Method for determining target information of at least one target object in an environment of a sensor system on the basis of an SAR algorithm, and also sensor system and vehicle

Abstract

The invention relates to a method for determining target information of a target object (12), wherein – each transmitting element emits a transmission signal (11) into the environment (2) in temporally successive transmission processes, – a reception signal (13) corresponding to the associated transmission signal (11) is received by the plurality of receiving elements (5), – a plurality of virtual antenna elements (14) are generated on the basis of the plurality of receiving elements (5) and an associated received reception signal (13), – a signal profile (15, 16, 17) is determined for an associated distance range (18, 19, 20) on the basis of the reception signals assigned to this distance range (18, 19, 20), – an extended signal profile is predicted on the basis of a linear prediction of the signal profile (15, 16, 17), – a target signal is reconstructed on the basis of an extended signal profile of an associated distance range (18, 19, 20), and – the target information of the target object (12) is determined on the basis of the reconstructed target signal. Moreover, the invention relates to a sensor system (1) and to a vehicle (7).

Description

[0001] Description

[0002] Method for determining target information of at least one target object in an environment of a sensor system based on a SAR algorithm, as well as sensor system and vehicle

[0003] The invention relates to a method for determining target information of at least one target object in the environment of a sensor system having at least one antenna array, wherein the at least one antenna array has a plurality of transmitting elements and a plurality of receiving elements. Furthermore, the invention relates to a sensor system having at least one antenna array, which has a plurality of transmitting elements and a plurality of receiving elements, and at least one electronic evaluation unit. The invention also relates to a vehicle having a sensor system.

[0004] For automated driving, the safest possible perception of the environment is essential. The environment is recorded using sensors such as radar, LiDa, and cameras. A holistic 360-degree 3D detection of the environment is particularly important, so that all starting aids and dynamic objects are detected. LiDa, in particular, plays a key role with its redundant, robust environment detection, as this type of sensor can precisely measure distances in the environment detection and can also be used for classification. However, these sensors are cost-intensive and complex to set up. 360-degree 3D environment detection is particularly problematic, as either many smaller individual sensors are required to ensure this, which usually work with many individual light sources and detector elements, or large sensors are installed. Furthermore, LiDa systems are susceptible to weather influences such as rain, fog, or direct sunlight.Radar sensors have been established in the automotive sector for years and deliver stable and reliable data in all weather conditions. Even poor visibility conditions such as rain, fog, snow, dust, or darkness barely affect their detection and reliability. However, their resolution is currently limited. Radar sensors currently in use have a resolution of approximately 7 degrees. To meet the requirements for autonomy levels 4 and 5, or stages 4 and 5 of automated driving with safe driving functions, radar sensors must be able to deliver three-dimensional images with fine resolution in the range of 0.1 degrees and even finer, with greater immunity to disturbances from their surroundings. This cannot be achieved with conventional radar technology because the resolution of such systems is too low.An object of the present invention is to improve, in particular to refine, the resolution of a sensor system or a detection system.

[0005] This problem is solved by a method, a sensor system, and a vehicle according to the independent patent claims. Useful further developments arise from the dependent patent claims.

[0006] One aspect of the invention relates to a method for determining target information of at least one target object in an environment of a sensor system which has at least one antenna array, wherein the at least one antenna array has a plurality of transmitting elements and a plurality of receiving elements, wherein

[0007] - In particular, each transmitting element of the plurality of transmitting elements transmits a transmission signal into the environment of the sensor system in successive transmission processes,

[0008] - In particular, a reception signal corresponding to the respective transmission signal is received by the plurality of reception elements after a respective transmission element has transmitted a respective transmission signal,

[0009] - In particular, on the basis of the plurality of receiving elements and a respective received signal, a plurality of virtual antenna elements are generated, wherein at least one virtual antenna element of the plurality of virtual antenna elements can be arranged virtually between two adjacent receiving elements,

[0010] - In particular, a respective received signal is assigned to a distance range,

[0011] - In particular, for a respective distance range, a signal curve is determined in relation to the plurality of receiving elements and the plurality of virtual antenna elements on the basis of the received signals assigned to this distance range,

[0012] - In particular, an extended signal curve is predicted based on a linear prediction of the specific signal curve of a respective distance range,

[0013] - In particular, on the basis of a respective predicted extended signal curve of a respective distance range, an actual target signal relating to the at least one target object is reconstructed, and

[0014] - In particular, the target information of the at least one target object is determined based on the reconstructed actual target signal. The proposed method enables a sensor system to be operated more efficiently by improving, in particular refining, the resolution of the sensor system. Furthermore, the proposed method can compensate for parallax effects in large antenna devices or devices of the sensor system. Contrary to the conventional approach of setting up a virtual device by moving a sensor, the virtual device is set up by temporally synthesizing individual antennas arranged over a large area. The basic prerequisites for applicability are coherent reception properties of the individual antennas and the MIMO (multiple input multiple output) principle.In particular, alternating transmission processes generate new virtual antennas whose positions cover the free space between the physically installed antennas, but whose spatial distances from each other do not satisfy the Nyquist criterion. The proposed method can remedy this situation.

[0015] After completing a transmission process within an M1 MO cycle, each virtual receiving antenna (real receiving element) receives a received signal that is temporally shifted from the transmitted signal. For the applicability of, for example, a SAR algorithm, the number of virtual receiving antennas or real receiving elements is too sparse, so the missing received signals must be compensated for using a model function through linear prediction or non-linear prediction. The model signal, based on the received signals, calculates a hypothetical received signal for each receiving antenna, which would be required to meet the Nyquist criterion and thus for the applicability of, for example, SAR (synthetic aperture radar) algorithms.

[0016] In this regard, in successive transmission processes, each transmission element, i.e., a transmission antenna, of the multiple transmission elements can transmit a respective or separate transmission signal, in particular an electrical signal, into the environment of the sensor system. After each transmission process has been carried out, a respective reception signal corresponding to the transmitted transmission signal can be received or detected by the multiple reception elements, i.e., reception antennas. In other words, the transmitted transmission signals can be reflected in the environment, for example, upon impact with at least one target object or multiple target objects, so that this back reflection can be received by one or more reception elements. For this purpose, the sensor system, which can be a detection system, such as a radar system, can have at least one antenna array or multiple antenna arrays.Such an antenna array comprises a number of real transmitting elements and real receiving elements. These can be arranged in a distributed manner depending on the application. When using the sensor system in the automotive sector, for example, the transmitting elements and the receiving elements can be arranged distributed throughout the vehicle. In this case, it may be the case that the number and especially the arrangement of the real transmitting elements and the real receiving elements is too sparse, which could result in inaccurate target detection or acquisition. To remedy this, several virtual antenna elements can be generated based on the multiple receiving elements and a respective received signal and the multiple virtual antenna elements.In other words, after each transmission process, virtual antenna elements, i.e. system-generated antenna elements, can be generated based on the one or more received signals and the corresponding receiving elements. This can be done, for example, using an electronic evaluation unit of the sensor system or another computing unit of the sensor system. In other words, after each transmission process, the signals received by one or more receiving elements can be checked to determine whether a sufficient number of real receiving elements are present to perform the corresponding signal evaluation. To achieve this, one or more virtual antenna elements can be generated by the system.In this case, these virtual antenna elements are generated in such a way that, for example, at least one virtual antenna element is generated between two adjacently arranged real receiving elements in order to be able to virtually compensate or fill this free space between the real receiving elements on the system side.

[0017] Based on each received signal, an assignment or classification to a distance range can be performed. This can be done by the evaluation unit, for example. The distance ranges can be range gates. Since a wide variety of signals are emitted into the environment and, depending on the transmission and the nature of the environment, the signals can travel different distances, a specific reception distance range exists for each received signal, for example, a distance between the received receiving element and the respective target object. Above all, received signals that have the same distance gate index can be assigned to a corresponding distance range.Subsequently, a signal profile, in particular a local signal profile, can be determined or generated for a respective distance range. In this case, in particular index-identical received signals with regard to the respective distance range can be generated to form a signal profile with regard to the plurality of real receiving elements and the plurality of virtual antenna elements. Subsequently, an extended signal profile or a model signal can be predicted for a respective distance range on the basis of a linear prediction or on the basis of a non-linear prediction. This can be done depending on a Nyquist criterion. Using the electronic evaluation unit, for example, or another computing unit, an actual target signal with regard to the at least one target object can then be deconstructed, mapped or reproduced, in particular on the system side and / or automatically.This offers the advantage that the resolution can be increased even if the number of real antenna elements is insufficient. However, this can be compensated for by generating virtual antenna elements and selecting or analyzing them with respect to the individual distance ranges. Based on the reconstructed actual target signal, the required target information, such as a target angle or target speed, can be generated for the target object and, for example, provided or transmitted to an environment model for environment detection. For example, the sensor system can be calibrated based on linear prediction.

[0018] The proposed method enables diagnostic capability and reliability testing in the event of a fault. Furthermore, compensation can be performed in the event of the failure of individual real elements, thus increasing the robustness of the sensor system. For example, after the failure of individual real antenna elements, the antenna array can be reconfigured so that the array does not have to be replaced. This can be achieved by generating virtual antenna elements. The procedure of the method according to the invention can refine or increase the resolution and, in particular, the accuracy of the sensor system. Thus, the detection range of the sensor system can also be increased.The smaller number of required real antenna elements allows for cost-effective production of the antenna array while still maintaining a refined resolution of the overall system or the transmission system. Furthermore, the actual target signal can be used, for example, as a calibration method. Furthermore, the proposed method for sensor systems offers the advantage of cost savings in control units and processing units.

[0019] The proposed method can be applied or transferred to Lida, camera and satellite communication systems.

[0020] In particular, the proposed method may be a computer-implemented method.

[0021] Above all, the proposed method offers the advantage that the Nyquist criterion can still be met in sensor systems designed in a sparse array configuration. This prevents ambiguities in the antenna pattern, allowing target direction to be improved. Furthermore, the proposed method allows the use of large antenna arrays, allowing distance changes between the individual antenna elements and a target object to be linearly simulated, unlike conventional applications.

[0022] In the exemplary embodiment, it is provided that the respective actual target signal is based on a synthetic aperture radar algorithm (Synthetic Aperture Radar Algorithm), a backprojection algorithm, a range cell migration algorithm (Range Cell Migration Algorithm) or a robust multi-field analysis algorithm (RMS).

[0023] "Robust Multiarray Analysis Algorithm"). Thus, a wide variety of algorithms can be used to achieve improved target detection and, in particular, improved resolution in a sparse array configuration of a sensor system. Above all, the use of the algorithm just mentioned can still achieve accurate target detection with an overall high detection range despite the sparsely populated real antenna elements of the antenna array.

[0024] The application of algorithms, particularly from the family of synthetic aperture radar (SAR) algorithms, enables the construction of large virtual devices by synthesizing many individual radar measurements along a path traveled by a moving transmission system, such as a radar system. After applying the reconstruction steps of a SAR algorithm, the constructed virtual device possesses the same properties as an equivalent physical device of the same dimensions. This advantageously utilizes this feature. Compliance with the Niquist criterion, which in the case of a synthetic device refers to the spatial separation between consecutive individual measurements, is essential for this construction step.

[0025] A As = -

[0026] 4 with As as the spatial distance between successive measurement positions and A a wavelength of the carrier signal.

[0027] A characteristic feature of the application of SAR algorithms during the design step is the alignment of a sensor, or rather the respective individual transmitting or receiving elements, perpendicular to the direction of movement of a carrier platform in order to cover the largest possible apparatus. With the present invention, the conventional application of SAR algorithms can be expanded by aligning the sensor, for example, in the direction of travel of the carrier platform. This can be particularly the case when the sensor system is used in the automotive sector.

[0028] Contrary to the conventional approach of creating a virtual device by moving a sensor, the virtual device is created through the temporal synthesis of large-area arrays of individual antennas. The basic prerequisites for its applicability are coherent reception characteristics of the individual antennas and the MIMO principle. For this purpose, alternating transmission processes generate new virtual antenna elements whose positions in the free space between the physically installed antennas, especially in real receiving elements, cover spatial distances that do not solely satisfy the Niquist criterion. This can be solved accordingly with the present invention.

[0029] The antenna array can be designed, for example, as a group antenna or as a phased array antenna.

[0030] In one embodiment, it is provided that a synthetic antenna array is generated based on a respective predicted extended signal profile of a respective distance range, the plurality of transmit elements, the plurality of receive elements, and the plurality of virtual antenna elements, wherein the synthetic antenna array is taken into account when reconstructing the actual target signal. In other words, a virtual antenna array, which can be referred to as a synthetic antenna array, can be generated via an M1 MO cycle. This can thus be done on the system side, so that the synthetic antenna array is an antenna array generated on the antenna system side, which generates both real antenna elements and virtual antenna elements.This allows for system-side synthesis of a fully populated array, thus eliminating or reducing the disadvantages of a sensor system with a sparse array configuration. The system-generated synthetic antenna array can then be used to reconstruct the actual target signal, particularly based on a SAR algorithm.

[0031] In one embodiment, it is provided that a hypothetical received signal is determined based on a respective predicted extended signal profile of a respective distance range or distance gate for at least one virtual antenna element and a plurality of virtual antenna elements. This at least one hypothetical received signal can be taken into account when reconstructing the actual target signal. After the plurality of virtual antenna elements have been generated and at least one virtual antenna array has been virtually positioned there between, for example, two adjacently arranged real receiving elements, a respective system-generated, in particular hypothetical, received signal for the respective virtual antenna element can be generated based on the adjacent real receiving elements and the received signals received by them or on other received signals of the plurality of real receiving elements.Thus, the synthetic antenna array or the virtual antenna array for system-side analysis can have a sufficient number of corresponding signals in order to subsequently provide the actual target signal for the respective target detection.

[0032] In one embodiment, a distance spectrum is determined based on a respective received signal from the plurality of receiving elements and / or the plurality of virtual antenna elements. The distance spectrum is a "range spectrum." For example, a corresponding distance spectrum can be calculated or generated based on the received signals and the virtually generated, in particular hypothetical, signals. In other words, a range spectrum can be calculated based on the received signals from both the real and the virtual antennas. This can be used to improve linear prediction. For linear prediction, it is advantageous to compensate for interfering phase terms. This can be achieved accordingly with the help of the distance spectrum.

[0033] For this compensation of the interfering phase terms, in a further embodiment, a range Doppler spectrum can be determined based on the range spectrum, on the basis of a respective received signal, on the basis of the multiple receiving elements, and / or on the basis of the multiple virtual antenna elements. This range Doppler spectrum, or "range Doppler spectrum," can be used to perform the corresponding compensation of the interfering phase terms, thus improving or enabling the applicability of the SAR algorithms.

[0034] In a further embodiment, potential target objects, i.e., hypothetical target objects, in the surrounding area can be identified based on the range-Doppler spectrum. In addition, a Doppler velocity of each potential target object can be determined. For example, using suitable detection algorithms, such as a CFAR threshold, after the range and range-Doppler spectrum calculation, potential targets can be identified and, in particular, their Doppler velocity can be calculated. Based on the determined Doppler velocity, the interfering phase terms can be compensated.

[0035] In one embodiment, a phase filter is determined based on the Doppler velocity and the potential target objects, whereby a respective received signal can be adjusted depending on the phase filter. In other words, a corresponding phase filter can be calculated based on the determined Doppler velocity, which can compensate for the Doppler phase term in each received signal. A received signal without an interfering phase term can then form the starting point for the application of the SAR algorithms.

[0036] The presented method can be a computer-induced method. Therefore, a further (independent) aspect of the invention relates to a computer program with program code means which cause an electronic computing device, when the program code means are processed by the electronic computing device, to carry out a method according to the previous aspect or an advantageous embodiment. Accordingly, a further aspect of the invention also relates to a computer-readable storage medium with a computer program product. A further aspect of the invention relates to a sensor system with at least one antenna array, which has a plurality of transmitting elements and a plurality of receiving elements and at least one electronic evaluation unit, wherein the sensor system is designed to carry out a method according to the previous aspect or an advantageous development thereof.

[0037] In particular, the sensor system can be a detection system, such as a radar system, LIDA system, camera system, or other environment detection system. The antenna array can, for example, be configured as a sparsely populated antenna array.

[0038] With the help of the proposed sensor system, improved environment detection and, in particular, improved target detection can be achieved.

[0039] A further aspect of the invention relates to a vehicle with a sensor system according to the previous aspect and an advantageous development. Above all, the vehicle can be a motor vehicle, such as a passenger car or a truck. In particular, the vehicle can be a highly automated vehicle, such as an at least partially autonomously or fully autonomously operated vehicle.

[0040] For this purpose, the environment or surroundings of the vehicle can be recorded with the help of the sensor system so that a corresponding environmental detection can be carried out in order to be able to make this available to driver assistance systems, vehicle guidance systems or other assistance systems of the vehicle.

[0041] Advantageous embodiments of one aspect can be considered advantageous embodiments of the other aspects or of all other aspects. The same applies in reverse.

[0042] For applications or application situations that may arise during the method and that are not explicitly described here, it can be provided that, according to the method, an error message and / or a request to enter user feedback is output and / or a default setting and / or a predetermined initial state is set. The invention also includes developments of the sensor system according to the invention and of the vehicle according to the invention that have features as already described in connection with the developments of the method according to the invention. For this reason, the corresponding developments of the sensor system according to the invention and of the vehicle according to the invention are not described again here.

[0043] The invention also includes combinations of the features of the described embodiments.

[0044] Exemplary embodiments of the invention are described below. Shown are:

[0045] Fig. 1 is a schematic representation, in particular a representation in block diagrams, of a sensor system;

[0046] Fig. 2 shows a schematic arrangement of transmitting elements and receiving elements of the sensor system from Fig. 1 on a vehicle;

[0047] Fig. 3 shows, starting from Fig. 2, the creation of virtual antenna elements by successive transmission processes of different transmission elements;

[0048] Fig. 4 shows a further transmission process starting from Fig. 3;

[0049] Fig. 5 shows, starting from Fig. 4, another transmission process in order to be able to generate further virtual antenna elements;

[0050] Fig. 6 shows schematic signal waveforms of the received signals of the receiving elements as well as the virtual antenna elements;

[0051] Fig. 7 shows, starting from Fig. 6, how the missing signal areas or signal components can be filled by linear prediction;

[0052] Fig. 8 shows a schematic sequence for determining target information of a target object by using a SAR algorithm in the sensor system of Fig. 1 with a "sparse array configuration"; Fig. 9 shows an exemplary sequence of a method for using linear prediction in the sensor system of Fig. 1;

[0053] Fig. 10 shows an exemplary transformed, local signal curve of a sampled received signal of the antenna array of the sensor system from Fig. 1;

[0054] Fig. 11 shows an exemplary comparison of an evaluation of a predicted angular spectrum of a 32-element patch antenna compared to a method of discrete Fourier transformation and linear prediction;

[0055] Fig. 12 shows, by way of example, various views of a vehicle with different arrangements of antenna elements of the antenna array;

[0056] Fig. 13 shows an exemplary representation of an arrangement of the transmitting and receiving elements in sparse array configuration in azimuth;

[0057] Fig. 14 shows an exemplary representation of an arrangement of the transmitting and receiving elements in sparse array configuration in elevation;

[0058] Fig. 15 shows an exemplary embodiment of how several antenna elements form an entire antenna array;

[0059] Fig. 16 shows another exemplary embodiment of how multiple antennas form an entire antenna array; and

[0060] Fig. 17 shows a schematic representation of an emission lobe formed by combining several antenna elements.

[0061] The exemplary embodiments explained below are preferred exemplary embodiments of the invention. In the exemplary embodiments, the described components each represent individual features of the invention that can be considered independently of one another. These features also further develop the invention independently of one another and are therefore to be considered as components of the invention, either individually or in a combination other than that shown. Furthermore, the described exemplary embodiments can also be supplemented by further features of the invention already described. In the figures, functionally identical elements are each provided with the same reference numerals.

[0062] Figure 1 shows an exemplary and sometimes schematic representation of a sensor system 1. The sensor system 1 can be a radar system for the automotive sector. It is also conceivable that the sensor system 1 can be a lidar system, camera system, and / or satellite communication system. With the help of the sensor system 1, in particular, an environmental detection or environmental perception of an environment 2 of the sensor system 1 can be performed. This is particularly advantageous in the automotive sector.

[0063] The sensor system 1, which is in particular an electronic system or an electronic device, can have at least one antenna array 3 or several such antenna arrays. Such an antenna array 3 can in turn have several, in particular real, transmitting elements 4 and several, in particular real, receiving elements 5. In this regard, Fig. 1 schematically shows a conceivable embodiment of a structure of a transmitting element 4 and a structure of a receiving element 5. The additional or numerous transmitting and receiving elements 4, 5 can be configured analogously.

[0064] In addition to the at least one antenna array 3, the sensor system 1 can have an electronic evaluation unit 6. This electronic evaluation unit 5 can be referred to as the central station or central processing unit of the sensor system 1. Signal processing in the sensor system 1 can be carried out using this electronic evaluation unit 6. For example, the transmitting and receiving elements 4, 5 can each be connected or coupled to conventional or electronic EPIC (electronic photonic integrated circuit) radar chips. The respective data of the antenna array 3 and in particular of the transmitting and receiving elements 4, 5 can be transmitted to the electronic evaluation unit 6 or to the central data processing unit for signal processing.

[0065] The electronic evaluation unit 6 can, in turn, transfer or transmit the data to an environment model, in particular for environment detection. In particular, the sensor system 1 and in particular all transmitting and receiving elements 4, 5 can be communicatively connected via electronic or optical connections. This can result in cost savings because the number of control units and computing units is lower. In order to be able to use the antenna array 3 particularly efficiently in the automotive sector, it is advantageous if the antenna array 3 is used as a sparsely populated antenna array, i.e., in a sparse array configuration or sparse matrix configuration. Accordingly, the individual transmitting and receiving elements 4, 5 can be placed or positioned as desired, in particular in or on a vehicle 7 (see Fig. 11).For this purpose, the proposed antenna array 3 can have a simplified or improved resolution, i.e., improved accuracy, compared to a conventional antenna array. A linear prediction method or linear prediction can be used or applied for this purpose.

[0066] For example, the electronic evaluation unit 6 can be referred to as an electronic computing device. The transmitting elements 4 can be transmitting antennas, and the receiving elements 5 can be receiving antennas. For example, in the present case, the electronic-photonic integrated circuits (EPICs) and their components are provided with the reference numeral 8. This shows special grating couplers and photodiodes for a transmitter, as well as two grating couplers, photodiodes, and a modulator for the receiver (receiving element 5). The electronic components are provided with the reference numeral 9. This can refer to analog-to-digital converters, quadrature amplitude modulators, signal processing units, "bias", frequency multipliers, or amplifier units. Furthermore, the optical components 10, in particular optical fibers, are shown accordingly.

[0067] For example, Fig. 1 shows that a central station, specifically the electronic evaluation unit 6, generates an optical carrier frequency. This is modulated at, for example, one-eighth of the carrier frequency and sent via the optical fiber to the antenna chips. The frequency is multiplied eightfold there, allowing the radiation to be emitted by the antenna chips. Signal detection occurs in the reverse direction. All data is then processed at the electronic evaluation unit 6.

[0068] In particular, the sensor system 1 can be a photonic radar system to increase the resolution. This involves co-integration of electronic and photonic components in a single semiconductor.

[0069] For example, the generation of an FMCW (continuous wave radar signal) or a comparable signal, such as PNCW (continuous wave)), CDMA (Code Division Multiple Access), or pulse signal, as well as the entire signal processing and evaluation, can be performed centrally by the electronic evaluation unit 6. Each transmit and receive module, i.e., the transmit and receive elements 4, 5, consist of an electronic-photonic co-integrated chip. Silicon photon technology can be used for the co-integration. This enables the monolithic integration of photonic components, radio-frequency electronics, and digital electronics together on a single chip—i.e., electronic-photonic co-integration. The technical integration of such a system lies in the signal transmission of gigahertz signals using an optical carrier signal in the terahertz frequency range.A central station generates an optical carrier frequency in the terahertz range, for example. The signal to be transmitted is modulated on this frequency, for example, at one-eighth of a frequency.

[0070] For example, by distributing the EPIC chips over a large area of ​​the vehicle surface and coherently processing the signals of the individual antennas, the resolution can be refined to within 0.1 degrees. A sparse array configuration is used. In this regard, the proposed sensor system 1 and, in particular, the method according to the invention make it possible to prevent unfavorable contrasts between the amplitudes of the main and side lobes, thus avoiding or preventing additional effort in signal processing for target detection and ambiguities in target detection.

[0071] Figure 2 schematically illustrates a schematic arrangement of the antenna array 3, and in particular of the transmitting and receiving antennas 4, 5. These elements 4, 5 can be distributed and, in particular, spaced apart from one another on the vehicle 7. As shown there, for example, the elements 4, 5 are not evenly distributed and are spaced apart from one another at different distances.

[0072] For example, in the following Fig. 3, starting from Fig. 2, it is shown that during a transmission process one of the transmission elements 4 transmits a transmission signal 11 into the environment 2. This transmitted transmission signal 11, which can be an electrical or electronic signal, can be reflected, for example, by a target object 12 in the environment 2, i.e. the area surrounding the vehicle 7. In particular, further such target objects 12 can also be located in the environment 2. In real road traffic, such a target object 12 could be a road user such as another vehicle or a living being. Likewise, the target object 12 can be a static right, such as a traffic barrier or a structure. One or more of the reception elements 5 can in turn receive a reception signal 13 corresponding to the transmitted transmission signals 11.This can be tracked successively. In particular, this occurs after each transmission process, during which a transmission element has always performed a corresponding transmission process. For example, after completing a transmission process within a MIMO cycle, each receiving element 5 can receive such a received signal 13 that is temporally shifted compared to the transmitted signal 11 due to the transmission and reflection. For the applicability of a SAR algorithm, for example, the number of real receiving elements 5 is too sparse, so the missing received signals must be compensated for using a model function through linear or non-linear prediction. In this regard, virtual antenna elements 14 can be generated through the alternating transmission processes.

[0073] As shown by way of example in Fig. 3, a respective virtual antenna element 14 can be generated such that it can be arranged between two adjacent receiving elements 5. This occurs, for example, on the system side or using software. With the help of the virtual antenna elements, the antenna array 2 can therefore be expanded virtually or using software. This process with regard to the generation of the virtual antenna elements 14 can be carried out alternately and in particular after a respective transmission process of one of the transmission elements 4. Thus, a virtual apparatus can be created by chronologically successive transmission processes of different transmission elements 4. Such continuous transmission of a respective transmission signal 11 from a respective transmission element 4 in chronologically successive transmission processes is further shown schematically in Fig. 4 and Fig. 5, for example.

[0074] As can be seen in Fig. 4 and in Fig. 5 starting from Fig. 3, a different transmitting antenna 4 in each case transmits a transmitted signal 11, so that a respective received signal 13 can in turn be received by a wide variety of receiving elements 5. In this regard, it can be seen in Fig. 4 starting from Fig. 3 and in Fig. 5 starting from Fig. 4 that the number of virtual antenna elements 14 is constantly increasing, so that the virtual or synthetic antenna array can be constantly expanded. Fig. 6 now shows signal curves based on the transmitted processes carried out and the generated virtual antenna elements 14. Here, signal curves 15, 16, 17 are shown with regard to a respective received signal 11 in different distance ranges 18, 19, 20.

[0075] Here, the signal waveforms 15, 16, 17, in particular high-value signal waveforms, are actually received signals with respect to the real receiving elements 5 as well as the virtual antenna elements 14. In other words, the amplitude waveforms can be represented here with respect to the distance ranges 15, 16, 17. Above all, Fig. 6 shows the received amplitudes within an index-equivalent distance gate or distance range based on physical and virtual antennas. As shown in Fig. 6, the signal waveforms 15, 16, 17 have gaps or incomplete signal ranges, which means that compliance with the Nyquist criterion and thus the applicability of an SAR algorithm is not precluded.

[0076] In order to solve this problem accordingly, the missing received signals or signal ranges can be compensated for using a model function for linear or non-linear prediction. A model signal can be estimated based on the received signal 13, whereby a hypothetical received signal can be calculated for a respective virtual antenna, which is required to comply with the Nyquist criterion and thus for the applicability of the SAR algorithm. In particular, the following Fig. 7, starting from Fig. 6, shows how missing signal components are estimated using linear prediction to position a fully occupied aperture to fulfill the Nyquist criterion. In other words, with regard to the signal curves 15, 16, 17, a respective extended signal curve can be predicted based on a linear prediction. The corresponding predicted ranges 21 are located between the missing ranges in Fig.7 is now supplemented, resulting in a virtually fully occupied aperture. In other words, the linear prediction and, in particular, the virtual antenna elements 14 can be used to perform a reconstruction, providing an actual target signal, with which, for example, information and the target object 12 can be determined.

[0077] The following Fig. 8 shows a schematic sequence of the method according to the invention for determining target information of the at least one target object 12 or several target objects, in particular in the environment 2 of the vehicle 7.

[0078] In particular, this process illustrates the exemplary use of SAR (synthetic aperture radar) algorithms with sensor systems with a sparse array configuration. In an optional step S10, elementary antennas, such as the transmit and receive elements 4, 5, can be interconnected to form the antenna array 3. A uniform linear array configuration or a sparse configuration can be used.

[0079] In an optional subsequent step S11, conventional or electronic-photonic radar chips can be connected to the elements 4, 5.

[0080] For a subsequent exemplary step S12, data can be transmitted to a central data processing unit, such as the electronic evaluation unit 6, for signal processing of the received data and / or for controlling the data to be transmitted (beam / waveform).

[0081] In an optional step S13, as previously explained, a virtual or synthetic antenna array can be created or spanned over an Ml MO cycle.

[0082] To enable the applicability of SAR algorithms, it is necessary to compensate for interfering phase terms before applying linear prediction. These phase terms are due to the carrier system's own motion, in this case the movement of vehicle 7, as well as to moving objects during a MIMO cycle. To compensate for these phase terms, the received signals of the physical elements 5 as well as the hypothetical signals of the virtual antenna elements 14 are evaluated. For this purpose, a range spectrum can first be calculated in step S14.

[0083] Subsequently, in an optional step S15, a range Doppler spectrum can be calculated or generated based on the range spectrum.

[0084] Subsequently, in an optional step S16, potential targets, i.e. potential or hypothetical target objects, can be determined using detection algorithms such as a CFAR (“false alarm rate”) threshold.

[0085] In an optional subsequent step S17, compensation can be performed for detected Doppler velocities from the range spectrum or beat signal. A respective Doppler velocity can be calculated for each potential target. The compensation can be performed based on a phase filter. Using the phase filter, the Doppler phase terms from a respective received signal can be compensated. This provides a starting point for the subsequent application of the SAR algorithms, resulting in a received signal without interfering received terms.

[0086] In a step S18, a model function can subsequently be applied by linear predictions (equal-index) of sample values ​​or equal-index distance gates or distance ranges 18, 19, 20. In this case, the linear detection can be used not only for calibrating the sensor system 1 but also for refining the triggering capability over equal-index distance ranges 18, 19, 20 with respect to the virtual aperture. In other words, before reconstruction by the SAR algorithms, a model signal can be determined in advance for each equal-index distance gate or distance range 18, 19, 20 across the received signals by linear prediction, which model signal estimates the missing signal components to fulfill the Nyquist criterion. This estimation result forms the starting point for the application of the SAR reconstruction and corresponds to the data occurrence of a fully occupied antenna array.For this purpose, a synthesis of a fully occupied array can be carried out as an intermediate result, in particular in an optional step S19.

[0087] Subsequently, in an optional step S20, synthetic aperture radar algorithms, such as "back projection" or "robust multiarray analysis algorithms," can be used or applied. Thus, using a SAR algorithm, a target angle with respect to the target object 12, i.e., a radar target, can be determined as target information, for example. Subsequently, in a step S21, the corresponding data can be transferred or transmitted to an environment model.

[0088] An example process for a linear prediction is explained below.

[0089] In this regard, in an exemplary step S30, a transmission signal 11 emitted by the antenna array 3 into the environment 2, in particular of the vehicle 7, can be received or measured, respectively. For this purpose, Figs. 15 to 17, for example, show how several transmitting and receiving elements 4, 5 form an entire array. For this purpose, the received signal or emission lobe, which is formed by combining several antenna elements, is shown, in particular, in Fig. 17. In an optional subsequent step S31, the received signal 13 can be sampled, i.e., sampled in time. For this purpose, in particular, the temporal wavefront of the received signal can be sampled to form a local signal.

[0090] In an optional step S32, an initial calibration of the antenna array 3 can be performed if necessary. For this purpose, the sampled received signal can be used as input, for example.

[0091] In an optional step S33, the sampled received signal can be transformed into a, in particular local, signal curve (cf. Fig. 10) in relation to the plurality of elements 4, 5 of the antenna array 3. In other words, a transformation of the temporal signal, i.e. the sampled received signal, of the wavefront into a local signal curve, i.e. the signal curve 15, 16, 17, in the direction of the antenna array 3 can be carried out. In this regard, this takes place in relation to an azimuth angle and / or an elevation or a height angle of the antenna array 3. For this purpose, for example, Fig. 13 shows the arrangement of the antenna elements 4, 5 in a sparse array configuration in azimuth. Fig. 14 again shows the arrangement of the antenna elements 4, 5 in a sparse array configuration in elevation.Figure 13 further illustrates, particularly schematically, that the antenna elements 4, 5 are spaced apart from one another. In particular, the individual antenna elements 4, 5 are spaced apart from one another by a multiple of 1 lambda.

[0092] In a subsequent optional step S34, an extended signal waveform can be predicted based on the signal waveform based on a linear prediction or a linear error propagation. In other words, the expected signal is mapped onto the subsequent antenna elements of the antenna array 3, expecting the linear propagation of the phase curve. For this purpose, a forward prediction and a backward prediction with regard to the signal waveform can be performed. This can be seen, for example, in Fig. 10. Furthermore, Fig. 10 shows, for example, the real aperture of the antenna array 3. The real antenna aperture is understood to mean, in particular, a surface on which the antenna elements 4, 5 of the antenna array 3 are distributed.

[0093] With the help of linear prediction, the resolution of the antenna array 3, in particular of the sensor system 1, can be refined or improved. With the help of linear prediction or a linear prediction algorithm, a directional spectrum can be calculated more precisely based on real data. For example, Fig. 11 compares an evaluation of a predicted angular spectrum of a 32-element patch antenna with a method of discrete Fourier transformation 22 and linear prediction 23. Here, it can be seen that a finer evaluation or resolution can be achieved with linear prediction.

[0094] In an optional step S35, a signal curve model, in particular including a phase curve, can be formed.

[0095] In a further optional step S36, for example, intermediate positions between antenna elements 4, 5 can be calculated based on this signal curve model, or failed or defective antenna elements 24 can be identified. For this purpose, for example, when designing the antenna array 3 in a thinned-array configuration, additional virtual antenna elements can be created or generated between real antenna elements 4, 5. Thus, the distance between two real antenna elements 4, 5 can be shortened by incorporating a virtual antenna element 14 between them. This is particularly advantageous for the resolution. In particular, the resolution can be improved by enlarging the antenna aperture. This can be achieved by providing multiple antenna elements 4, 5.However, in order to be able to dispense with real antenna elements 4, 5 for reasons of cost and space, virtual antenna elements 14 can be added instead of software-based ones.

[0096] For example, if two objects are to be resolved in angle, i.e. in azimuth and elevation, an aperture extended in two directions is required.

[0097] The distances between the individual antenna elements 4, 5 determine the unambiguously measurable angular range. Larger antenna distances lead to ambiguities (side lobes) in the angle measurement. This can be remedied by using such virtual antenna elements 14. This allows, above all, the contrast between the main and side lobes in the sparse array configuration of an antenna array 3 to be improved.

[0098] In a further step S37, the actual signal waveform can be reconstructed using optimization approaches between the measured phase waveform and the signal waveform model. In other words, an actual signal waveform can be reconstructed based on the predicted extended signal waveform. For example, the signal waveform can be mathematically described using the following formula.

[0099] For this purpose, a model can be used to predict additional signal values, thereby artificially expanding the real aperture of the antenna array. This can be described by the following formula.

[0100] The spatial aperture signal can be described by the following formula: p(m) = v(m) + r(m). Here, v(m) can be defined as explainable and p(m) as unexplainable.

[0101] With the following formulas The existence of a linear relationship between signal values ​​and model coefficients can be described. This can be achieved by minimizing the prediction performance, as exemplified in the following formula. fii 2 )

[0102] E j lp(m + 1) — p(m + 1) f

[0103] In a step S38, for example, an ideal model or an ideal signal model can then be generated or created. This can then be used in a subsequent exemplary step S39 to calculate or determine the actual antenna positions of the antenna elements 4, 5.

[0104] Using these real antenna positions, it is possible to determine which antenna elements 4, 5 are defective or faulty. This can be remedied by virtually positioning a virtual antenna at the actual position of the failed antenna elements 4, 5. Thus, the accuracy and functionality of the antenna array 3, in particular of the sensor system 1, can be maintained even in the event of a failure or error.

[0105] In a subsequent exemplary step S40, a calibration of the antenna array 3 or the sensor system 1 can again be carried out based on the real antenna position and, for example, based on the model.

[0106] In an optional step S41, for example, based on the implementation of the previous steps, a virtual extension of the antenna elements 4, 5 between individual antennas can be performed. This can increase the contrast between the main and side lobes. Furthermore, a virtual extension beyond the physical array boundaries of the antenna array 3 can be achieved. This enables a refinement of the resolution. Furthermore, an increase in the response range can be achieved. This is achieved 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.

[0107] List of reference symbols

[0108] 1 sensor system

[0109] Vicinity

[0110] antenna array

[0111] Transmission elements

[0112] 5 receiving elements

[0113] Electronic evaluation unit

[0114] 7 vehicle

[0115] 8 Photonic Components

[0116] 9 Electronic components

[0117] 10 Optical Components

[0118] 11 Transmission signal

[0119] 12 Target object

[0120] 13 Reception signal

[0121] 14 Virtual antenna elements

[0122] 15 signal curves

[0123] 16 signal curves

[0124] 17 signal curves

[0125] 18 Distance range

[0126] 19 Distance range

[0127] 20 distance range

[0128] 21 Model function

[0129] 22 Discrete Fourier Transform

[0130] 23 Linear Prediction

[0131] 24 Missing antenna elements

[0132] S10 - S21 steps

[0133] S30 - S41 Further steps

Claims

Patent claims 1. A method for determining target information of at least one target object (12) in an environment (2) of a sensor system (1) which has at least one antenna array (3), wherein the at least one antenna array (3) has a plurality of transmitting elements (4) and a plurality of receiving elements (5), wherein - each transmitting element of the plurality of transmitting elements (4) transmits a transmission signal (11) into the environment (2) of the sensor system (1) in successive transmission processes, - a reception signal (13) corresponding to the respective transmission signal (11) is received by the plurality of reception elements (5) after a respective transmission element (4) has transmitted a respective transmission signal (11), - a plurality of virtual antenna elements (14) are generated on the basis of the plurality of receiving elements (5) and a respective received reception signal (13), wherein at least one virtual antenna element of the plurality of virtual antenna elements (14) can be arranged virtually between two adjacent receiving elements (5), - a respective received signal (13) is assigned to a distance range (18, 19, 20), - for a respective distance range (18, 19, 20) on the basis of the received signals assigned to this distance range (18, 19, 20), a signal profile (15, 16, 17) is determined in relation to the plurality of receiving elements (5) and the plurality of virtual antenna elements (14), - an extended signal curve is predicted on the basis of a linear prediction of the determined signal curve (15, 16, 17) of a respective distance range (18, 19, 20), - on the basis of a respective predicted extended signal curve of a respective distance range (18, 19, 20), an actual target signal relating to the at least one target object (12) is reconstructed, and - the target information of the at least one target object (12) is determined on the basis of the reconstructed actual target signal.

2. The method according to claim 1, wherein the respective actual target signal is reconstructed based on a synthetic aperture radar algorithm, a backprojection algorithm, a range cell migration algorithm or a robust multi-field analysis algorithm.

3. The method according to claim 1 or 2, wherein a synthetic antenna array is generated on the basis of a respective predicted extended signal curve of a respective distance range (18, 19, 20), the plurality of transmitting elements (4), the plurality of receiving elements (5) and the plurality of virtual antenna elements (14), wherein the synthetic antenna array is taken into account when reconstructing the actual target signal.

4. Method according to one of the preceding claims, wherein a hypothetical received signal is determined on the basis of a respective predicted extended signal curve of a respective distance range (18, 19, 20) for at least one virtual antenna element of the plurality of virtual antenna elements (14), wherein the at least one hypothetical received signal is taken into account when reconstructing the actual target signal.

5. Method according to one of the preceding claims, wherein a distance spectrum is determined on the basis of a respective received reception signal (13), the plurality of reception elements (4) and / or the plurality of virtual antenna elements (14).

6. The method according to claim 5, wherein a distance Doppler spectrum is determined on the basis of the distance spectrum, a respective received signal (13), the plurality of receiving elements (5) and / or the plurality of virtual antenna elements (14) 7. The method according to claim 6, wherein potential target objects in the environment (2) and a Doppler velocity of a respective potential target object are determined on the basis of the range Doppler spectrum.

8. The method according to claim 7, wherein a phase filter is determined on the basis of the Doppler velocities of the potential target objects, wherein a respective received signal (13) is adapted depending on the phase filter.

9. Sensor system (1) with at least one antenna array (3) which has a plurality of transmitting elements (4) and a plurality of receiving elements (5), and at least one electronic evaluation unit (6), wherein the sensor system (1) is designed to carry out a method according to one of the preceding claims.

10. Vehicle (7) with a sensor system (1) according to claim 9.

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