Method for determining information of antenna array, method for operating antenna array, antenna array, sensor system and vehicle having sensor system

Abstract

The invention relates to a method for determining information of an antenna array (2) having a plurality of antenna elements (4), carrying out the following steps: receiving a received signal (8) corresponding to a transmitted signal (7) transmitted by the antenna array (2) into an environment (6); -sampling the received reception signal (8); transforming the sampled reception signal (8) into a signal curve (9) relating to a plurality of antenna elements (4) of the antenna array (2) by means of the evaluation unit (5); predicting an extended signal curve (10) by the evaluation unit (5) on the basis of a linear prediction of the signal curve (9); -reconstructing an actual signal curve (21) of the received signal (8) on the basis of the predicted extended signal curve (10); and determining antenna information of the antenna array (2) from the reconstructed actual signal curve (21) by means of the evaluation unit (5). The invention further relates to a method for operating an antenna array (2), to an antenna array (2), to a sensor system (3), and to a vehicle (1).

Description

[0001] The invention relates to a method for determining information of an antenna array having a plurality of antenna elements.

[0002] The invention further relates to a method for operating an antenna array having a plurality of antenna elements.

[0003] The invention further relates to an antenna array having an evaluation unit. The invention further relates to a sensor system having at least one antenna array and a vehicle having a sensor system.

[0004] For example, US 2021 / 0 382 132 A1 discloses a method and apparatus for determining the direction of a signal received from a radar system.

[0005] In addition, US 2021 / 0 080 542 A1 also discloses a method for determining the direction of a received radar signal. To this end, a matrix transformation can be performed to perform the determination.

[0006] It is an object of the present invention to increase, in particular to refine, the resolution of an antenna array of a sensor system.

[0007] This object is achieved by a method, an antenna array, a sensor system and a vehicle according to the independent patent claims. Reasonable further training follows from the dependent patent claims.

[0008] One aspect of the present invention relates to a method for determining information of an antenna array having a plurality of antenna elements, performing the following steps:

[0009] - in particular, receiving a receive signal corresponding to a transmit signal emitted by the antenna array into the environment;

[0010] - in particular, sampling the received receive signal;

[0011] - in particular, transforming the sampled received signal into a signal curve associated with a plurality of antenna elements of the antenna array by means of the evaluation unit;

[0012] In particular, the extended signal curve is predicted by the evaluation unit based on a linear prediction of the signal curve;

[0013] - in particular, reconstructing the actual signal curve of the received signal based on the predicted extended signal curve;

[0014] In particular, antenna information of the antenna array is determined by the evaluation unit based on the reconstructed actual signal curve.

[0015] The proposed method can be used to refine or increase the resolution of antenna arrays, and in particular, sensor systems equipped with such antenna arrays. This allows antenna arrays to be used more efficiently, particularly in the automotive sector. Furthermore, the proposed method can be used to improve or increase the accuracy of antenna arrays, particularly for environmental detection. The detection range can also be increased. Improving the resolution of antenna arrays, and in particular sensor systems, allows for more cost-effective production of antenna arrays, which also has a positive impact on the entire sensor system or overall system.

[0016] An antenna array, which can be designed as a group antenna or a phased array antenna, for example, can have multiple, in particular, a large number of antenna elements. The antenna elements can be individual antennas, i.e., single antennas. Using the antenna array, a transmit signal, in particular an electrical or electronic transmit signal, can be transmitted into the environment of the antenna array, i.e., into the surrounding area. This can be accomplished using the entire antenna array or at least one or more individual antennas of the antenna array. If the transmitted transmit signal is reflected by an object in the environment, the signal corresponding to the transmit signal and reflected by the object can be received as a receive signal by the antenna array, in particular, by one or more antennas of the antenna array. This received signal, in particular an electrical signal, can then be processed or evaluated for signal processing or environmental monitoring. For this purpose, the received receive signal can be sampled, for example, using an electronic evaluation unit, in particular a sensor system. Optionally, a predetermined sampling frequency or sampling rate can be used. The sampled receive signal can then be transformed or converted into a signal profile, in particular a local signal profile, associated with the multiple antenna elements of the antenna array. This can be accomplished using an evaluation unit.

[0017] The signal curve can also be a phase curve related to the arrangement or orientation of the antenna elements of the antenna array. Based on this transformed signal curve, an extended signal curve can be formed or predicted. For this purpose, linear prediction and / or linear error propagation can be used or applied. Thus, linear prediction is used to predict or estimate the extended signal curve relative to the antennas of the antenna array.

[0018] Based on the predicted or estimated extended signal curve, the actual signal curve of the received signal is reconstructed or formed. This reconstruction allows the actual signal curve to be reconstructed even if individual antennas in the antenna array or an antenna within the antenna array fails. This is particularly beneficial for improving the resolution, and particularly the accuracy, of the antenna array.

[0019] The evaluation unit can determine or obtain antenna information and / or multiple antenna information items of an antenna array based on the reconstructed actual signal curve. This antenna information can be used to determine whether individual antennas in the antenna array are faulty or defective. For example, the reconstructed actual signal curve can be used to compensate for faulty antennas in the antenna array, allowing for reliable and accurate signal evaluation of received signals, particularly for environmental monitoring. This can, for example, increase the system robustness of the antenna array, and in particular, a system incorporating the antenna array.

[0020] Therefore, the reconstructed actual signal curve can be used to generate antenna information. This antenna information can be used to perform diagnostics and provided, for example, to a processing unit and / or a computing unit of the sensor system or a unit coupled to the sensor system. Therefore, the antenna information can be used to improve the diagnostic capabilities and reliability of the antenna array, and in particular the sensor system. This is particularly advantageous in the event of a fault, as signal processing for environmental detection can be performed even in the event of a fault in the antenna array. This is particularly advantageous when the antenna array is used in automated vehicles, especially highly automated vehicles, where reliable environmental detection is crucial.

[0021] In particular, the proposed method may be a computer-implemented method.

[0022] In one exemplary embodiment, the sampled received signal is transformed into a, in particular, localized signal curve based on the azimuth and / or elevation angle of the antenna array. By taking into account the azimuth and / or elevation angle, i.e., the tilt angle of the antenna array, the sampled received signal can be transformed into a signal curve more precisely and therefore more accurately. By taking into account the angles, and in particular the alignment or orientation of the antenna array, the signal curve can be better formed, in particular as a localized signal curve. For this purpose, the temporally sampled received signal can be converted into a signal curve taking into account the orientation of the antenna array. This is particularly advantageous for detecting missing or faulty individual antennas in the antenna array and then compensating for them.

[0023] In another exemplary embodiment, the actual signal curve is reconstructed using an optimization method between a signal curve (i.e., the transformed signal curve) and an extended signal curve (i.e., the predicted or predicted signal curve). Thus, mathematical optimization methods, in particular, can be used to determine or reconstruct a target signal or target signal curve, i.e., the actual signal curve, based on an actual signal as the transformed signal and the predicted signal (i.e., the extended signal curve). For example, linear optimization methods can be used for this purpose. Other mathematical optimization methods are also conceivable. By determining the actual signal curve, the signal curve can be determined even in the event of a failure of individual antennas in the antenna array, and this can then be used for signal evaluation.

[0024] In one exemplary embodiment, an idealized signal model of an antenna array is generated based on an actual signal curve. Thus, a model representing the actual signal curve can be generated or produced and used, for example, for diagnostics, reliability testing, and / or error analysis of the antenna array. Specifically, the signal model or signal curve model can be used to determine antenna information or other antenna information about the antenna array.

[0025] In one exemplary embodiment, it is provided that the actual antenna position of at least one antenna element of the antenna array is determined based on an ideal signal model. Thus, the signal model, and in particular the reconstructed actual signal curve, can be used to determine at least one position or antenna position of an antenna element within the antenna array. Specifically, the signal model can be used to determine or determine each antenna position of the corresponding antenna element of the antenna array. This is also the actual or true antenna position of the corresponding antenna element. By determining the respective true antenna position of the antenna element, it is possible to determine whether the antenna array has faulty, malfunctioning, and / or even non-existent individual antenna elements. This can be prevented when performing or checking the antenna array in an erroneous manner, so that faulty or defective antenna elements can be suppressed, thereby increasing the robustness of the antenna array, in particular the robustness of the system containing the antenna array.

[0026] For example, the actual antenna position can be provided along with the antenna information. This is particularly advantageous for diagnostics and reliability testing of antenna arrays. Based on the determination of the actual antenna position, and in particular the faulty antenna element, the antenna array can be reconfigured, particularly after a failure of an individual antenna element. This offers advantages over replacing the antenna array, and in particular individual elements of the antenna array. This means that the antenna array can continue to operate, as reliable use of the antenna array can still be guaranteed.

[0027] Another aspect of the present invention relates to a method for operating an antenna array having a plurality of antenna elements, wherein the antenna characteristics of the antenna array are adjusted according to specific antenna information of the aforementioned aspect or an advantageous development thereof. Thus, the previously described method of the aforementioned aspect can be used to advantageously operate the antenna array.

[0028] For example, an antenna array can be referred to as an antenna arrangement or antenna group. Using antenna information, at least one antenna property can be adjusted or adapted. Antenna characteristics can be, for example, antenna features such as the resolution, accuracy, detection range, or reliability of the antenna array. For this purpose, for example, the antenna information can be used to provide a reconstructed actual signal curve and / or an ideal signal model, so that this information can be taken into account and / or antenna properties adjusted when operating the antenna array. This allows the antenna array to operate more efficiently and, in particular, be more fail-safe.

[0029] In one exemplary embodiment, in particular, another aspect provides for calibrating the antenna array based on antenna information. Using the antenna information and / or utilizing multiple antenna information, the antenna array can be calibrated in a manner that refines the resolution or resolution of the antenna array. Furthermore, calibration allows the antenna array to be adjusted based on the respective states of the individual antenna elements. Thus, the antenna array can be calibrated based on the reconstructed actual signal curve using the antenna information determined at the outset, most importantly compensating for defective and / or malfunctioning antenna elements and adjusting or adjusting the antenna array accordingly. This means that the antenna array can be continuously checked and calibrated as needed, allowing the antenna array to operate more efficiently and, in particular, increasing its robustness.

[0030] Optionally, using the antenna information and thus the reconstructed actual signal curve, a calibration method or calibration option for the antenna array can be provided in the simplest and most effective way.

[0031] Calibration of the antenna array is particularly advantageous when the antenna array has a sparse array configuration (ie a sparse array configuration).

[0032] In one exemplary embodiment, another aspect provides for generating at least one virtual antenna element for the antenna array based on the antenna information. The antenna array can, for example, provide or characterize position information for multiple antenna elements of the antenna array. For this purpose, actual signal curves and / or ideal signal models can also be used to generate or create additional virtual antenna elements. For example, the at least one virtual antenna element or multiple virtual antenna elements can be used to increase the resolution of the antenna array. Thus, the at least one virtually generated antenna element can be used to virtually or fictitiously extend the antenna array, allowing for consistent detection accuracy or probability of detection, for example, even in the event of a malfunction of a real antenna element.

[0033] In another exemplary embodiment, in particular, another aspect provides that the virtual antenna position of at least one virtual antenna element is determined in such a way that the at least one virtual antenna element can be arranged between two real antenna elements of the antenna array. This is particularly advantageous for thin antenna arrays in sparse array configurations. In an antenna array designed in this way, the individual antenna elements are relatively far apart from one another, allowing at least one virtual antenna to be precisely positioned, fictitiously or virtually, within these distances or gaps between two real antenna elements. Most importantly, the resolution of the antenna array can be increased because, while the number of real antenna elements used for signal processing or signal calculation is small, the number of antenna elements can be expanded by the additional virtual antenna elements. This also has the advantage that the antenna array does not need a large number of additional real antenna elements, thus reducing manufacturing costs and, therefore, maintenance costs. It is also advantageous for use in the automotive sector because the antenna array can be arranged on the vehicle or on the vehicle's profile and / or body in such a way that the real antennas can also be arranged at a certain distance from one another, and the at least one virtual antenna or multiple virtual antennas can be used accordingly during processing, signal processing, or environmental detection.

[0034] In another exemplary embodiment, in particular, another aspect provides for determining the virtual antenna position of at least one virtual antenna element in such a way that a missing or functionally impaired real antenna element from the plurality of antenna elements is replaced with the at least one virtual antenna element. This allows the antenna array to continue operating effectively despite a faulty or damaged real antenna element, as the virtual antenna element can be used to compensate for the defective real antenna element. For this purpose, antenna information can be used to provide, for example, which real antenna element is faulty and where it is located. Thus, particularly with the aid of an electronic evaluation unit, the virtual antenna element can be generated in such a way that its virtual position corresponds to the position of the defective real antenna element. This means that the antenna array can continue to operate, and in particular, function, despite faulty individual antenna elements. Furthermore, by using the generated virtual antenna element, the antenna array can operate longer, as defective real antenna elements do not need to be replaced or immediately repaired, as the software-based generation of the virtual antenna element provides a remedial measure.

[0035] By performing such an initial calibration, particularly after sampling the received receive signal, improved signal processing can subsequently be performed. Thus, with the aid of the initial calibration, the antenna array can be made more precise or improved by a first calibration. The initial calibration is, for example, an initial calibration. This means that subsequent signal processing can be improved at an early stage.

[0036] Another aspect of the invention relates to an antenna array with an evaluation unit, wherein the antenna array has a plurality of antenna elements and wherein the antenna array is designed to carry out the method according to one of the preceding aspects or an advantageous development thereof.

[0037] In particular, the embodiments of the aforementioned aspects can be used as advantageous embodiments of antenna arrays. Antenna arrays can be referred to as, for example, antenna modules or antenna groups. For example, antenna arrays can be used as transmitting and / or receiving units for environmental detection.

[0038] The antenna array has a large number of antenna elements or elementary antennas which are in turn connected to form an array. In particular, the proposed antenna array has an improved resolution.

[0039] In one exemplary embodiment, in particular another aspect provides that the antenna array is configured as a sparse antenna array. In particular, the antenna array can be an irregular antenna array, in particular a "sparse array configuration," and thus the antenna array can be manufactured or produced more cost-effectively, since a smaller number of actual antenna elements are required to form the antenna array.

[0040] Another aspect of the invention relates to a sensor system having at least one antenna array designed according to one of the aforementioned aspects or advantageous developments thereof. In particular, the sensor system can have the antenna array described above or at least one antenna array described in this manner.

[0041] The sensor system according to the present invention can utilize distributed antennas to reduce the data transmission load in radar systems where the radar sensor devices are used as intended. For example, the radar system can be used in motor vehicles. The radar system can also be used in a variety of technical applications. For example, the radar system can be used in aviation, navigation, automation, or communications technology.

[0042] In particular, such sensor systems can be used, for example, in at least partially autonomous motor vehicles, but particularly also in fully autonomous motor vehicles. However, to achieve such automated driving, safe awareness of the surrounding environment is crucial. Sensors such as radar, lidar, and cameras are used to record the surrounding environment. A holistic, 360-degree, three-dimensional image of the environment is particularly important so that all static and dynamic objects can be detected. Redundant and robust environmental detection plays an important role, particularly with lidar, as this type of sensor can accurately measure distances and can also be used for classification. However, these lidar sensors are expensive and complex. 360-degree, three-dimensional environmental detection is particularly challenging because either many smaller individual sensors, often operating with many separate light source and detector elements, are required to ensure this, or a large lidar sensor is required. Furthermore, lidar sensors are susceptible to weather conditions such as rain, fog, or direct sunlight. The sensor system according to the present invention can provide a remedy in this regard.

[0043] Radar sensors or radar systems, particularly sensor systems, are also well-established in motor vehicle manufacturing and provide reliable and fail-safe data in all weather conditions. Even conditions with poor visibility, such as rain, fog, snow, dust, and darkness, have little impact on their perception reliability. However, resolution has been limited to date, particularly since the tandem radars currently in use are only designed with a resolution of around 7°. To meet the demands for higher levels of automation in motor vehicle construction with safety features, radar systems are required to provide high-resolution three-dimensional images in the range of 0.1° or less and exhibit high insensitivity to interference from their surroundings. This is unattainable with conventional radar technology due to the low resolution of such systems. To significantly improve resolution, the radar system according to the present invention can be used. By integrating electronic and photonic components on a single system-on-a-chip (SoC), i.e., a single semiconductor chip, the resolution of photonic sensor systems can be increased.

[0044] For example, silicon photonics technology can be used to co-integrate photonic and electronic components on a single system-on-chip. This enables the monolithic integration of photonic components, high-frequency electronics, and digital electronics on a single integrated circuit or chip. Such systems offer the advantage of being able to perform signal transmission of GHz signals using optical carrier signals in the terahertz frequency range.

[0045] FMCW signal generation, as well as all signal processing and evaluation, is performed by a central station (e.g., a computing device). Each transmit and receive module consists of an electronic-photonic co-integrated chip (a so-called "EPIC chip") using silicon photonics technology. This allows the monolithic integration of photonic components, high-frequency electronics, and digital electronics on a single chip ("EPIC"). The transmitted signal is modulated at 1 / 8 the radar frequency and sent via optical fiber to the antenna chip. This frequency is then octupled so that the antenna chip can emit the radar radiation. Signal detection is performed in reverse. All data is processed at the central station.

[0046] By distributing EPIC chips or antenna elements over a large area on the vehicle surface and coherent signal processing of the individual antennas, it is possible to refine the resolution to within 0.1°. Sparse array configurations can also be used. However, this results in an unfavorable contrast between the amplitudes of the main lobe and side lobes, resulting in additional effort in the signal processing for target detection and potential ambiguity in target detection. Sensor systems can provide a remedy in this regard.

[0047] A further aspect of the invention relates to a vehicle having a sensor system designed according to the aforementioned aspect or advantageous developments thereof.

[0048] In particular, vehicles can be highly automated, partially autonomous, or fully autonomous. Sensor systems are used to detect the vehicle's surroundings. This is particularly necessary for driver assistance systems or other vehicle systems.

[0049] Another use of the invention is to use those already described in lidar systems, camera systems or satellite communication systems.

[0050] An environmental sensor system, and in particular a sensor system, can be understood as a sensor system capable of generating sensor data or sensor signals that depict, represent, or reproduce the environment of the environmental sensor system. In particular, the ability to detect electromagnetic or other signals from the environment is not sufficient for a sensor system to be considered an environmental sensor system. For example, cameras, radar systems, lidar systems, or ultrasonic sensor systems can be considered environmental sensor systems.

[0051] A computing unit, in particular an evaluation unit, can be understood as a data processing device comprising processing circuitry. Thus, a computing unit can, in particular, process data to perform computational operations. This can also include operations that perform indexed accesses to data structures, such as translation tables (LUTs) ("look-up tables").

[0052] In particular, a computing unit may include one or more computers, one or more microcontrollers, and / or one or more integrated circuits, such as one or more application-specific integrated circuits (ASICs), one or more field-programmable gate arrays (FPGAs), and / or one or more system-on-a-chip (SoCs). A computing unit may also include a physical or virtual network of computers or other of the aforementioned units.

[0053] In various exemplary embodiments, a computing unit includes one or more hardware and / or software interfaces and / or one or more memory units.

[0054] Advantageous embodiments of one aspect of the invention may be considered advantageous embodiments of all other aspects of the invention, and vice versa.

[0055] For applications or application cases that can be generated by the method and are not explicitly described here, it can be provided that according to the method, error messages and / or requests for user feedback are output and / or standard settings and / or predetermined initial states are set.

[0056] The present invention also includes improvements of the antenna array according to the invention, the sensor system according to the invention, and the vehicle according to the invention, which have the features already described in conjunction with the improvements of the method according to the invention. Therefore, the corresponding developments of the antenna array according to the invention, the sensor system according to the invention, and the vehicle according to the invention will not be described here.

[0057] The invention also includes combinations of features of the described embodiments.

[0058] The following describes exemplary embodiments of the present invention. In the accompanying drawings:

[0059] Figure 1 exemplarily showing antenna elements of an antenna array with different views of a vehicle having different arrangements;

[0060] Figure 2 A schematic diagram of a sensor system is shown, the system having at least one sensor having a Figure 1 Antenna array;

[0061] Figure 3 Shown in Figure 2 An exemplary sequence of a method for using linear prediction in a sensor system;

[0062] Figure 4 An exemplary embodiment showing how multiple antenna elements form an overall antenna array;

[0063] Figure 5Another exemplary embodiment showing how multiple antenna elements form an overall antenna array;

[0064] Figure 6 A schematic diagram showing a transmission lobe formed by combining multiple antenna elements;

[0065] Figure 7 A local signal curve 9 showing an exemplary transformation of the received signal of a sampled antenna array;

[0066] Figure 8 An exemplary representation showing an arrangement of antenna elements in a sparse array configuration in azimuth is shown;

[0067] Figure 9 an exemplary representation showing the arrangement of antenna elements 4 in a sparse array configuration in elevation; and

[0068] Figure 10 An exemplary comparison of the evaluation of the predicted angular spectrum of a 32-element patch antenna with discrete Fourier transform and linear prediction methods is shown.

[0069] The embodiments described below are preferred embodiments of the present invention. In the exemplary embodiments, the components described each represent individual features of the present invention that can be considered independently of one another, which also develop the present invention independently of one another, and are therefore also considered to be part of the present invention individually or in combinations different from the combinations shown. In addition, the exemplary embodiments described can also be supplemented by further features of the present invention that have already been described.

[0070] In the figures, functionally identical elements are provided with the same reference numerals.

[0071] Figure 1 Various views or side views of a vehicle 1 are schematically shown. The vehicle 1 may be a highly automated vehicle. In particular, for autonomous driving, safe or efficient environmental perception or detection is crucial. For this purpose, at least one antenna array 2 may be arranged in or on the vehicle 1. The antenna array 2 and / or a plurality of such antenna arrays may be part of a sensor system 3 (see Figure 2 With the aid of the sensor system 3 , an environmental detection, in particular of the vehicle 1 , can be performed.

[0072] Such a sensor system 3 can be, for example, a radar system or a radar sensor system, in particular for use in the automotive sector.

[0073] It is also conceivable that the sensor system 3 is a lidar system, a camera system or a satellite communication system.

[0074] The antenna array 2 or antenna module may consist of a large number or a few individual antenna elements 4 or elementary antennas. These multiple antenna elements 4 may be connected to form an array or antenna array 2.

[0075] In addition to the at least one antenna array 2 , the sensor system 3 can also have an evaluation unit 5 , in particular an electronic one (see Figure 2 The evaluation unit 5 can be referred to as a central station or central processing unit of the sensor system 3 , for example. Signal processing of the sensor system 3 can take place in the evaluation unit 5 .

[0076] For example, each antenna element 4 can be connected or coupled to a conventional or electronic photonic radar chip. The corresponding data from the antenna array 2, and in particular the antenna elements 4, can be transmitted to an evaluation unit 5 or a central data processing unit for signal processing. This can, in turn, be used to control the data to be transmitted, for example, for beamforming or waveform shaping. The evaluation unit 5 can then transmit or transfer the data to an environment model, in particular for environmental detection. In particular, the sensor system 3, and in particular all antenna elements 4 or antenna array 2, can be communicatively connected to the same evaluation unit 5 via electronic or optical connection options. This means that costs can be reduced in terms of the number of control devices and computer units. To enable particularly efficient use of the antenna array 2 in the automotive sector, it is advantageous if the antenna array 2 is configured as a sparse antenna array, i.e., in a sparse array configuration. Thus, the individual antenna elements 4 can be placed or positioned anywhere, in particular in or on the vehicle 1. To this end, the proposed antenna array 2 can achieve refined or improved resolution, i.e., improved accuracy, compared to conventional antenna arrays. For this purpose, linear prediction methods or linear prediction can be used.

[0077] Below Figure 3 Such a process or method is described in . To this end, Figure 3 An example of a possible procedure using the method of linear prediction in the sensor system 3 is shown.

[0078] In this respect, in an exemplary first step S1 , a received signal 8 corresponding to a transmitted signal 7 emitted by the antenna array 2 into the environment 6 , in particular the vehicle 1 , may be received or measured. For this purpose, for example, Figures 4 to 6 It shows how a plurality of antenna elements 4 form the entire array. For this purpose, the received signal or the transmit lobe formed by combining the plurality of antenna elements 4 is mainly located in Figure 6 Shown in.

[0079] In an optional subsequent second step S2, the received signal 8 can be sampled, ie temporally sampled. For this purpose, in particular, the temporal wavefront of the received signal 8 can be sampled to form a local signal.

[0080] In an optional third step S3, an initial calibration of the antenna array 2 may optionally be performed. For this purpose, for example, the sampled receive signal 8 may be used as input.

[0081] In an optional fourth step S4, the sampled received signal 8 can be transformed into a signal curve 9 associated with a plurality of antenna elements 4 of the antenna array 2, in particular a local signal curve 9 (see Figure 7 ). In other words, a transformation of the time signal of the wavefront (i.e. the sampled received signal 8) into a local signal curve (i.e. the signal curve 9) can be performed in the direction of the antenna array 2. In this respect, this is done relative to the azimuth and / or elevation or inclination of the antenna array 2. For this purpose, for example, Figure 8 The arrangement of the antenna elements 4 in a sparse array configuration in azimuth is shown in FIG. Figure 9 In FIG. 1 , the arrangement of the antenna elements 4 in a sparse array configuration in elevation can again be seen. Figure 8 It is also particularly schematically shown that the antenna elements 4 are at a certain distance from one another. In particular, the distance between the individual antenna elements 4 is a multiple of 1 / 2λ.

[0082] In a subsequent optional step S5, an extended signal curve 10 can be predicted based on the signal curve 9 based on linear prediction or linear error propagation. In other words, the expected signal 10 is mapped onto subsequent antenna elements 11 of the antenna array 2 in the case of linear propagation of the expected phase curve. For this purpose, a forward prediction 12 and a backward prediction 13 can be performed for the signal curve 9. This can be done, for example, in Figure 7 Also, for example, Figure 7 : shows the actual aperture 14 of the antenna array 2. The actual antenna aperture is to be understood in particular as the surface over which the antenna elements 4 of the antenna array 2 are arranged in a distributed manner.

[0083] With the help of linear prediction, the resolution of the antenna array 2, in particular the sensor system 3, can be refined or increased. With the help of linear prediction or a linear prediction algorithm, the calculation of the directional spectrum can be performed more precisely based on real data. For this purpose, for example, Figure 10 In , the evaluation of the predicted angular spectrum of a 32-element patch antenna is compared with the methods of discrete Fourier transform 15 and linear prediction 16. Here it can be seen that a finer evaluation or resolution can be achieved by linear prediction.

[0084] In an optional sixth step S6 , a signal curve model can be formed, in particular including the phase curve.

[0085] In another optional seventh step S7, the signal curve model can be used, for example, to calculate intermediate positions between antenna elements 4 or to identify faulty or defective antenna elements. For this purpose, when designing antenna array 2 in a sparse array configuration, additional virtual antenna elements can be formed or generated between real antenna elements 4. Thus, by installing virtual antenna elements 17, 18 between two real antenna elements 4, the distance between them can be shortened. This is particularly advantageous for resolution. In particular, resolution can be improved by increasing the antenna aperture. This can be achieved by providing multiple antenna elements 4. However, to enable the elimination of real antenna elements 4 for cost and space reasons, virtual antenna elements 17, 18 can be added instead using software technology.

[0086] For example, if you want to resolve two objects at a certain angle (i.e., azimuth and elevation), you need an aperture that extends in both directions.

[0087] The distance between the individual antenna elements 4 determines the clearly measurable angular range. Larger antenna spacing can lead to ambiguity in the angle measurement (secondary peaks). Using virtual antenna elements 17 and 18 can remedy this. Most importantly, the contrast between the main lobe and side lobes in the sparse array configuration of antenna array 2 can be improved.

[0088] In a further eighth step S8, the actual signal curve can be reconstructed by an optimization method between the measured phase curve and the signal curve model. In other words, the actual signal curve 21 can be reconstructed based on the predicted extended signal curve 10 (see Figure 7 ).

[0089] For example, the signal curve 21 can be mathematically described using the following formula.

[0090]

[0091] To do this, a model can be identified that predicts further signal values, thereby artificially expanding the true aperture of the antenna array. This can be described by the following formula.

[0092]

[0093] The local aperture signal can be described using the following formula.

[0094]

[0095] You can Defined as interpretable, Defined as unexplainable.

[0096] Use the following formula

[0097]

[0098] It can be described that there is a linear relationship between the signal value and the model coefficients. This can be achieved by minimizing the prediction performance, as shown in the following formula.

[0099]

[0100] In a ninth step S9 , for example, an ideal model or an ideal signal model can then be generated or created, which can in turn be used in a subsequent exemplary tenth step S10 in order to be able to calculate or determine the actual antenna position of the antenna element 4 .

[0101] Using these real antenna positions, it is possible to determine which antenna elements 4 are defective or faulty. Remedial measures can be provided because the virtual antenna can be virtually positioned at the real position of the faulty antenna element 4. Thus, even in the event of a fault or error, the accuracy or functionality of the antenna array 2, and in particular the sensor system 3, can be maintained.

[0102] In a subsequent exemplary eleventh step S11 , a calibration of the antenna array 2 or the sensor system 3 can be performed again based on the real antenna positions and, for example, based on a model.

[0103] In the optional twelfth step S12, a virtual expansion of antenna elements 4 between the individual antennas can be performed, for example, based on the execution of the previous steps S1 to S11. This allows for an increase in the contrast between the main lobe and the side lobes. Furthermore, a virtual expansion beyond the physical array boundaries of antenna array 2 can be achieved. This can improve resolution and increase the response range, primarily by improving the SNR (signal-to-noise ratio). Furthermore, a cross-check of the signal model can be performed, for example, by tracking real data.

[0104] Furthermore, it is conceivable that the information obtained from steps S1 to S11 is used to provide antenna information, which can be used to provide an improved control method for the antenna array 2.

[0105] Reference Signs List

[0106] 1 vehicle

[0107] 2-antenna array

[0108] 3-sensor system

[0109] 4 antenna elements

[0110] 5 assessment units

[0111] 6 Environment

[0112] 7 Transmitting signal

[0113] 8Receive signal

[0114] 9Signal curve

[0115] 10 Extended signal curve

[0116] 11 Subsequent antenna elements

[0117] 12 Forward Prediction

[0118] 13 Backward Prediction

[0119] 14 True Aperture

[0120] 15 Discrete Fourier Transform

[0121] 16 Linear Prediction

[0122] 17,18,20 virtual antenna elements

[0123] 19 defective real antenna elements

[0124] 21 Actual signal curve

Claims

1. A method for determining information of an antenna array (2) having a plurality of antenna elements (4), wherein the following steps are performed: - receiving a received signal (8) corresponding to a transmitted signal (7) emitted by the antenna array (2) into the environment (6); - sampling the received reception signal (8); - transforming the sampled received signal (8) into a signal curve (9) associated with a plurality of antenna elements (4) of the antenna array (2) by means of an evaluation unit (5); - predicting an extended signal curve (10) by the evaluation unit (5) based on a linear prediction of the signal curve (9); - reconstructing the actual signal curve (21) of the received signal (8) based on the predicted extended signal curve (10); - Determining antenna information of the antenna array (2) by the evaluation unit (5) based on the reconstructed actual signal curve (21).

2. The method according to claim 1, It is characterized by: The sampled received signal (8) is transformed into a signal curve, in particular a local signal curve, based on the azimuth angle and / or elevation angle of the antenna array (2).

3. The method according to claim 1 or 2, It is characterized by: The actual signal curve (21) is reconstructed with the aid of an optimization method between the signal curve (9) and the expanded signal curve (10).

4. The method according to any one of the preceding claims, It is characterized by: An ideal signal model of the antenna array (2) is generated based on the actual signal curve (21).

5. The method according to claim 4, It is characterized by: The actual antenna position of at least one antenna element (4) of the antenna array (2) is determined based on the ideal signal model.

6. Method for operating an antenna array (2) having a plurality of antenna elements (4), wherein antenna characteristics of the antenna array (2) are adjusted as a function of antenna information determined according to one of the preceding claims.

7. The method according to claim 6, It is characterized by: The antenna array (2) is calibrated according to the antenna information.

8. The method according to claim 6 or 7, It is characterized by: At least one virtual antenna element (17, 18, 20) is generated for the antenna array (2) based on the antenna information.

9. The method according to claim 8, It is characterized by: A virtual antenna position of at least one virtual antenna element (17, 18, 20) is determined such that the at least one virtual antenna element (17, 18, 20) can be arranged between two real antenna elements (4) of the antenna array (2).

10. The method according to claim 8 or 9, It is characterized by: A virtual antenna position of at least one virtual antenna element (17, 18, 20) is determined so that a missing or functionally impaired real antenna element (19) of the plurality of antenna elements (4) is replaced by the at least one virtual antenna element (17, 18, 20).

11. The method according to any one of the preceding claims 6 to 10, It is characterized by: An initial calibration of the antenna array (2) is performed based on the sampled received signal (8).

12. An antenna array (2) having an evaluation unit (5), wherein the antenna array (2) has a plurality of antenna elements (4), and wherein the antenna array (1) is designed to carry out the method according to one of claims 6 to 11.

13. The antenna array (2) according to claim 12, It is characterized by: The antenna array (2) can be configured as a sparse antenna array.

14. A sensor system (3) comprising at least one antenna array (2) according to claim 12 or 13.

15. A vehicle having a sensor system (3) according to claim 14.

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