another adjacent intensity distribution in the database.

[0017] The calculation of the noise attenuation distance measurement by the sensor simulation unit based on the intensity distribution can be configured in various ways. In a simple configuration of the present invention, the intensity components of the reflections at different penetration depths are easily read from the intensity distribution and directly used. That is, the response signal detected by the simulated sensor consists of a plurality of reflections, where the spatial distance of each individual reflection consists of the calculated Euclidean distance plus its penetration depth stored in the intensity distribution.

[0018] The drawback of this configuration is that it can lead to unrealistic sensor simulations. This is because the response signal is repeated when the incident angles match. Such drawbacks are particularly problematic in simulation scenarios where the incident angle of the laser beam is assumed to be constant. As an example, the simulation of a highly automated agricultural machine that can sweep the laser beam of a LIDAR system in a circular orbit across a cereal field without changing the elevation angle can be mentioned. If the 3D model of the cereal field is modeled as a bounding box, a constant incident angle will also occur in this case, so the simulated sensor should detect exactly the same response signal every time it scans.

[0019] Thus, in an advantageous configuration, the noise attenuation routine is configured to apply a random number generator when calculating the noise attenuation distance measurement to vary the noise attenuation distance measurements relative to each other. Particularly advantageously, the noise attenuation routine is configured to interpret the intensity distribution as a probability distribution from which the probability for different penetration depths into the complex for individual reflections of the laser beam can be read out, and based on this to calculate the noise attenuation distance measurement. As an example, the noise attenuation routine can be configured to simulate a fixed or variable number of reflections of the laser beam. In this case, the noise attenuation routine accesses the intensity distribution associated with the angle of incidence and configures the random number generator such that random numbers corresponding to the statistical distribution of the settings of the intensity distribution are generated. Subsequently, the noise attenuation routine uses the configured random number generator to associate one penetration depth into the complex with each reflection from the set number of reflections and thus simulates the noise attenuation distance measurement obtained from the reflections of the laser beam calculated in this way.

[0020] The creation of the intensity distribution may be based on measurements actually carried out in reality, but advantageously it is carried out based on a fine particle 3D model of the complex of small objects that decomposes the individual small objects, whereby the fine particle 3D model makes it possible to calculate the position of the entry point of the laser beam penetrating into the complex based on ray casting. In the fine particle 3D model, high-resolution ray casting of the laser beam incident into the complex at different angles of incidence is repeatedly carried out. The laser beam is modeled as a plurality of beams that simulate an expanded, i.e., non-zero beam diameter, fan-shaped laser beam as a whole.

[0021] For each angle of incidence to which an intensity distribution is to be associated, a corresponding ray casting is performed, and based on this ray casting, the incidence points of a plurality of beams on the surface of a small object within the fine particle 3D model are calculated. Next, by counting the incidence points depending on the penetration depth of the beam into the fine particle 3D model, an intensity distribution for each intensity distribution is created. In other words, the intensity distribution is configured such that the penetration depth interval is plotted on the horizontal axis, and on the vertical axis, a quantity characterizing the number of beams that have entered the surface of the small object at the penetration depth within each interval of each ray casting and caused reflection at this incidence point is plotted.

[0022] In the simplest case, when a uniform luminance is assumed for all reflections, the intensity of the reflection of the laser beam corresponding to the penetration depth is proportional to the number of each incidence point. However, at the development stage of the present invention, it is also possible to associate an individual luminance with each reflection, for example, considering material properties or the size or working area of the surface where the incidence point exists.

[0023] At the development stage of the present invention, each intensity distribution from a plurality of intensity distributions is associated with at least one other parameter in addition to the angle of incidence. Another parameter here may be another physical quantity that affects the reflection of the laser beam, for example, the type of vegetation, the divergence angle of the laser beam, the density of plants, the row spacing, the height of the vegetation, or the maturity. Here, the noise attenuation routine is configured to select an intensity distribution associated with the calculated angle of incidence and at least one other parameter from a plurality of intensity distributions.

[0024] The present invention will be described in detail below with reference to the drawings. The drawings are highly schematic. Geometric dimensions and the number of elements are sometimes shown in a state that does not conform to reality for better visualization.

Brief Description of the Drawings

[0025]

Figure 1

Figure 2

Embodiments for Carrying Out the Invention

[0026] The figure of FIG. 1 schematically shows the creation of the intensity distribution 2 associated with the incident angle θ. A virtual environment executed on a computer-based simulation device for testing a LIDAR system includes a simulated LIDAR sensor 4 and a fine particle 3D model 6 of a composite of small objects 8. The fine particle 3D model 6 decomposes the individual small objects 8, that is, includes a detailed 3D modeling of the individual small objects 8, and further includes a surface 10 that envelopes the composite and defines the outer boundary of the composite.

[0027] The sensor simulation unit that simulates the LIDAR sensor includes a ray casting routine. The ray casting routine models the laser beam with high resolution by a plurality of beams 12 that produce a simulation of a fan-shaped laser beam having an overall expanded beam diameter. Each beam 12 is a straight line guided through the three-dimensional space of the virtual environment. The beams 12 radiate fan-shaped from a common origin that is spatially identical to the coordinates of the simulated LIDAR sensor 4 within the virtual environment. The optical axis 14 of the laser beam is incident on the envelope surface 10 of the composite 6 at the incident angle θ, and the sensor simulation unit is configured to calculate this incident angle θ. For each beam 12, the ray casting routine checks for the presence of an incident point 16 on the surface of the virtual environment.

[0028] For each beam 12 where the incident point 16 is located on the surface of the small object 8, an intrusion depth D defined as the distance from the corresponding penetration point of each beam 12 on the envelope surface 10 to the respective incident point 16 is associated.

[0029] To create the intensity distribution 2, after all the incident points 16 have been calculated once, all the incident points 16 within the composite body, i.e., all the incident points 16 enclosed by the surface 10, are calculated, and the penetration depth D is calculated for each incident point 16 enclosed by the surface 10. The distribution of the penetration depth D is plotted as a histogram 18. The completed histogram 18 shows a plurality of penetration depth intervals D1, D2, D3, …, DN on the horizontal axis and the number of incident points 16 for which the penetration depth D is within each interval on the vertical axis. By interpolating the numbers plotted on the histogram 18, the histogram 18 is converted into the intensity distribution 2, and the intensity distribution 2 is stored in the database 20 so as to be uniquely associated with the incident angle θ within the database 20. This process is repeatedly performed multiple times at different incident angles θ in order to fill the database 20 with a plurality of intensity distributions 2 that rasterize the parameter space of the possible incident angles θ, which are associated with different incident angles θ respectively, with sufficient density. The parameter space rasterized by the intensity distribution 2 can include, in addition to the incident angle θ, another parameter that affects the reflection of the laser beam, and this other parameter is appropriately changed when creating the intensity distribution 2, and the intensity distribution 2 within the database 20 is associated therewith.

[0030] In a three-dimensional virtual environment, θ is the azimuth angle θ H and the elevation angle θ V and is a spatial angle consisting of them, and the intensity distribution 2 should be correspondingly associated within the database 20. In the creation of the intensity distribution 2 described above, for the sake of simplicity, each incident point 16 was made to achieve one set contribution, equal for all incident points 16, to the temporal dispersion intensity of the response signal measured by the simulated sensor 4. However, of course, it is also possible to associate individual intensities with each incident point 16. In the latter case, when creating the histogram 18, the individual incident points 16 are weighted differently according to the intensities associated with them.

[0031] The figure of FIG. 2 shows the operation mode of the sensor simulation during real-time simulation executed after the manufacture of the database 20. The ray casting routine of the sensor simulation part represents the laser beam of the LIDAR sensor emitted from the simulated sensor 4, but calculates only a single beam 12 without considering the beam diameter of the laser beam, instead of a high-resolution beam bundle. The fine particle 3D model 6 of the composite of the small object 8 is replaced by a simple monolithic 3D model 5 including only the envelope surface 10. Therefore, the composite of the small object 8 is modeled by a polyhedron, for example, by a bounding box, without decomposing the small object 8 during real-time simulation.

[0032] The sensor simulation part periodically calls the ray casting routine during the simulation in order to simulate the scanning of the environment by, for example, a circular laser beam, and simulates the operation mode of the LIDAR sensor by orienting the beam 12 in the changing spatial direction of the virtual environment. Every time the incident point of the beam 12 is on the envelope surface 10, the sensor simulation part calls the noise attenuation routine. The noise attenuation routine calculates the incident angle θ of the beam 12 on the envelope surface 10, and from the database 20, the matching intensity distribution 2, that is, its azimuth angle θ H and its elevation angle θ VCall the intensity distribution 2 that is most similar to the calculated angle of incidence θ with respect to (and another parameter associated with intensity distribution 2 in database 20). The noise attenuation routine corrects the called intensity distribution 2 based on interpolating the called intensity distribution 2 with at least one adjacent intensity distribution in the database in order to adapt the called intensity distribution 2 to the calculated angle of incidence θ. The noise attenuation routine interprets the intensity distribution 2 corrected in this way as the probability distribution of the penetration depth D of each given reflection of the laser beam incident into the complex of small objects 8 at the angle of incidence θ. The noise attenuation routine calls a random number generator for each reflection to be simulated, and the random number generator associates a penetration depth with each reflection one by one while applying the intensity distribution 2, so that one penetration depth D is associated with each of the set number of reflections of the laser beam to be simulated, whereby a statistical distribution of the penetration depth D corresponding to the intensity distribution 2 is obtained for a plurality of reflections.

[0033] The virtual environment in which the simulated sensor 4 operates includes two classes of 3D objects, and the sensor simulation unit is configured to distinguish between these two classes. The first class describes compact objects into which the laser beam cannot penetrate. Examples of such objects are buildings, vehicles, road signs, and humans. When the incident point of beam 12 is on an object of the first class, the sensor simulation unit does not call the noise attenuation routine and simulates the distance measurement based only on the Euclidean distance from the simulated sensor 4 to the incident point, and uses the Euclidean distance as the measured distance of the simulated sensor 4 (which may be slightly incorrect in some cases for simulating the measurement accuracy of sensor 4).

[0034] The second class describes a composite of small objects that can be penetrated by a laser beam. When the entry point 16 is on an object of the second class, the sensor simulation unit performs the calculation of the Euclidean distance from the sensor 4 to the entry point 16 in the same manner as described above, but does not use the Euclidean distance as the measured distance. Instead, the sensor simulation unit calls a noise attenuation routine to calculate a plurality of entry points each having a different penetration depth D, as described above. Based on the plurality of penetration depths, the noise attenuation routine calculates a noise-attenuated distance measurement consisting of a plurality of distance measurements corresponding to a plurality of reflections of the laser beam at different small objects 8. For each entry point 16 calculated based on the random number generator by the noise attenuation routine, a unique measured distance obtained from the sum of the Euclidean distance and the individual penetration depth D of each entry point 16 is calculated. From the totality of all the distance measurements thus calculated, the noise attenuation routine performs a noise-attenuated distance measurement. When calculating the noise-attenuated distance measurement, the noise attenuation function, particularly the different round-trip times resulting from the different penetration depths D, is also considered, and a response signal of a temporally distorted laser beam is simulated.

[0035] The noise attenuation routine outputs the noise-attenuated distance measurement to the sensor simulation unit. The sensor simulation unit calculates a synthetic sensor signal that simulates a real sensor signal output by a physical LIDAR sensor based on the corresponding noise-attenuated distance measurement, based on the noise-attenuated distance measurement, and outputs this synthetic sensor signal to the interface of the simulation device. The interface can be connected to a control system under test configured to process the sensor signal.

[0036] The present invention applies a simple ray casting method using only a single beam 12 and a simple 3D model 5 including only an envelope surface 10, enabling the simulation of multiple reflections of a laser beam in a composite of small objects in a realistic state. The simulation here can be executed at an acceptable cost and in hard real-time at the operating speed of a physical LIDAR sensor due to such simplification, and thus can be used for testing and development of a control system.

Claims

1. An apparatus for performing real-time simulation of laser beam scanning of a complex of small objects (8), the apparatus comprising: A virtual environment including a 3D model (5) that models the complex of small objects (8) monolithically without including modeling of individual small objects (8); A sensor simulation unit configured to simulate a sensor that performs distance measurement using a laser beam; The sensor simulation unit comprising: - A ray casting routine configured to calculate an incident point (16) of a laser beam from the sensor on the surface of the virtual environment and simulate the distance measurement performed by the sensor based on calculation of the Euclidean distance from the incident point to the sensor; - A database (20) including a plurality of intensity distributions (2), each intensity distribution (2) from the plurality of intensity distributions (2) being associated with one incident angle θ of the laser beam, and being able to read out an intensity component of reflection of the laser beam from each intensity distribution (2) from the plurality of intensity distributions (2) depending on the penetration depth D of the laser beam into the complex of small objects; - A noise attenuation routine configured to calculate the incident angle θ of the laser beam on the surface (10) of the 3D model, select the intensity distribution (2) associated with the calculated incident angle θ from the plurality of intensity distributions (2), and calculate a noise-attenuated distance measurement taking into account the Euclidean distance and the selected intensity distribution (2); The sensor simulation unit being configured to call the noise attenuation routine to simulate a plurality of reflections (16) of the laser beam at a plurality of small objects (8) when the incident point (16) of the laser beam is located on the surface of the 3D model (5). Apparatus.

2. The complex of small objects (8) is a vegetation element, in particular a complex of ears, i.e., a cereal field, or a complex of grass, i.e., a pasture, or a complex of leaves, i.e., a leafy plant or a thicket or a coniferous forest, The apparatus according to claim 1.

3. ​ The small object (8) is on the order of the beam diameter of the laser beam or smaller than the beam diameter of the laser beam, whereby the laser beam penetrates into the complex of the small objects (8), and as the penetration depth D increases, the intensity is lost due to reflection by the plurality of small objects (8). The apparatus according to claim 1.

4. The 3D model (5) of the complex does not include modeling of individual small objects (8). The apparatus according to claim 1.

5. The 3D model (5) is a surface (10) that envelopes the complex. The apparatus according to claim 4.

6. Each intensity distribution (2) associates one quantity characteristic of a plurality of reflections with a different penetration depth (D), respectively. Each of the plurality of reflections corresponds to a plurality of incident points (16) of a laser beam modeled and simulated with high resolution by a plurality of beams (12) in the fine particle 3D model (6) of the complex that decomposes individual small objects (8). The apparatus according to claim 1.

7. The sensor simulation unit is configured to calculate an intensity component in consideration of the number of the incident points (16). The apparatus according to claim 6.

8. Each intensity distribution (2) is associated with at least one other parameter in addition to the incident angle θ. The noise attenuation routine is configured to select an intensity distribution (2) associated with the calculated incident angle θ and one of the at least one other parameter, for example, the type of vegetation, the divergence angle of the laser beam, the density of plants, the row spacing, the height of the vegetation, the maturity, from the plurality of intensity distributions. The apparatus according to claim 2.

9. The sensor simulation unit is configured to generate a synthetic sensor signal of the sensor in order to mimic the presence of the sensor in a control system that evaluates a sensor signal, particularly a LIDAR system (Light Detection and Ranging), which is being tested. The apparatus according to claim 1.

10. A method for performing real-time simulation of laser beam scanning of a complex of small objects (8), the method comprising performing a sensor simulation of a sensor that performs distance measurements using a laser beam in a virtual environment including a 3D model (5) that monolithically models a complex of small objects (8) without modeling individual small objects (8), using a ray casting routine, the ray casting routine being configured to calculate an incident point (16) of a laser beam from the sensor (4) on a surface in the virtual environment and to simulate the distance measurements performed by the sensor (4) based on calculating the Euclidean distance from the incident point (16) to the sensor (4); Calculating the angle of incidence θ of the laser beam on the surface (10) of the 3D model (5); selecting an intensity distribution (2) associated with the angle of incidence θ from a database (20) containing a plurality of intensity distributions (2), wherein each intensity distribution (2) from the plurality of intensity distributions (2) is associated with one angle of incidence θ of the laser beam, and an intensity component of the reflection of the laser beam can be read from each intensity distribution (2) from the plurality of intensity distributions (2) depending on a penetration depth (D) of the laser beam into the complex of the small object (8); calculating a noise attenuated distance measure taking into account the Euclidean distance and the selected intensity distribution (2) to simulate multiple reflections (16) of a laser beam on multiple small objects (8); A method comprising:

11. The method comprises: calculating a composite sensor signal of said sensor (4) based on noise attenuated distance measurements; - feeding said composite sensor signal to a control system under test, in particular a LIDAR system (Light Detection and Ranging), which evaluates the sensor signal; Including, The method of claim 10.

12. The method comprises: providing a fine-grained 3D model (6) of a composite of small objects (8) in said virtual environment, resolving the individual small objects; Iteratively calculating, in the fine particle 3D model (6), points of incidence (16) of a plurality of beams (12) onto the surface of the small object (8), the plurality of beams (12) collectively simulating a fan-shaped laser beam with an expanded beam diameter for a plurality of angles of incidence θ; A step of creating an intensity distribution (2) by counting the incident points (16) depending on the penetration depth of the beam into the fine particle 3D model (6); comprising; The method according to claim 10.

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