LiDAR system for environmental sensing and method for operating a LiDAR system

Abstract

The application relates to a lidar system (20) for environmental sensing for a vehicle (30), wherein the lidar system (20) has an optical receiving sensor (14) with at least two pixels (Px), wherein the lidar system (20) is configured to perform a correction of optical crosstalk between the at least two pixels (Px) and to determine a residual error of the correction using a model of the residual error stored on a computing device (28) of the lidar system (20). The application further relates to a method for operating a lidar system (20) and a computer program product.

Description

Technical area

[0001] The application relates to a lidar system for environmental detection for a vehicle and a method for operating a lidar system. background

[0002] Modern vehicles (cars, vans, trucks, motorcycles, etc.) are equipped with a multitude of sensor systems whose data is used to inform the driver and / or provide data to driver assistance systems. These sensor systems record the vehicle's surroundings, including other road users. Based on the recorded data, a model of the vehicle's environment can be created, and changes in this environment can be responded to.

[0003] Sensor systems are constantly being developed for various functions, e.g., for environmental detection in the near and far range of vehicles, such as passenger cars or commercial vehicles. Sensor systems can also be used for driver assistance systems, especially assistance systems for autonomous or semi-autonomous vehicle control. They can be used, in particular, to detect obstacles and / or other road users in the front, rear, or blind spot area of ​​a vehicle. Sensor systems can be based on various sensor principles, such as radar, ultrasound, optics, etc.

[0004] An important optical sensor principle for environmental detection, e.g. of vehicles, is Lidar technology (Lidar, English: Light Detection and Ranging). A Lidar system has an optical transmitter and an optical receiver. The transmitter can emit an optical signal in the form of light, which can be continuous or pulsed. The optical transmission signal can also be modulated. In a Lidar system, light in the form of laser beams in the ultraviolet, visible, or infrared range can be used. The receiver can receive the light after it has been reflected from an object in the vicinity of the Lidar system. The received optical signal can be evaluated using the transmitted optical signal, e.g., using a time-of-flight method, and the spatial position and distance of the object from which the reflection occurred can be determined.In this context, reflection or reflected light is understood to mean any light that is thrown back and is intended to include, in particular, light that is thrown back by scattering or absorption-emission.

[0005] DE102021117361A1 describes a lidar system for environmental detection in a vehicle. The lidar system has an optical receiving sensor with a pixel matrix. Optical crosstalk correction between the pixels of the pixel matrix is ​​provided. Overview

[0006] A lidar system for environmental detection for a vehicle comprises an optical receiving sensor with at least two pixels. The lidar system is configured to correct optical crosstalk between the at least two pixels and to determine a residual error of the correction using a model of the residual error stored on a computing device of the lidar system.

[0007] A method for operating the lidar system comprises: • Correcting optical crosstalk between the at least two pixels and • Determining the residual error of the correction using the residual error model stored on the computing device of the lidar system.

[0008] To detect the environment, the lidar system has a transmitter that emits light. A receiver can receive the light reflected in the environment. By evaluating the transmitted and received light, e.g., in the computing device, an object in the environment can be detected and, for example, the distance to the object can be determined.

[0009] To receive the light, the receiving device has the receiving sensor, which has at least two pixels for receiving the light. The receiving sensor can also have more than two pixels, which can be arranged, for example, in a matrix. Using the pixels, the receiving sensor converts the received light into an electrical received signal. For this purpose, the respective pixel can, for example, have one or more photosensitive elements, e.g., photosensitive semiconductor elements such as photodiodes. A respective pixel can, for example, receive the light from a respective spatial direction and convert it into a respective electrical received signal. The pixel image data, from which image data of the surroundings can be determined, can then be determined from the received signals of the respective pixels.

[0010] The image data of the surroundings acquired by the lidar system is used for environmental detection by the lidar system. The image data can also include, for example, the intensities of the received light. Information can be obtained from the image data, such as the location of objects in the surrounding area, their distance, relative speeds, and other information.

[0011] Optical crosstalk, also called blooming, between the pixels of the receiving sensor is an undesirable effect that affects the quality of images or the accuracy of measurements. Optical crosstalk occurs, for example, when the receiving sensor is saturated by an intense light source, causing neighboring pixels to register higher values ​​than they should. This can lead to inaccurate measurements and lower data quality. Optical crosstalk can be triggered, for example, by sources in the environment that cause excessive reflections. In optical crosstalk, for example, excessive reflections can cause received light in the receiving sensor and thus in the image data to bleed into neighboring pixels. In scanning lidar systems, blooming can generate incorrect scan points.

[0012] Lidar systems operate with emitted light. This can lead to unwanted blooming effects, such as excessive reflections from highly reflective or retroreflective objects in the surrounding area and / or from objects that are very close to the detection system. Such highly reflective, retroreflective, or nearby objects can, due to the excessive reflections they cause, overshadow areas larger than themselves, resulting in a bright halo around such an object in the image data.

[0013] Optical crosstalk correction mitigates the effects of optical crosstalk in lidar systems. Various methods can be used to correct optical crosstalk. For example, affected regions can be identified and the associated image data can be corrected.

[0014] To determine the distance to objects in the surrounding area, a time-of-flight method, particularly an indirect time-of-flight method, can be used. In the indirect time-of-flight method, the light travel time is measured indirectly, e.g., by determining a phase shift between transmitted and received light. In the indirect time-of-flight method, the light transmission and reception can be pulsed.

[0015] To correct the optical crosstalk between at least two pixels, the light can be emitted with a shorter transmission duration, i.e., with a shorter exposure time, before and / or after the actual acquisition process in order to identify possible sources of optical crosstalk. The shorter exposure time can, for example, make it possible to identify the sources of blooming without the pixels reaching saturation. Using a correction value that depends on the identified possible sources, the optical crosstalk can then be corrected during the actual acquisition process.

[0016] To correct the optical crosstalk between the at least two pixels, the method described in DE102021117361A1 can be used, for example.

[0017] A residual error is determined for the correction of the optical crosstalk between at least two pixels of the receiving sensor. Even after the correction, there may still be errors in the image data that were not eliminated, for example, by under- or overcorrection. The residual error refers to the remaining error or inaccuracy in the correction of the optical crosstalk. The residual error depends, for example, on a difference between the image data after the correction and the expected image data without crosstalk, also called reference data. The residual error allows a quantification of the errors remaining in the image data after the correction.

[0018] The residual error can therefore be used to quantify the errors remaining in the image data after correction and thus to determine the quality of the image data after correction. To do this, it is possible, for example, to compare the residual error with the image data after correction. This comparison can, for example, include a comparison of the signal intensity of the image data with the residual error. In particular, the comparison can include the formation of a quotient, for example by dividing the signal intensity of the image data by the residual error. For example, if the signal in the image data after correction is strong and the residual error is small, it can be concluded that the acquired image data of the environment is reliable. For example, if the signal in the image data after correction is weak and the residual error is large, it can be concluded that the acquired image data of the environment is reliable. So, for example, ifIf the residual error is much smaller than the corrected image data, then the image data obtained after correction is reliable, and the environment detection is of good quality. If, for example, the residual error is of a similar magnitude to the image data after correction, then the image data obtained after correction is unreliable, and the environment detection is of poor quality. The comparison of the size of the residual error to the image data can be performed, for example, by division, i.e., by forming a quotient.

[0019] Determining the residual error is advantageous because it can be used to determine the quality of the image data of the environment captured by the lidar system. The quality can, for example, relate to the accuracy of a distance measurement and / or the accuracy of the spatial direction of a detected object in space and / or the accuracy of a determined intensity.

[0020] The residual error of the correction is determined using the residual error model stored on the computing device of the lidar system. The model stored on the computing device enables, for example, an estimation of the residual error. The model stored on the computing device can, in particular, include a mathematical model of the residual error.

[0021] In some embodiments, the residual error can be determined on a pixel-by-pixel basis. In such an embodiment, the model of the residual error refers to a respective pixel of the receiving sensor. It is possible for the model to be different for different pixels. If the model of the residual error is stored as a mathematical model, the residual error can be stored as a function f(i,j), where i, j indicate the position of the pixel in the pixel matrix.

[0022] In one embodiment, the residual error model may include a first component that depends on a global residual error behavior, where the global residual error behavior relates to the receiving sensor. For example, the function f may include a model for the shape of the global residual error. The shape of the global residual error behavior may be represented, for example, by the function f1(i,j,b,c) = ∑|b| ∗ g1(i,j,c), where g1 may represent the global shape of the global residual error.

[0023] In one embodiment of the lidar system, the residual error model has a second component that depends on a local residual error behavior, wherein the local residual error behavior relates to a respective pixel and / or its immediate surroundings. The local residual error behavior can, for example, comprise determining a convolution kernel for the respective pixel using its immediate surroundings.

[0024] The convolution kernel is a small matrix used for convolution operations on the pixel image data. The convolution kernel is applied to the image data by sliding it across the image pixel by pixel. At each position, the elements of the convolution kernel are multiplied by the corresponding pixels in the image area covered by the convolution kernel. The resulting values ​​are then summed to produce a single output value representing the local residual error at that pixel position. For example, the local residual error can be characterized using the convolution kernel: f2(i,j,b,c) = ∫b(x - i,y - j) ∗ g2(x,y,c) dxdy, where g2 can represent the convolution kernel for the local residual error.

[0025] In one embodiment, the lidar system is configured to acquire image data relating to at least one source in the environment for crosstalk, wherein the correction depends on the image data relating to the at least one source. The lidar system is further configured to determine the residual error using the image data relating to the at least one source.

[0026] In one embodiment, the method may comprise: • Acquiring image data to the at least one source for the crosstalk, wherein the correction depends on the image data to the at least one source and • Determining the residual error using the image data for the at least one source.

[0027] Blooming effects in lidar systems can occur, for example, on highly reflective, retroreflective, and / or nearby objects. Such causes of optical crosstalk are also referred to as blooming sources. If information about the sources of crosstalk is available, this information can be used to correct the crosstalk and / or to determine the residual error of the crosstalk correction. For example, the model can be stored as a mathematical model in which the residual error for pixel i, j depends on a blooming source. This has the advantage that the determination of the residual error can be more accurate.

[0028] In one embodiment of the lidar system, the determination of the residual error can depend on at least one parameter determined by calibrating the lidar system. This has the advantage that the determination of the residual error can be better tailored to the lidar system and / or the environment in which it is used.

[0029] For example, the model can be stored as a mathematical model with the function f(i, j, b, c). The residual error for pixel i, j depends on a blooming source b and other parameters c. The other parameters c can be calibration parameters, for example, which are defined during a calibration process for the lidar system.

[0030] The image data acquired for the at least one source can be filtered before use for correction and / or before use to determine the residual error. This can achieve better data quality. For example, noise filtering can be applied to the image data of the blooming sources before they are used to determine the residual error. In particular, noise filtering can be applied to the image data of the sources before they are used in the mathematical model f.

[0031] The residual error for a correction can be determined during operation of the lidar system. "During operation" can mean, for example, that the lidar system is in use in the vehicle and is capturing the surroundings while driving. Crosstalk correction can be performed during operation. The residual error can also be determined during operation, for example, while the vehicle is moving and / or during environmental detection. The residual error can then be used to determine the quality of the lidar system's environmental detection during operation.

[0032] The lidar system can have an output interface through which residual error information can be output, depending on the determined residual error. For example, the determined residual error can be output together with the image data.

[0033] In one embodiment, the lidar system is configured to use the determined residual error to determine the quality of the environment detection by the lidar system. In particular, the quality of the image data acquired by the lidar system can be determined.

[0034] The described lidar system can be used, for example, in a vehicle. The image data and / or residual error information output by the lidar system can then be further used by the vehicle's control units. In particular, the residual error and / or residual error information can be further used by the vehicle's control units to determine the quality of the image data output by the lidar system. The image data output by the lidar system relates to the environment detected by the lidar system. In particular, further processing and use in autonomous or semi-autonomous driving systems is also possible. In particular, output to an on-board computer is also possible, where information about the vehicle and its environment is centrally processed.

[0035] A vehicle may have a described lidar system and the vehicle computer. The vehicle computer is configured to receive the residual error information, whereby the execution of a driving function by the vehicle computer depends on the residual error information.

[0036] The method for operating the lidar system may further comprise determining the at least one further parameter in a parameter calibration process, wherein the residual error depends on the at least one further parameter.

[0037] The residual error model can be determined in a model calibration process. This model calibration process can be performed manually and / or automatically. Various model candidates can be tested on the lidar system through manual or automated application and comparison, and the most suitable model can be selected.

[0038] In particular, the model can be determined iteratively in the model calibration process. During this iterative process, the model can be gradually modified and improved.

[0039] In the model calibration process, the residual error model can be selected based on the following criteria, for example a) The residual error should be as small as possible to achieve the best performance. This means determining fewer residual errors that are incorrectly determined to be too large. b) The residual error should be greater than or equal to the actual residual error obtained by comparing the results after blooming correction with the reference data in order to reduce the number of erroneous residual errors that are too small.

[0040] A computer program product includes instructions that, when executed by the lidar system, cause the lidar system to perform the described method.

[0041] In autonomous driving applications, the method and / or the lidar system enable detection of whether the detection results of the lidar system can be trusted. If the residual error is too large, the system can react, e.g., by switching to other sensor systems or deactivating the autonomous driving function. Character list

[0042] In the following, embodiments of this application are further explained and described with reference to the figures. Fig. 1 schematically shows an embodiment of a receiving sensor, Fig. 2 schematically shows a vehicle with a lidar system, Fig. 3 a schematic illustration of image data with a convolution kernel, Fig. 4 a method for operating the lidar system.

[0043] The same reference numerals are used throughout the figures to refer to identical or similar elements. Representations in the figures may not be to scale. Character description

[0044] In Fig. Figure 1 schematically illustrates an embodiment of a receiving sensor 14 of a receiving device 24. The receiving sensor 14 has a field of pixels Px, also called a pixel array. In the example shown, the receiving sensor has four pixels Px arranged in a 2x2 matrix. The example shown is for illustrative purposes; in particular, the field of pixels Px can have significantly more than four pixels Px. To identify individual pixels Px of the pixel array, the rows of the pixel array can be indexed, for example, with i, and the columns of the pixel array can be indexed, for example, with j.

[0045] The receiving sensor 14 receives light L, which comprises light L reflected or backscattered by an environment 32. The received light L is converted into an electrical received signal by the receiving sensor 14. The respective pixels Px of the receiving sensor 14 can be designed such that they can receive light from a respective solid angle. The pixels can thus be assigned a respective region of the environment 32 from which they receive reflected or backscattered light L. To obtain the electrical received signal, the pixels Px can be evaluated individually and / or in groups. The pixels Px can also be assigned to respective spatial directions individually and / or in groups.

[0046] It is possible that - e.g. triggered by special objects O in the environment 32 - not only the pixel Px assigned to the direction from which the light L arrives is triggered, but also neighboring pixels Px are "hit". This is optical crosstalk and is also referred to as blooming. This is an undesirable optical artifact. Such special objects that trigger crosstalk, also called sources or blooming sources, can be, for example, highly reflective objects O such as road signs. The cause of the crosstalk can be that the affected pixels Px become saturated. For optical receive sensors, saturation means that the maximum intensity that the receive sensor can process is reached and exceeded. This leads to artifacts, e.g. blooming.

[0047] Fig. 2 schematically shows a vehicle 30, for example a passenger car, with a lidar system 20. The lidar system 20 is arranged in the front region of the vehicle 30. The surroundings 32 detected by the lidar system 20 are located in front of the vehicle 30 in the direction of travel. An object O is schematically shown in the surroundings 32. The lidar system 20 has a transmitting device 22 for emitting light L. The transmitting device 22 can in particular have a light source for emitting laser light. The lidar system 20 further has the receiving device 24 for receiving the reflected light L. The receiving device 24 has the receiving sensor 14 with pixels Px for receiving the light L, by means of which pixels Px can be used to convert light L into the electrical sensor signal. The transmitted and received light L can be evaluated in a computing device 28, e.g. B. to detect object O and / or determine the distance to object O.The computing device 28 can also monitor and control the transmission process in the transmission device 22 and the reception process in the reception device 24.

[0048] To determine the distance to object O in the environment 32, a time-of-flight method, in particular an indirect time-of-flight method, can be used. In the indirect time-of-flight method, the light travel time is measured indirectly, e.g., by determining a phase shift between transmitted and received light L.

[0049] In the example shown, the surroundings 32 in front of the vehicle 30 can be monitored in the direction of travel. It is also possible to arrange the lidar system 20 in other areas of the vehicle 30, for example, in the rear area and / or in the side areas. It is also possible to arrange multiple lidar systems 20 on the vehicle 30, in particular in corner areas of the vehicle 30.

[0050] With the lidar system 20, stationary or moving objects O, in particular vehicles, persons, animals, plants, obstacles, road surface irregularities, in particular potholes or stones, road markings, traffic signs, open spaces, in particular parking spaces, precipitation or the like, can be detected in the environment 32.

[0051] In Fig. 2 also shows a vehicle computer 34. The vehicle computer 34 is connected to the lidar system 20 via a data interface, via which output data from the lidar system 20 can be transmitted to the computing unit 34 of the vehicle 30.

[0052] The vehicle computer 34 can, for example, be configured as a central vehicle computer 34 of the vehicle 30, in which data from multiple sensor systems of the vehicle 30 can be received, evaluated, and / or further processed. The vehicle computer 34 can, for example, be used to implement autonomous or semi-autonomous driving functions.

[0053] In the lidar system 20, optical crosstalk between the pixels Px is also corrected. By correcting the optical crosstalk, the effects of the optical crosstalk in the lidar system 20 are mitigated. Various methods can be used to correct the optical crosstalk. For example, affected regions can be identified and the associated image data I.14 can be corrected.

[0054] When correcting crosstalk, the indirect time-of-flight method can particularly take advantage of the fact that the emission and reception of light can be pulsed. To correct optical crosstalk between the pixels Px, for example, the light L can be emitted before and / or after the actual acquisition process with a shorter emission duration, i.e. with a shorter exposure time, in order to determine the possible sources of the optical crosstalk. The shorter exposure time can, for example, make it possible to determine the sources of blooming without the pixels Px becoming saturated. The crosstalk can be corrected using a correction variable determined in conjunction with the shorter exposure time. For example, the correction variable can depend on the possible sources determined.During the actual acquisition process—with a longer exposure time—the optical crosstalk can then be corrected using the correction variable. To correct the optical crosstalk between the pixels Px, the method described in DE102021117361A1 can be used, for example.

[0055] To correct the optical crosstalk between the pixels Px of the receiving sensor 14, a residual error is determined. Even after the correction, there may still be errors in the image data I.14 that were not eliminated, for example, by under- or overcorrection. The residual error refers to the remaining error or the inaccuracy in the correction of the optical crosstalk. The residual error depends, for example, on a difference between the image data I.14 after the correction and the expected image data I.14 without crosstalk, also called reference data. The residual error allows a quantification of the errors remaining in the image data I.14 after the correction. For quantification, the residual error is related, for example, to the image data I.14 after the correction, e.g., compared. This comparison can, for example, involve forming a quotient in which, for example, the signal strength of the image data I.14 after the correction is divided by the residual error.The signal strength depends particularly on the intensity of the individual pixel image data I.Px. For example, if the residual error is much smaller than the corrected image data I.14, then the acquired image data I.14 after correction is reliable, and the environment detection is of good quality. If, for example, the residual error is of a similar magnitude to the image data I.14 after correction, then the acquired image data I.14 after correction is unreliable, and the environment detection is of poor quality. The comparison of the magnitude of the residual error to the image data can be performed, for example, by division, i.e., by forming a quotient.

[0056] The residual error of the correction is determined using a model of the residual error stored on the computing device 28 of the lidar system 20. The model stored on the computing device 28 can, for example, be a mathematical model f that depends on the pixel Px. The model can also be calibrated for the lidar system 20 and / or the vehicle 30. A calibrated model then depends, for example, on further parameters c. The model can also depend on the blooming source b and be stored as a mathematical model with the function f(i, j, b, c). The residual error for the pixel Px with the indices i, j depends on the blooming source b and the further parameters c.

[0057] Residual error information, which depends on the determined residual error, can be output via the output interface of the lidar system 20. For example, the determined residual error can be output together with the image data I.14. The image data I.14 and / or information on the residual error output by the lidar system 20 can then be further used by the vehicle computer 34 and / or by other control units of the vehicle 30. In particular, further processing and use in autonomous or semi-autonomous driving systems can take place.

[0058] The residual error information can be particularly useful for autonomous driving applications. For example, it can be used to determine whether the output data from the lidar system 20 can be trusted. If the residual error becomes too large, the system can switch to other sensor systems or, for example, deactivate the autonomous driving function.

[0059] During online processing, the sensor can use the mathematical model f to compare the strength of the electrical received signal for the respective pixel Px after blooming correction with the residual error in order to determine the quality of the respective pixel image data I.Px after blooming correction. From this, for example, the impact on the false alarm rate or the accuracy of the determined distance can be derived. The quality of the result after blooming correction can be determined during operation of the lidar system 20 in the vehicle 30.

[0060] The residual error model may include a global component related to the receiving sensor. For example, the function f may include a model for the shape of the global residual error—related to the entire receiving sensor or regions of the receiving sensor, the submatrices with pixels Px.

[0061] The residual error model may also have a local component. The local component refers to a particular pixel Px and / or its immediate surroundings. Fig. 3 shows an embodiment of a local component. Fig. The convolution kernel 16 shown in Figure 3 can be used as such a local component. The convolution kernel 16 is a small matrix used for convolution operations on the pixel image data I.Px. The convolution kernel is applied to the image data I.14 by sliding it over the image data I.14 pixel Px by pixel Px. At each position, the elements of the convolution kernel 16 are multiplied by the corresponding pixels Px of the image data I.14 covered by the convolution kernel 16. The resulting values ​​are then summed to produce a single output value representing the local component of the residual error at that particular pixel position.

[0062] In Fig. 4 shows a method for operating the lidar system 20.

[0063] In A, the detection of possible sources of optical crosstalk takes place. For this purpose, the environment 32 can be illuminated, for example, by emitted light L with a short exposure time. The short exposure time can be selected such that possible sources of crosstalk can be detected, but the crosstalk itself does not occur. For this purpose, the short exposure time is selected to be shorter than the exposure time used for environmental detection by the lidar system 20. In A, a correction value is determined which depends on the sources.

[0064] In B, the environment is detected by the lidar system 20. Light L is emitted by the transmitting device 22, reflected in the environment 32, e.g., at the object O, and received by the receiving device 24. To receive the light L, the receiving device 24 has the receiving sensor 14 with the pixels Px. Optical crosstalk can occur between the pixels Px.

[0065] The optical crosstalk is corrected in C. Various methods can be used to correct the optical crosstalk. For example, a correction value determined in A, which depends on the sources detected in A, can be used for the correction.

[0066] In D, the residual error of the correction from C is determined. To determine the residual error, the correction value determined in A can be used in addition to the corrected image data I.14 determined in C.

[0067] In E, the image data I.14 is output together with residual error information, which depends on the residual error determined in D.

[0068] A new acquisition process of the lidar system 20 is then started with a jump to A.

[0069] The image data acquired for the at least one source in A can be filtered before use for correction and / or before use to determine the residual error. This can achieve better data quality. For example, noise filtering can be applied to the image data of the blooming sources before they are used to determine the residual error in D.

[0070] The determination of the residual error in D for a correction made in C can be performed during operation of the lidar system 20. The correction of the crosstalk in C and the determination of the residual error in D can be performed while the vehicle is moving and / or during ongoing environmental detection by the lidar system 20.

[0071] The residual error can, for example, be compared with the corrected image data I.14 to determine the quality of the image data I.14. The comparison can, for example, involve the formation of a quotient. The quality of the image data I.14 can, for example, include the quality of the calculated distance and / or the quality of other properties, such as their intensity values. This allows the quality of the environmental detection by the lidar system 20 to be continuously determined. This quality can then be taken into account for further use by other vehicle systems, such as driver assistance systems or systems supporting autonomous or semi-autonomous driving. QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] DE 102021117361A1 [0005, 0016, 0054]

Claims

[1] Lidar system (20) for environmental detection for a vehicle (30), wherein the lidar system (20) has an optical receiving sensor (14) with at least two pixels (Px), wherein the lidar system (20) is configured to correct optical crosstalk between the at least two pixels (Px) and to determine a residual error of the correction using a model of the residual error stored on a computing device (28) of the lidar system (20). [2] Lidar system according to claim 1, wherein the lidar system (20) is further configured to determine the residual error on a pixel-by-pixel basis. [3] Lidar system according to claim 1 or 2, wherein the model of the residual error has a first component that depends on a global residual error behavior, the global residual error behavior relating to the receiving sensor (14). [4] Lidar system according to one of the preceding claims, wherein the model of the residual error has a second component which depends on a local residual error behavior, wherein the local residual error behavior relates to a respective pixel (Px) and / or its immediate surroundings. [5] Lidar system according to claim 4, wherein the local residual error behavior comprises determining a convolution kernel (16) for the respective pixel (Px) using its immediate surroundings. [6] Lidar system according to one of the preceding claims, wherein the lidar system is designed to acquire image data (I.14) relating to at least one source for the crosstalk in the environment, wherein the correction depends on the image data (I.14) relating to the at least one source, and wherein the lidar system (20) is further designed to carry out the determination of the residual error using the image data (I.14) relating to the at least one source. [7] Lidar system according to one of the preceding claims, wherein the determination of the residual error depends on at least one parameter which was determined by calibration of the lidar system (20). [8] Lidar system according to one of the preceding claims, wherein the lidar system (20) is designed to determine the residual error during operation for a correction made. [9] Lidar system according to one of the preceding claims, comprising an output interface via which residual error information can be output which depends on the determined residual error. [10] Lidar system according to one of the preceding claims, wherein the lidar system (20) is designed to use the determined residual error to determine the quality of the environmental detection by the lidar system (20). [11] Vehicle (30) with a lidar system (20) according to one of the preceding claims, further comprising a vehicle computer (34) which is arranged to receive the residual error information, wherein the execution of a driving function by the vehicle computer (34) depends on the residual error information. [12] Method for operating a lidar system (20), wherein the lidar system (20) has an optical receiving sensor (14) with at least two pixels (Px), the method comprising: Correcting optical crosstalk between the at least two pixels (Px) and Determining a residual error of the correction using a model of the residual error stored on a computing device (28) of the lidar system (20). [13] Method according to claim 12, wherein the residual error is determined pixel-related. [14] Method according to one of claims 12 or 13, further comprising: Acquiring image data (I.14) relating to at least one source for the crosstalk, wherein the correction depends on the image data (I.14) relating to the at least one source and Determining the residual error using the image data (1.14) for the at least one source. [15] Method according to one of claims 12 to 14, further comprising: Filtering the image data (I.14) acquired for the at least one source before use to determine the residual error. [16] Method according to one of claims 12 to 15, wherein the residual error is determined during operation for a correction made. [17] Method according to one of claims 12 to 16, further comprising: Determining at least one further parameter in a parameter calibration process, wherein the residual error depends on the at least one further parameter. [18] Method according to one of claims 12 to 17, further comprising: Determining the model in a model calibration process, which is carried out manually and / or automatically. [19] The method of claim 18, wherein the model is determined iteratively in the model calibration process. [20] Use of the residual error determined by the method according to one of claims 12 to 19 to determine the quality of an environmental detection. [21] A computer program product including instructions which, when executed by a lidar system (20), cause the lidar system (20) to perform a method according to any one of claims 12 to 19.

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