Method for determining a design of an ultra-wideband sensor for a vehicle, computer program, device and computer

Abstract

Exemplary embodiments of the present invention provide a method for determining the design of an ultra-wideband sensor for a vehicle. The method comprises obtaining information about the link budget for the ultra-wideband sensor and obtaining information about the path loss of a signal emitted by the ultra-wideband sensor. Furthermore, the method comprises obtaining information about the minimum link budget required to detect an object and determining whether the design of the ultra-wideband sensor is sufficient for detecting the object. The determination of whether the design is sufficient is performed based on the link budget, the path loss, and the required minimum link budget. If the design of the ultra-wideband sensor is insufficient, the method further comprises adjusting the design of the ultra-wideband sensor to detect the object.

Description

[0001] Exemplary embodiments of the present invention relate to a method for determining a design of an ultra-wideband sensor for a vehicle, a computer program, a device and a computer, in particular but not exclusively to a concept for adapting a design of an ultra-wideband sensor for determining an object in the interior of a vehicle.

[0002] Several aspects must be considered when designing an ultra-wideband sensor with radar and radio functionality. On the one hand, the ultra-wideband sensor must be capable of detecting an object, such as a living being, inside a vehicle using its radar functionality. On the other hand, the ultra-wideband sensor must be capable of communicating with the vehicle's digital key using its radio functionality. For cost reasons, both functionalities should ideally be integrated into a single ultra-wideband sensor.

[0003] There is therefore a need to provide a method for determining the design of an ultra-wideband sensor for a vehicle. The method, the device, the computer program, and the computer according to the independent claims address this need.

[0004] The exemplary implementations are based on the core idea that a method for determining the design of an ultra-wideband sensor for a vehicle can be established based on information about a required minimum link budget, the link budget of the ultra-wideband sensor itself, and path loss. The link budget and path loss of the ultra-wideband sensor can be determined using classical methods or algorithms. For example, the link budget and / or path loss can be determined through simulations. The minimum required link budget can be determined based on the output of a machine learning algorithm. In other words, the design process can establish a relationship between the output of a machine learning algorithm and a classical design of the ultra-wideband sensor.

[0005] Exemplary embodiments relate to a method for determining the design of an ultra-wideband sensor for a vehicle. The method includes obtaining information about the link budget for the ultra-wideband sensor and obtaining information about the path loss of a signal emitted by the ultra-wideband sensor. Furthermore, the method includes obtaining information about the minimum link budget required to detect an object and determining whether the design of the ultra-wideband sensor is sufficient for detecting the object. The determination of whether the design is sufficient is performed based on the link budget, the path loss, and the required minimum link budget. If the design of the ultra-wideband sensor is insufficient, the method further includes adjusting the design of the ultra-wideband sensor to detect the object.By using the link budget, path loss, and the required minimum link budget, the design of an ultra-wideband sensor can be carried out considering both a structural design and the output of a machine learning algorithm. In other words, the design of the ultra-wideband sensor can be performed in conjunction with the application of a machine learning algorithm.

[0006] In one embodiment, obtaining information about the required minimum link budget can involve comparing the standard deviation of an empty reference signal (indicative of a measurement without an object to be determined) with the standard deviation of an object reference signal (indicative of a measurement with an object to be determined). By comparing the standard deviations of known reference signals, a parameter for the required minimum link budget can be advantageously determined. For example, the required minimum link budget can correspond to a minimal difference between the standard deviation of the empty reference signal and the standard deviation of the object reference signal.

[0007] In one embodiment, obtaining information about the required minimum link budget can involve determining a peak-to-peak value between the empty reference signal and the object reference signal. Determining a peak-to-peak value can improve the accuracy of determining the required minimum link budget.

[0008] In one embodiment, the blank reference signal and the object reference signal can be measurement signals from the interior of a vehicle. The method can further include determining the required minimum link budget for a plurality of seats in the vehicle's interior and selecting the seat with the largest required minimum link budget to determine whether the ultra-wideband sensor design is sufficient for object detection. By selecting the seat with the largest required minimum link budget, it can be ensured that the required minimum link budget is achieved for every seat.

[0009] Accordingly, the ultra-wideband sensor can be designed in such a way that detection of an object can be guaranteed for every seat in the interior of the vehicle.

[0010] In one embodiment, the blank reference signal can comprise a plurality of blank reference signals for different object orientations, and the object reference signal can comprise a plurality of object reference signals for the different object orientations. The method can further include determining the required minimum link budget for a plurality of object orientations within the vehicle's interior and selecting the object orientation with the largest required minimum link budget to determine whether the ultra-wideband sensor design is sufficient for object detection. Selecting the object orientation with the largest required minimum link budget ensures that the required minimum link budget is achieved for each object orientation.Accordingly, the ultra-wideband sensor can be designed in such a way that detection of an object can be guaranteed for a majority, in particular every, object orientation in the interior of the vehicle.

[0011] In one embodiment, the object reference signal can be a measurement signal of an object that results in a minimum detectable amplitude in the object reference signal. That is, the object's measurement signal can have an amplitude just sufficient to enable object identification. For example, the object reference signal could be a measurement signal from another vehicle for which a machine learning algorithm was known to be able to identify the object without error.

[0012] In one embodiment, adapting the design of the ultra-wideband sensor to identify the object can include determining a parameter of the ultra-wideband sensor for coexistence operation as a radio sensor, and adapting the design based on this determined parameter. This allows the ultra-wideband sensor to be designed for vehicle use within the framework of the coexistence principle. For example, a digital gain can be set taking coexistence operation into account.

[0013] Exemplary embodiments also include a computer program for carrying out one of the methods described herein, if the computer program runs on a computer, a processor, or a programmable hardware component.

[0014] Another embodiment is a device for determining the design of an ultra-wideband sensor. The device comprises an interface for communication with other communication devices (e.g., for receiving information about the link budget) and a data processing circuit configured to perform at least one of the methods described herein. Further embodiments include a computer with a device as described herein.

[0015] Examples of implementation are explained in more detail below with reference to the accompanying figures. These show: Fig. Figure 1 shows a schematic representation of a method for determining a design of an ultra-wideband sensor for a vehicle; Fig. Figures 2a-2f show exemplary empty reference signals and object reference signals; Fig. Figure 3 shows an example of a method for determining the design of an ultra-wideband sensor; and Fig. Figure 4 shows a block diagram of an embodiment of a device for determining the design of an ultra-wideband sensor for a vehicle.

[0016] Several embodiments are now described in more detail with reference to the accompanying drawings, in which some of these embodiments are illustrated. For the sake of clarity, the thickness dimensions of lines, layers, and / or regions may be exaggerated in the figures.

[0017] Fig. Figure 1 shows a schematic representation of a method 100 for determining a design of an ultra-wideband sensor for a vehicle. The method 100 comprises obtaining information about a link budget for the ultra-wideband sensor. Obtaining the information about a link budget can include determining the information about a link budget. For example, the method 100 can be carried out by a device. The device can be configured to trigger a configuration of the ultra-wideband sensor from a memory. The configuration of the ultra-wideband sensor can, for example, be a structural arrangement of elements of the ultra-wideband sensor on a circuit board, specifying, for example, a ground or type of ultra-wideband sensor. For example, the ultra-wideband sensor can be a lollipop antenna or a patch antenna. That is to say,Information about a link budget can be determined, for example, based on the antenna type of the ultra-wideband sensor. The link budget can therefore be determined by the structural design of the ultra-wideband sensor. Optionally or alternatively, obtaining the information can include receiving the information. For example, the device can receive the link budget information from the ultra-wideband sensor.

[0018] Furthermore, the method comprises obtaining information about a path loss of a signal emitted by the ultra-wideband sensor. Obtaining the path loss information can include determining the path loss information. For example, the device can be configured to trigger a configuration of the vehicle's interior, such as a cover, of the ultra-wideband sensor from a memory. The interior configuration can influence the propagation of a measurement signal emitted by the ultra-wideband sensor. In particular, attenuation of the emitted measurement signal can occur. That is, the (available) link budget can be reduced by a path loss due to a structural design of the vehicle's interior. For example, a channel response for the ultra-wideband sensor can be degraded by the interior configuration.Obtaining information about path loss (120) can enable consideration of path loss for determining a design. Optionally or alternatively, obtaining the information can include receiving the information. For example, the device can receive the path loss information from a central control unit.

[0019] Furthermore, the procedure includes obtaining information about a required minimum link budget to identify an object, such as a sleeping baby. Obtaining the information about the required minimum link budget can involve determining it. For example, the device can receive information about the output of a machine learning algorithm and determine the information about the required minimum link budget based on the output. Optionally or alternatively, obtaining the information about the required minimum link budget can involve receiving it. For example, the information about the required minimum link budget can be received from another device trained to execute the machine learning algorithm.

[0020] The information about the required minimum link budget can be used as a metric that links the output of a machine learning algorithm to the structural parameters of the ultra-wideband sensor (i.e., the link budget and path loss). Specifically, the required minimum link budget can be determined based on raw data from an ultra-wideband sensor. This determination can be made using a reference vehicle. For example, the deviation of two measurements from the ultra-wideband sensor under different conditions can be compared to determine the required minimum link budget. In other words, the information about the required minimum link budget, or the metric, can be used to verify whether the link budget, minus the path loss, is sufficient to enable the identification of an object inside the vehicle.

[0021] Accordingly, the procedure includes determining whether the design of the ultra-wideband sensor is sufficient for object detection. This determination is based on the link budget, path loss, and the required minimum link budget. This allows for the advantageous determination of the suitability of an ultra-wideband sensor design.

[0022] The information about the required minimum link budget or metric can be understood as a lookup table. That is, the information about the required minimum link budget can relate an available link budget (the link budget minus path loss) to the output of a machine learning algorithm used to identify an object inside the vehicle. This allows the available link budget to determine whether it is possible to identify the object inside the vehicle using the machine learning algorithm based on the raw data from the ultra-wideband sensor. In particular, the information about the required minimum link budget or metric can be determined for a condition, such as a reference vehicle, and applied to multiple vehicles. That is, the information about the required minimum link budget or metric...The metric can be used to determine the design of the ultra-wideband sensor for a specific vehicle without having to perform measurements on that vehicle. This reduces the effort required to determine the design of the ultra-wideband sensor.

[0023] The information about the required minimum link budget or metric can be used to relate target values ​​of an antenna measurement, i.e. the required minimum link budget, and output values ​​of a simulation of the ultra-wideband sensor (for example, based on a CAD model).

[0024] If the design of the ultra-wideband sensor is insufficient, the procedure further includes adapting the design of the ultra-wideband sensor to determine the object. This adaptation may involve increasing the number of bits for the link budget. For example, the number of bits may be increased from 256 to 512. Due to the coexistence principle, the number of bits for the link budget cannot be increased arbitrarily. Accordingly, the adaptation may optionally or alternatively involve adapting the configuration of the vehicle's interior. Adapting the configuration of the vehicle's interior can reduce path loss and thus increase the available link budget.

[0025] Method 100 can be used to determine the design of an ultra-wideband sensor for object detection. When designing an ultra-wideband sensor for an ultra-wideband radar with radar functionality, the quality of the raw signals from the ultra-wideband radar (e.g., combined antenna gain) is crucial for correct evaluation by a machine learning algorithm. In particular, a scenario with a minimal detectable signal from an object, especially a living being (for example, a sleeping baby), may be of interest. For instance, the ability to detect the breathing of a sleeping baby might be required. Accordingly, the raw signals of the sleeping baby's breathing must be such that the baby's breathing pattern can be distinguished from the background noise. This may require a minimal link budget.Information about the required minimum link budget can therefore enable the identification of an object inside the vehicle with a minimal detectable signal. In other words, Method 100 can enable the design of the ultra-wideband sensor so that an object inside the vehicle with a minimal detectable signal can be identified using the ultra-wideband sensor. The design of the ultra-wideband sensor can be carried out, in particular, under the premise that a vehicle access function and a radar function on the ultra-wideband sensor must operate together. In other words, Method 100 can take into account restrictions due to a coexistence functionality in the choice of symbol count to increase the digital gain.

[0026] Method 100 enables the establishment of a relationship between the link budget of the ultra-wideband sensor (for example, encompassing a combined antenna gain and digital amplification, etc.), the path loss to be determined in the integration environment of the ultra-wideband sensor, i.e., the vehicle interior, and information about a required minimum link budget or metric. This allows for the appropriate design of the ultra-wideband sensor. For example, various reference signals and their standard deviations and / or peak-to-peak values ​​of the standard deviations can be determined for Method 100. Thus, Method 100 can be used in a development process to define or determine whether the signal quality or...The signal-to-noise ratio of a channel response of the ultra-wideband sensor is sufficient to detect an object, especially a living being, (just barely) in various positions and / or orientations inside the vehicle.

[0027] In one embodiment, obtaining information about the required minimum link budget can involve comparing the standard deviation of an empty reference signal (indicative of a measurement without a target object) with the standard deviation of an object reference signal (indicative of a measurement with a target object). The empty reference signal and / or the object reference signal can be measurement signals from an ultra-wideband sensor in a reference vehicle. That is, the empty reference signal and / or the object reference signal can have been acquired independently of any specific vehicle for which the implementation is intended. Accordingly, the empty reference signal and / or the object reference signal can have been measured for known values ​​of the link budget and path loss.Based on the standard deviation between the blank reference signal and the object reference signal, a statement can be made as to whether object detection was possible with the minimum detectable signal inside the reference vehicle. Accordingly, the standard deviation can serve as a measure of the output of the machine learning algorithm as a function of the raw signals from the ultra-wideband sensor.

[0028] For example, as in Fig. As shown in Figures 2a-2f, the standard deviation of a "vehicle empty measurement" (based on the empty reference signal) is compared to a "vehicle with occupants and smallest movement amplitude measurement" (based on the object reference signal) using a multiple range of measurements via a ranging round. The difference in standard deviations can indicate the possibility of identifying an object with a minimal detectable signal. This difference can be related to the trained machine learning algorithm (specifically, an output) to determine how the available link budget (i.e., the link budget minus path loss) needs to be adjusted by designing the ultra-wideband sensor to achieve a correct classification by the machine learning algorithm. The information about the required minimum link budget, or rather, theThe metric can therefore serve as an interface between the output of a machine learning algorithm and the actually recorded measurement signals and / or simulated signals of the ultra-wideband sensor.

[0029] Optionally or alternatively, obtaining information about the required minimum link budget can involve determining a peak-to-peak value between the blank reference signal and the object reference signal. Determining a peak-to-peak value can simplify the process of determining the required minimum link budget or improve upon combining it with the difference of standard deviations.

[0030] In one embodiment, the blank reference signal and the object reference signal can be measurement signals from the interior of a vehicle. Method 100 can further include determining the required minimum link budget for a plurality of seats in the vehicle's interior and selecting the seat with the largest required minimum link budget to determine whether the ultra-wideband sensor design is sufficient to detect the object. By selecting the seat with the largest required minimum link budget, the ultra-wideband sensor can be designed such that a sufficient link budget is available to detect an object at any seat in the vehicle. This ensures that the ultra-wideband sensor design can detect the object in the vehicle's interior.

[0031] In one embodiment, the blank reference signal can comprise a plurality of blank reference signals for different object orientations, and the object reference signal can comprise a plurality of object reference signals for the different object orientations. Method 100 can further comprise determining the required minimum link budget for a plurality of object orientations inside the vehicle and selecting the object orientation with the largest required minimum link budget to determine whether the ultra-wideband sensor design is sufficient to identify the object. That is, the information about the required minimum link budget can depend on the orientation of the object inside the vehicle. For example, a baby in a car seat can be secured facing forward or rearward in a vehicle seat.Depending on the orientation of the infant car seat, the required link budget can vary, as the seat can introduce additional attenuation into the channel response. Information about the required minimum link budget allows for the appropriate determination of the available link budget for the ultra-wideband sensor. This ensures object detection regardless of the object's orientation within the vehicle.

[0032] In one embodiment, the object reference signal can be a measurement signal of an object that results in a minimal detectable amplitude in the object reference signal. That is, the object's measurement signal can have an amplitude just sufficient to enable object identification. For example, the object reference signal can be a measurement signal from another vehicle for which a machine learning algorithm is known to have been able to identify the object without error. This means that with a lower amplitude of the measurement signal, object identification may have been inaccurate. The measurement signal could, for example, include the breathing of a sleeping baby. That is, a sleeping baby can be an object with a minimal detectable signal. Alternatively, other objects, such as a cat or a dog, can also be or generate a minimal detectable signal.

[0033] In one embodiment, adapting the design of the ultra-wideband sensor to identify the object can include determining a parameter of the ultra-wideband sensor for coexistence operation as a radio sensor, and adapting the design based on this determined parameter. This allows the ultra-wideband sensor to be designed for use within the vehicle under the coexistence principle. For example, a digital gain can be set so that the radio functionality of the ultra-wideband sensor is not impaired.

[0034] Fig. Figures 2a-2f show exemplary empty reference signals and object reference signals. The upper image shows the empty reference signal (dashed line) and the object reference signal (solid line). The lower image shows the standard deviations of the two signals. Based on the Fig. 2a-2f can provide information about a required minimum link budget or metric (as in relation to Fig. 1 described) can be determined.

[0035] In the Fig. 2a and Fig. 2b. No signal from an object is discernible in the object reference signal. Accordingly, no clear trend emerges for the standard deviations. In particular, a low peak-to-peak value is obtained (for Fig. 2b even a negative peak-to-peak value). In comparison, in the Fig. 2c-2f, a signal from the object is recognizable within the object reference signal. Accordingly, different values ​​result for the standard deviations. In particular, the peak-to-peak value is significantly larger. Based on the standard deviations, it is therefore possible to determine which pipe signal is still suitable for identifying an object based on the object reference signal. This information can, for example, be used in the form of a lookup table for the procedure to determine the design of the ultra-wideband sensor.

[0036] Fig. Figure 3 shows an example of a method for determining the design of an ultra-wideband sensor. Block 312 shows the output of the machine learning algorithm. The known output of the machine learning algorithm allows a correlation to be established, indicating which measurement signals (or raw signals) of the ultra-wideband sensor are evaluated by which output of the machine learning algorithm, or conversely, which output the machine learning algorithm provides for which measurement signals. For example, it can be determined how the machine learning algorithm classifies a difference in the standard deviations of 0.1 between the blank reference signal and the object reference signal.

[0037] Block 322 allows for the establishment of a relationship between the link budget and the output of the machine learning algorithm. For example, it can be determined how much distance to the link budget exists for a difference of 0.1 in the standard deviations (represented by the dashed block 310). In particular, a worst-case scenario can be considered. That is, as described above, a seating position and / or object orientation can be selected for which the largest minimum link budget is required. For example, for variant 1 (reference 352) of the ultra-wideband sensor, a higher link budget may be required for the worst-case scenario than for variant 2 (reference 354) of the ultra-wideband sensor. For variant 3 (reference 356) of the ultra-wideband sensor, an even higher link budget may be required than for variant 1.Theoretically, the link budget could also be sufficient for variant 3, provided no path losses occur.

[0038] Block 322 accounts for path losses. Compared to block 332, which represents the theoretical link budget of the ultra-wideband sensor (for example, 256 bits), the available link budget in block 322 is reduced by a safety margin of 320. This safety margin can, in particular, specify a necessary margin for the machine learning algorithm. Optionally or alternatively, the safety margin 320 can specify the maximum permissible standard deviation for a given path loss. For example, the safety margin 320 can specify the maximum permissible path loss for a highly damped vehicle interior for variant 1 of the ultra-wideband sensor.

[0039] Fig. Figure 4 shows a block diagram of an embodiment of a device 30 for determining the design of an ultra-wideband sensor for a vehicle. The device 30 includes an interface 32 for communication with other communication devices (e.g., for receiving information about the link budget). The device 30 further includes a data processing circuit 34 configured to carry out at least one of the methods described herein, for example, the method which relates to at least one of the Fig. 1 and Fig. 3 is described for a device. Further embodiments include a computer 40 with a device 30.

[0040] The in Fig. The interface 32 shown in Figure 4 can, for example, correspond to one or more inputs and / or one or more outputs for receiving and / or transmitting information, such as digital bit values ​​based on a code, within a module, between modules, or between modules of different entities. The interface 32 can, for example, be configured to communicate with other network components via a (radio) network or a local area network.

[0041] In exemplary embodiments, the data processing circuit 34 can correspond to any controller or processor, or to a programmable hardware component. For example, the data processing circuit 34 can also be implemented as software programmed for a corresponding hardware component. In this respect, the data processing circuit 34 can be implemented as programmable hardware with appropriately adapted software. Any processor, such as digital signal processors (DSPs), can be used. These exemplary embodiments are not limited to a specific type of processor. Any processor, or even multiple processors, are conceivable for implementing the data processing circuit 34.

[0042] As in Fig.As shown in Figure 4, the interface 32 can be coupled to the respective data processing circuit 34 of the device 30. In examples, the device 30 can be implemented by one or more processing units, one or more processing devices, or any means of processing, such as a processor, a computer, or a programmable hardware component that can be operated with appropriately adapted software. Likewise, the described functions of the data processing circuit 34 can also be implemented in software, which is then executed on one or more programmable hardware components. Such hardware components can be a general-purpose processor, a digital signal processor (DSP), a microcontroller, etc.The data processing circuit 34 can be able to control the interface 32, so that any data transmission that takes place via the interface 32 and / or any interaction in which the interface 32 may be involved can be controlled by the data processing circuit 34.

[0043] In one embodiment, the device 30 may comprise a memory and at least one data processing circuit 34 which is functionally coupled to the memory and configured to perform one of the methods described above.

[0044] In examples, interface 32 can correspond to any means of receiving, receiving, transmitting, or providing analog or digital signals or information, such as any connector, contact, pin, register, input terminal, output terminal, conductor, track, etc., that enables the provision or receipt of a signal or information. Interface 32 can be wireless or wired and can be configured to communicate with other internal or external components, such as sending or receiving signals or information.

[0045] Further embodiments include computer programs for carrying out one of the methods described herein, where the computer program runs on a computer, a processor, or a programmable hardware component. Depending on specific implementation requirements, embodiments of the invention can be implemented in hardware or in software. The implementation can be carried out using a digital storage medium, for example, a floppy disk, a DVD, a Blu-ray disc, a CD, a ROM, a PROM, an EPROM, an EEPROM, a FLASH memory, a hard disk, or other magnetic or optical storage media on which electronically readable control signals are stored. These control signals can interact with, or interact with, a programmable hardware component in such a way that the respective method is carried out.

[0046] A programmable hardware component can be a processor, a computer processor (CPU = Central Processing Unit), a graphics processor (GPU = Graphics Processing Unit), a computer, a computer system, an application-specific integrated circuit (ASIC = Application-Specific Integrated Circuit), an integrated circuit (IC = Integrated Circuit), a system-on-a-chip (SOC = System on Chip), a programmable logic element, or a field-programmable gate array with a microprocessor (FPGA = Field Programmable Gate Array).

[0047] The digital storage medium can therefore be machine-readable or computer-readable. Some embodiments thus include a data carrier containing electronically readable control signals capable of interacting with a programmable computer system or a programmable hardware component to perform one of the methods described herein. An embodiment is therefore a data carrier (or a digital storage medium or a computer-readable medium) on which the program for performing one of the methods described herein is recorded.

[0048] In general, embodiments of the present invention can be implemented as a program, firmware, computer program, or computer program product with program code or as data, wherein the program code or data is / are effective in carrying out one of the methods when the program runs on a processor or a programmable hardware component. The program code or data can, for example, also be stored on a machine-readable medium or data carrier. The program code or data can be in the form of, among other things, source code, machine code, bytecode, or other intermediate code. Reference symbol list 30 Device 32 interface 34 Data processing circuit 40 computers 100 methods for determining an interpretation 110 Receiving information about a link budget 120 Receiving information about a path loss 130 Obtaining information about a required minimum link budget 140 Determine whether the interpretation is sufficient 150 Adapting the interpretation 312 Output machine learning algorithm 320 safety margin 322 Relationship between link budget and output of a machine learning algorithm 332 theoretical link budget 352, 354, 356 variants of the ultra-wideband sensor

Claims

[1] A method (100) for determining a design of an ultra-wideband sensor for a vehicle, comprising: Receive (110) information about a link budget for the ultra-wideband sensor; Receiving (120) information about a path loss of a signal emitted by the ultra-wideband sensor; Obtain (130) information about a required minimum link budget to determine an object; Determine (140), based on the link budget, path loss, and required minimum link budget, whether the design of the ultra-wideband sensor is sufficient to determine the object; and If the design of the ultra-wideband sensor is insufficient, adjust (150) the design of the ultra-wideband sensor to determine the object. [2] The method (100) according to claim 1, wherein obtaining the information about the required minimum link budget comprises comparing a standard deviation of an empty reference signal indicative of a measurement without an object to be determined and a standard deviation of an object reference signal indicative of a measurement with an object to be determined. [3] The method (100) according to claim 1 or 2, wherein obtaining the information about the required minimum link budget comprises determining a peak-to-peak value between the empty reference signal and the object reference signal. [4] The method (100) according to claim 2 or 3, wherein the blank reference signal and the object reference signal are measurement signals from an interior of a vehicle, and wherein the method (100) further comprises: Determining the required minimum link budget for multiple seats in the vehicle's interior; and Selecting the seat with the largest required minimum link budget to determine whether the ultra-wideband sensor design is sufficient to identify the object. [5] The method (100) according to any one of claims 2-4, wherein the blank reference signal comprises a plurality of blank reference signals for different object orientations and the object reference signal comprises a plurality of object reference signals for the different object orientations, and wherein the method (100) further comprises: Determining the required minimum link budget for multiple object orientations within the vehicle's interior; and Selecting the object orientation with the largest required minimum link budget to determine whether the ultra-wideband sensor design is sufficient to determine the object. [6] The method (100) according to any of the preceding claims, wherein the object reference signal is a measurement signal of an object which results in a minimum possible detectable amplitude in the object reference signal. [7] The method (100) according to any of the preceding claims, wherein adapting the design of the ultra-wideband sensor for determining the object comprises determining a parameter of the ultra-wideband sensor for coexistence operation of the ultra-wideband sensor as a radio sensor; and adapting the design comprises adapting based on the determined parameter. [8] A computer program for carrying out one of the methods (100) according to any of the preceding claims, wherein the computer program runs on a computer, a processor, or a programmable hardware component. [9] A device (30) for determining a design of an ultra-wideband sensor, comprising: an interface (32); and a data processing circuit (34) for carrying out at least one of the procedures (100) is designed according to one of claims 1-7. [10] A computer (40) comprising a device (30) according to claim 9.

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