Method for controlling coherently coordinated radar sensor network

Abstract

The invention relates to a method for controlling a coherently coordinated radar sensor network having a plurality of radar sensors (11, 12, 13), at least two sensors (12, 13) operating coherently. The sensor data (SD1, SD2, SD3) are divided into data (KD) to be coherently analyzed and utilized and data (NKD) to be non-coherently analyzed and utilized according to the analysis and utilization type. The data (KD) to be analysed and utilized coherently and the data (NKD) to be analysed and utilized incoherently are transmitted to different analysing and utilizing units (110, 120, 130; 31, 32, 33), and then the respective different analysis and utilization units perform analysis and utilization in each case. The individual analytic utilities are combined into an overall analytic utilities.

Description

Technical Field

[0001] The invention relates to a method for controlling a coherently coordinated radar sensor network and also to a coherently coordinated radar sensor network for performing the method. Background Art

[0002] DE 10 2015 224 787 A1 describes a coherent radar sensor network consisting of at least two radar sensors. The radar sensors are synchronized with each other either by exchanging data or by signals. Each radar sensor transmits information about the radar signal to a processing device. The processing device can be constructed externally or can also be integrated in one of the radar sensors. The processing device processes the received information and preferably determines both the dual-station and the single-station distance to the object.

[0003] DE 10 2019 220 238 A1 discloses a coherent radar sensor network consisting of at least two radar sensors and a method for calibrating the same. In this case, a phase control signal is transmitted between the radar sensors, and a radar signal is sent based on the phase control signal. An analysis and utilization unit analyzes and utilizes the received signal of the radar sensor.

[0004] Usually, the radar signal is analyzed and utilized centrally in an analysis and utilization unit. This applies not only to coherent data but also to incoherent data. The analysis and utilization unit can also be part of the radar sensor, to which the data of the remaining radar sensor is then sent.

[0005] Furthermore, it is known for incoherent radar sensor networks to evaluate the incoherent data in a decentralized manner among the radar sensors. Summary of the invention

[0006] A method for controlling a coherently coordinated radar sensor network is proposed. The coherently coordinated radar sensor network has a plurality of radar sensors that are connected to one another and interact with one another. At least two sensors and preferably all sensors operate coherently. However, incoherently coordinated sensors may also be provided.

[0007] It is provided that the sensor data to be analyzed and utilized are divided so as to be analyzed and utilized in different analysis and utilization units. The analysis and utilization unit can be a physical computing device or a processor or can be implemented as a virtual core or a software block. According to the analysis and utilization type, the sensor data is divided into data to be analyzed and utilized coherently (hereinafter also referred to as coherent data) and data to be analyzed and utilized incoherently (hereinafter also referred to as incoherent data). For this reason, it is preferred to calculate the (two-dimensional) spectrum. Then, the division is based on the spectrum. Here, some regions are obtained, which are advantageously analyzed and utilized coherently or incoherently. Then, complex spectrum samples are allocated according to the regions. In the case of frequency modulated continuous wave radar (FMCW), the division can also be carried out by means of filtering based on time signals. Coherent data is obtained by high-pass filtering and incoherent data is obtained by low-pass filtering. The data to be analyzed and utilized coherently and the data to be analyzed and utilized incoherently are transmitted to different analysis and utilization units respectively. Then, the data exists on the analysis and utilization unit, and then, the analysis and utilization unit respectively performs the analysis and utilization of its data. Thus, incoherent data are analyzed by at least one analysis unit and separately, coherent data are analyzed by at least one other analysis unit. The individual analyses are then combined into an overall analysis that is performed in one analysis unit.

[0008] The division distributes the computational effort to a plurality of evaluation and utilization units, and individual evaluations and utilizations can be performed in parallel, so that the respective evaluation and utilization units need to exert less computing power or the overall effective power is increased.

[0009] When analyzing and utilizing incoherent data, for example, vector velocity detection and / or creation of a common target list (English: Location Aggregation). When analyzing and utilizing coherent data, phase and / or frequency synchronization can be performed via the antenna array and / or angle estimation can be performed. For this purpose, reference is made to DE 10 2019 220 238 A1.

[0010] Preferably, the assignment of the analysis and utilization units to the data is performed according to the expected computational cost or the expected required computational power for the data of the corresponding analysis and utilization type, so as to balance the computational cost required for the analysis and utilization of the corresponding data items by the analysis and utilization units. For example, the analysis and utilization of coherent data requires more computational power than the analysis and utilization of incoherent data. Therefore, in particular, the number of analysis and utilization units and / or the computational power of the analysis and utilization units are preferably selected according to the analysis and utilization type.

[0011] Preferably, it is provided that the divided data have the same data volume in order to achieve a constant data rate. This is particularly important in the case of a plurality of coordinated sensors (for example in the case of four or more sensors). Here, the coherent part and / or the incoherent part can be subdivided again. Preferably, the threshold value is dynamically adapted to the data.

[0012] In the overall evaluation, the individual evaluation data for each target are combined in one evaluation unit. Ultimately, therefore, all antenna combinations of the transmitting and receiving antennas of all sensors are jointly evaluated, which is necessary, for example, for coordinated angle calculations.

[0013] A further division of the sensor data to be analyzed can be provided. The sensor data can be divided according to one or more of the following criteria for the radar signal used:

[0014] Distance zone - here, a distance threshold can be specified for partitioning;

[0015] Doppler / velocity region - velocity can be derived from Doppler shift, so either the Doppler shift can be used directly as a criterion, or a velocity threshold can be specified; and

[0016] · Angular area.

[0017] These criteria represent meaningful cutting planes for the sensor data. Combinations of these criteria can also be used for the segmentation. In particular, the segmentation into coherent and incoherent data and the segmentation into distance regions can be advantageously combined, since a coherent angular analysis is only meaningful from a certain distance onwards, at which the assumption for the far field applies.

[0018] The mentioned threshold values ​​can be optimized depending on the data rate, computing power, computing operations, etc. Preferably, a common separation plane is determined before the information exchange. For this purpose, for example, a handshake protocol can be carried out between the sensors. As an example, a minimum threshold value can always be used for the division. Preferably, it is provided that these cuts have the same data volume in order to achieve a constant data rate. It is particularly important that, due to the division, certain areas contain more objects than other areas. Preferably, the threshold value is dynamically adapted to the data.

[0019] The data of different standards are then transmitted to different analysis and utilization units. The analysis and utilization units then respectively perform analysis and utilization of their data. The individual analysis and utilization are then combined into an overall analysis and utilization, which is performed in one analysis and utilization unit. By partitioning, the computational effort is distributed to a plurality of analysis and utilization units, and individual analysis and utilization can be performed in parallel, so that the corresponding analysis and utilization units need to exert less computing power.

[0020] In order to divide the sensor data, they can be transmitted to a data distribution unit. The data distribution unit divides the sensor data as described above and then distributes them accordingly to the evaluation units. The data distribution unit can be part of one or more of the sensors or can be constructed as an independent unit.

[0021] Nowadays, radar sensors usually already have an analysis and utilization unit. In particular, data can be distributed to the analysis and utilization unit in the radar sensor. For this purpose, the above-mentioned data distribution unit can preferably be used. Then, a two-way connection with the sensor is required. Then, the analysis and utilization unit in the radar sensor performs the analysis and utilization of its data. This results in the advantage that no central computing device is required, because the analysis and utilization can be performed directly in the radar sensor.

[0022] In addition, the total data rate between the evaluation units is reduced compared to central evaluation. A portion of the data remains in the sensor or in its evaluation unit until it is completely evaluated. In the case of an identical data load between N evaluation units, the following relationship applies to the data rates in both cases:

[0023]

[0024] As an example for three sensors, the total data rate is reduced by a factor of 1 / 3 compared to central analysis utilization.

[0025] Since the data in the evaluation unit of the radar sensor are not discarded or overwritten until after the complete exchange, a data buffer is preferably provided. 传感器数据 In the uniform case, the buffer size D 缓冲区 It can be estimated by the following relationship:

[0026]

[0027] As an example for three analysis and utilization units, the size of the buffer is thus reduced to at least 1 / 3 compared to the central analysis and utilization unit. In addition to the division of the data, buffering can also take place in the above-mentioned data distribution unit.

[0028] Alternatively or additionally, a central computing device with multiple analysis and utilization units can be provided. Data is transmitted to the central computing device and is divided therein to different analysis and utilization units. The division can be carried out by the above-mentioned data allocation unit, which can be implemented as a separate unit in one or more sensors in the sensor or as a part of the central computing device. Then, multiple analysis and utilization units inside the central computing device perform analysis and utilization of their data. Here, the data of each sensor can be analyzed and utilized separately from each other until angle estimation. In particular, multiple analysis and utilization units are implemented as different processors of computing equipment or are implemented as virtual cores or are implemented as software blocks. Preferably, the analysis and utilization unit of the central computing device accesses the central memory, so that data can be used for each analysis and utilization unit. Alternatively, a memory can be set for each analysis and utilization unit or for a group of analysis and utilization units.

[0029] If there is not only an evaluation unit in the sensor but also a central processing unit with a plurality of evaluation units, it is preferably provided that the sensor data to be evaluated incoherently are transmitted to the evaluation units of the incoherent radar sensors, since these require less computing power. The sensor data to be evaluated incoherently can then be transmitted to the central processing unit, whose more powerful evaluation unit takes over the evaluation at a higher computing cost.

[0030] According to one aspect, the sensor data can be transmitted as raw data from the sensor. Thus, a simple sensor head can be used, which provides raw data (e.g., analog-to-digital converter data). Optionally, these raw data can be greatly reduced before transmission. Alternatively, Fourier-transformed data, such as, for example, range FFT data, Doppler FFT data, and / or range Doppler FFT data, can be transmitted. Thus, a simple and cost-effective radar sensor can be used, which does not need to have a preprocessing unit in the presence of raw data, and which needs to have a simple preprocessing unit that performs Fourier transform in the presence of Fourier-transformed data. If a central computing device is present for analysis and utilization, the radar sensor does not need to have an analysis and utilization unit. In addition, all information for all targets is transmitted by raw data or Fourier-transformed data. Although this results in a high data rate during transmission, it does not result in loss of information. If only raw data is transmitted, some measures can be performed during analysis and utilization, typically, the measures are performed during preprocessing, such as, for example, distance and / or Doppler analysis and utilization by means of fast Fourier transform.

[0031] When performing overall analysis and utilization, non-coherent integration (NCI) can be performed based on multiple sensors. NCI calculation can be performed not only for coherent data but also for incoherent data. Preferably, for targets with far-field conditions, common NCI calculation is performed, because in the presence of these targets, it can be assumed that they can be detected by multiple sensors in the same range speed unit. For nearby areas (incoherent areas), NCI calculation is preferably performed individually based on the data of a single sensor or the data of the measurement of a dual station. In the case of single analysis and utilization, there is such a danger: the target cannot be identified by a single sensor. Before the data is finally discarded, the missing target of the measurement of a single sensor or a dual station can be detected by the central NCI calculation later. Thus, for downstream target detection (for example, by means of a constant false alarm rate, CFAR), a higher integral gain is achieved compared with a single analysis and utilization. As a result, the sensitivity and effective distance of the collaborative sensor network are improved. Finally, for the corresponding data type, typical other signal processing steps are performed based on multiple or single sensors, such as, for example, angle analysis and utilization and / or speed analysis and utilization and incoherent processing steps (for example, obtaining vector velocity and / or creating a common target list). The signal processing steps are named the same for coherent and incoherent analysis, but are implemented differently. Preferably, for coherent data, an angle analysis can be performed based on all sensors, and for incoherent data, an angle analysis can be performed based on a single sensor data. Preferably, for coherent data, a velocity analysis can be performed in a conventional manner, and for incoherent data, a velocity analysis can be additionally supplemented by a vector velocity analysis. This means additional analysis results. The common results can be output, for example, in the form of a target list.

[0032] According to a further aspect, the sensor data can be preprocessed in the sensor before they are transmitted. To this end, a preprocessing unit can be provided in the sensor, or the above-described analysis and utilization unit can be used in the sensor. The preprocessed sensor data are then transmitted and divided and analyzed and utilized as described above.

[0033] According to a further aspect, the sensor data can be transmitted to an analysis and utilization unit. The analysis and utilization unit can be integrated in the sensor or can be constructed in a central computing device. Preprocessing is then performed in the analysis and utilization unit. Preferably, the sensor data is preprocessed in the analysis and utilization unit, and the analysis and utilization is also performed in the analysis and utilization unit. Alternatively, the preprocessed sensor data can be transmitted and divided as described above.

[0034] In one form of preprocessing, a distance and / or Doppler analysis is performed in each sensor or in each analysis unit, for example by means of a fast Fourier transform (FFT) or by means of a discrete Fourier transform (DFT). In addition, an adapted analysis with a constant false alarm rate (CFAR) is performed in each sensor with these data and thus the detection of the target, that is, target detection, is performed. In the adapted CFAR, a higher false alarm rate is used compared to conventional methods. Due to the higher false alarm rate, relatively more targets are detected. The higher false alarm rate should be selected so that all targets are detected as much as possible, so that no information about the targets in the scene detected by the sensor is discarded. The preprocessed sensor data is then transmitted. As a result, the data rate when transmitting the preprocessed data is reduced by a multiple, for example, by the order of a factor of 10, compared to the transmission of the original data.

[0035] In the overall analysis, advantageously, an analysis with a lower constant false alarm rate is performed based on all sensors. Here, the term "lower" refers to a comparison with the CFAR described previously. Preferably, a common parameterization is used for the CFAR. Thus, a common target in a common form is detected. Additionally, as described above, non-coherent integration (NCI) can be performed based on multiple sensors in a spectral region in which data is transmitted by more than one sensor. Compared to a single analysis, a significantly higher integration gain is achieved. Finally, as described above, for the corresponding data type, typical additional signal processing steps are performed based on multiple or single sensors, such as, for example, angle analysis and / or velocity determination, and incoherent processing steps (for example, determining vector velocity and / or creating a common target list).

[0036] During preprocessing, each sensor or each evaluation unit independently decides which data to discard. Therefore, it may happen that part of the sensors may not transmit sensor data. However, it is disadvantageous for the overall evaluation of a coherent and coordinated radar network to use defective data for angle determination. Preferably, such a quality criterion is introduced: it is determined by the quality criterion whether to analyze and utilize targets detected only by part of the radar sensors. Such a quality criterion can be, for example, a majority decision of the sensors. If the quality criterion is met, the partially detected target is analyzed and utilized. In this case, it can be provided that the angle analysis is performed only with a subset of the radar sensors. In order to analyze and utilize incoherent data, aggregation of targets can be performed.

[0037] In a preprocessing of sensor data in another way, distance and Doppler analysis is performed in each sensor or in each analysis unit. Then, a complete analysis with a constant false alarm rate is performed in each sensor or in each analysis unit. Preferably, a common parameterization is used for the CFAR. A common target in a common form is thus detected. Here, some targets can be discarded compared to the raw data and the analysis with a lower CFAR. In addition, peak search can be performed and adjacent areas of the peak can be additionally transmitted, preprocessed and / or analyzed if necessary. In addition, in each sensor or in each analysis unit, angle estimation is performed based on sensor data of a single sensor and / or a dual station measurement path. A roughly estimated angle is thus obtained. The result of this preprocessing is stored in a target list, which additionally contains phase information. These additional information are related to the relative phase position of the single transmitter-receiver antenna channel for each target and exist as the complex amplitude of all virtual channels. The target list with phase information is transmitted as preprocessed sensor data.

[0038] During the overall analysis and utilization, the target lists of individual sensors or individual analysis and utilization units can be merged. In addition, CFAR and / or peak extraction can be performed again to reduce the amount of data. If multiple pre-processed sensor data provide the same target (for example, the same distance and Doppler data and, if necessary, the same angle or angle range), collaborative angle estimation can be performed based on the target list. As a result, the computational cost is significantly reduced during the overall analysis and utilization and in the best case when coherent data is analyzed and utilized. As a result, the data rate during the transmission of pre-processed data is reduced by several times, for example, on the order of magnitude of a factor of 1000, compared to the transmission of raw data. When a single sensor is analyzed and utilized and then analyzed and utilized collaboratively, the collaborative integral gain before CFAR is relatively small. Finally, as described above, for the corresponding data type, typical additional signal processing steps are performed based on a single or multiple sensors.

[0039] The roughly estimated angle obtained in the preprocessing described above can be determined more thoroughly by means of refinement during the overall analysis and utilization, because the relative phase position of the transmit-receive antenna channel exists in all target lists. For this reason, coherent collaborative angle estimation is performed with higher angular resolution in a predeterminable area around at least one estimated angle. For example, this can be done by means of a fast Fourier transform or a Bartlett estimator or a maximum likelihood method. Because the angle area (in which a higher angular resolution is applied) is severely limited, for example, within the separation capability of a single sensor in elevation and azimuth, the computational cost for this analysis and utilization is comparable to the traditional angle estimation of a single sensor over the entire angle area. Through this analysis and utilization, in particular, multiple targets can also be found in the angle area and separated. Under normal circumstances, the result of this angle estimation can replace the rough angle estimation of the sensor or analysis and utilization unit. If it is lower than the quality factor of the collaborative analysis and utilization, the angle estimation of a single sensor or analysis and utilization unit can be used. The quality factor can be obtained, for example, as a result of the association between the control matrix and the complex amplitude. For this reason, meta-information about the processing method can be added to the target list.

[0040] The computer program is provided for carrying out each step of the method, in particular when the computer program is executed on a computing device. It enables the method to be carried out in a conventional computing device without having to make structural changes thereto. For this purpose, it is stored on a machine-readable storage medium.

[0041] In addition, a coherent radar sensor network with a plurality of radar sensors is proposed. At least two sensors work in a coordinated manner. In addition, the radar sensor network has a data distribution unit, with which the sensor data can be distributed. The data distribution unit can be part of one or more of the sensors. The radar network is configured to perform the steps of the method described above.

[0042] Furthermore, the coherently coordinated radar sensor network may have a central computing device. The central computing device is configured to carry out the steps of the method described above. For this purpose, the central computing device may have a data distribution unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Exemplary embodiments of the invention are shown in the drawings and are explained in more detail in the following description.

[0044] Figure 1 A schematic diagram showing the data and its partitioning.

[0045] Figure 2An image showing the systemic nature of a coherently coordinated radar sensor network according to one embodiment of the present invention.

[0046] Figure 3 A systematic diagram of a coherently coordinated radar sensor network according to a further specific embodiment of the present invention is shown.

[0047] Figure 4 Angle diagram showing azimuth and elevation used for angular estimation of a target. DETAILED DESCRIPTION

[0048] Figure 1 The basic idea of ​​the method according to the invention is shown in a schematic illustration of data. Figure 2 and Figure 3 A coherently coordinated radar sensor network with multiple radar sensors (three of which are shown) 11, 12, 13 is shown respectively. In this example, the first radar sensor 1 is constructed as an incoherent sensor, and the second radar sensor 12 and the third radar sensor 13 are coherently constructed. In other embodiments, all radar sensors 11, 12, 13 can be coherently constructed. The sensor data SD1, SD2, SD3 detected by the radar sensors 11, 12, 13 are divided by the data distribution unit 2 according to the type of analysis and utilization of these sensor data (that is, whether they are analyzed and utilized coherently or incoherently). First, a (two-dimensional) spectrum can be calculated, and the division is based on the spectrum. Here, some areas are obtained, which are advantageously analyzed and utilized coherently or incoherently. In the case of a frequency modulated continuous wave radar (FMCW), the division can be performed by means of filtering. Coherent data KD is obtained by means of high-pass filtering, and incoherent data NKD is obtained by means of low-pass filtering. The coherent data KD and the incoherent data NKD are assigned to different evaluation units 110, 120, 130; 31, 32, 33 and are evaluated there. Figure 2 and Figure 3 For example, vector velocities are determined from the incoherent data NKD and / or a common target list is created. For the coherent data KD, for example, phase and / or frequency synchronization is performed via the antenna array and an angle estimation is also performed.

[0049] Additionally, the data may be divided according to the range, Doppler / velocity and / or angle range of the radar signal used and distributed to evaluation units 110 , 120 , 130 , 31 , 32 , 33 which then perform an evaluation of their data.

[0050] exist Figure 2In the embodiment, radar sensors 11, 12, 13 respectively have an analysis unit 110, 120, 130, which performs preprocessing of sensor data SD1, SD2, SD3. Alternatively, raw data and / or Fourier transformed data, such as, for example, range FFT data, Doppler FFT data and / or range Doppler FFT data, can also be transmitted, and corresponding steps can be performed later during the analysis. The preprocessed sensor data SD1, SD2, SD3 contain a target list ZL1, ZL2, ZL3 with corresponding targets Z1, Z2, Z3 (see Figure 4 ). The preprocessed sensor data SD1, SD2, SD3 (or raw data and / or Fourier transformed data) are transmitted to the data distribution unit 2. Here, the data distribution unit is constructed as a separate unit, but it can also be part of the radar sensor 11, 12, 13. The data distribution unit 2 is as described above. Figure 1 The data are divided as described in the related description and transmitted to the analysis and utilization units 120, 130, 140 of the radar sensors 11, 12, 13. There is a bidirectional connection between the radar sensors 11, 12, 13 and the data distribution unit 2. In this case, the incoherent data NKD are sent to the analysis and utilization unit 110 of the first radar sensor 11. This applies in particular to the case where the data distribution unit 2 is part of the radar sensors 11, 12, 13. The coherent data KD are separated according to the sub-spectra of the target or the selected area and are divided accordingly and transmitted to the analysis and utilization unit 120 of the second radar sensor 12 and to the analysis and utilization unit 130 of the third radar sensor 13, which operate coherently. Then, in the analysis and utilization units 110, 120, 130, as described above, Figure 1 The data of these sensors are analyzed and utilized in a related manner. The analyzed data are then transmitted again to the central computing device 3 via the data distribution unit 2. The central computing device 3 has an analysis unit 30 which generates a common analysis result. Alternatively, this can also be performed in one of the analysis units 110, 120, 130 of the radar sensors 11, 12, 13.

[0051] exist Figure 3In the embodiment, radar sensors 11, 12, 13 respectively have preprocessing units 111, 121, 131, which perform preprocessing of sensor data SD1, SD2, SD3. Alternatively, raw data and / or Fourier transformed data, such as, for example, range FFT data, Doppler FFT data and / or range Doppler FFT data, can also be transmitted, and corresponding steps can be performed later when performing analysis and utilization. The preprocessed sensor data SD1, SD2, SD3 contain target lists ZL1, ZL2, ZL3 with corresponding targets Z1, Z2, Z3 (see Figure 4 ). The preprocessed sensor data SD1, SD2, SD3 (or raw data and / or Fourier transformed data) are transmitted to the data distribution unit 2. In addition, a central computing device 3 with a plurality of analysis and utilization units 30, 31, 32, 33 is provided. The analysis and utilization units 30, 31, 32, 33 can be, for example, processors, virtual cores or software blocks. Here, the data distribution unit 2 is constructed as a separate unit, but it can also be part of the central computing device 3. The data distribution unit 2 is as described above. Figure 1 The data are divided as described in the related description and transmitted to the analysis and utilization units 31, 32, 33 of the central computing device 3. The connection between the radar sensors 11, 12, 13 and the data distribution unit 2 and between the data distribution unit 2 and the central computing device 3 can be constructed as a simple connection. Purely by way of example, the incoherent data NKD is sent to the analysis and utilization unit 31. The coherent data KD is separated according to the sub-spectrum of the target or the selected area and is divided and transmitted to the analysis and utilization units 32 and 33 accordingly. Then, in the analysis and utilization units 31, 32, 33, as described above Figure 1 The data are analyzed in a linked manner. The analyzed data are then transmitted to the analysis unit 30, which performs an overall analysis of the combined analysis.

[0052] exist Figure 4 3 shows three target lists ZL1, ZL2, ZL3 for three radar sensors 11, 12, 13. In this example, they each have three targets Z1, Z2, Z3. In the three target lists ZL1, ZL2, ZL3 of the three radar sensors 11, 12, 13, at least the first target Z1 should be identical. Given the azimuth In preprocessing, the azimuth angle for the first target Z1 is estimated by the first radar sensor 11 using a rough angle estimation with low resolution. and elevation angle θ1. In the overall analysis, coherent collaborative angle estimation is performed for all radar sensors 11, 12, 13. Because the rough angle and θ1 are already known, so an angular estimation with higher angular resolution is performed in a prescriptive region around them. The higher angular resolution is obtained by Figure 4 A tighter grid is shown in Figure 2. The limits of this region are chosen to be and And for an elevation angle θ, the limits of the region are chosen to be θ1-Δθ and θ1+Δθ.

Claims

1. A method for controlling a coherently coordinated radar sensor network having a plurality of radar sensors (11, 12, 13), wherein: At least two sensors (12, 13) operate coherently, characterized in that the sensor data (SD1, SD2, SD3) are divided into data to be coherently analyzed (KD) and data to be incoherently analyzed (NKD) according to the type of analysis, and the data to be coherently analyzed (KD) and the data to be incoherently analyzed (NKD) are transmitted to different analysis units (110, 120, 130; 31, 32, 33), which then perform the analysis respectively, wherein the individual analyses are combined into an overall analysis.

2. The method according to claim 1, characterized in that The sensor data (SD1, SD2, SD3) are divided according to the range region, Doppler / velocity region and / or angle region of the radar signal used, and the data of different regions are transmitted to different analysis and utilization units (110, 120, 130; 31, 32, 33), and then the different analysis and utilization units perform analysis and utilization respectively, wherein the individual analysis and utilization are combined into an overall analysis and utilization.

3. The method according to any one of the preceding claims, characterized in that The sensor data (SD1, SD2, SD3) are transmitted to a data distribution unit (2), the sensor data (SD1, SD2, SD3) are divided by the data distribution unit, and the data to be coherently analyzed and utilized (KD) and the data to be incoherently analyzed and utilized (NKD) are distributed by the data distribution unit (2) to the analysis and utilization units (110, 120, 130; 31, 32, 33).

4. The method according to any one of the preceding claims, characterized in that The data (KD, NKD) are distributed to an evaluation unit (110, 120, 130) in the sensor (11, 12, 13), and the evaluation unit of the sensor (11, 12, 13) performs the evaluation.

5. The method according to any one of the preceding claims, characterized in that The data (KD, NKD) are transmitted to a central computing device (3), and an evaluation unit (31, 32, 33) of the central computing device (2) carries out the evaluation.

6. The method according to any one of claims 1 to 5, characterized in that The sensor data (SD1, SD2, SD3) are transmitted by the sensors (11, 12, 13) as raw data or as Fourier transformed data.

7. The method according to any one of claims 1 to 5, characterized in that The sensor data (SD1, SD2, SD3) are preprocessed in the sensors (11, 12, 13) and are transmitted as preprocessed sensor data.

8. The method according to any one of claims 1 to 6, characterized in that The sensor data (SD1, SD2, SD3) are preprocessed in the evaluation and utilization unit (110, 120, 130).

9. The method according to claim 7 or 8, characterized in that: In the preprocessing of the sensor data (SD1, SD2, SD3), a distance and Doppler evaluation is carried out, and thus the detection of objects (Z1, Z2, Z3) is carried out by means of an adapted evaluation with a constant false alarm rate.

10. The method according to claim 9, characterized in that In the overall evaluation, a further evaluation is performed with a lower constant false alarm rate in order to detect the common target ( Z1 ).

11. The method according to claim 9 or 10, characterized in that: Objects detected by only a portion of the radar sensors (11, 12, 13) are evaluated only if a quality criterion is met.

12. The method according to claim 7 or 8, characterized in that: During preprocessing of the sensor data (SD1, SD2, SD3), a distance and Doppler evaluation is performed and thus a detection of targets and an angle estimation are performed by a complete evaluation with a constant false alarm rate, wherein the transmitted sensor data contain a target list (ZL1, ZL2) with phase information.

13. The method according to claim 12, characterized in that At least one angle estimated during the preprocessing with respect to the target (Z1) For evaluation, a coherent coordinated angle estimation is performed with a higher angle resolution within a predeterminable region around the estimated at least one angle. 14 . A computer program configured to execute each step of the method according to claim 1 .

15. A machine-readable storage medium on which a computer program according to claim 14 is stored.

16. A coherent radar sensor network comprising a plurality of radar sensors (11, 12, 13) and a data distribution unit (2), wherein: At least two sensors (12, 13) operate in a coherent manner, wherein the radar network is provided to carry out the method according to any one of claims 1 to 13.

17. The coherent coordinated radar sensor network according to claim 16, characterized in that A central processing unit (3) is provided for carrying out the method according to any one of claims 1 to 13.

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