Methods for radar sensor data processing and radar sensor data processing systems

Abstract

The invention relates to a method for processing radar sensor data (10) of radar sensor data (12) from a radar sensor system (20) that detects at least one target object (14) in an environment (16) of a carrier system (18). The invention further relates to a radar sensor data processing system.

Description

[0001] The invention relates to a method for radar sensor data processing according to the preamble of claim 1. Furthermore, the invention relates to a radar sensor data processing system. State of the art

[0002] Driver assistance systems in vehicles use radar sensors to detect the vehicle's surroundings and to detect target objects in the vehicle's surroundings. When using radar sensors to detect the surroundings, high angular resolution is desired, which in turn depends on the size of the antenna aperture. In radar sensors composed of multiple transmit / receive units, the entire sensor array forms a virtual antenna aperture that extends beyond the physical aperture. Such radar systems can, for example, be constructed as MIMO radar sensors, which have multiple transmit / receive units. To increase the overall antenna aperture, the transmit / receive units are arranged at larger and irregular distances from one another.

[0003] In such sparse arrays, the transmit / receive units are not evenly distributed. This can result in sidelobes that interfere with the accurate determination of the direction of arrival (DoA) of a received radar reflection from a target object.

[0004] In order to detect and eliminate the secondary elevations, for example, the method proposed in “A Unified Approach to Sparse Signal Processing”, F. Marvasti, A. Amini, F. Haddadi, M. Soltanolkotabi, BH Khalaj, A. Aldroubi, S. Sanei and J. Chambers, EURASIP Journal on Advances in Signal Processing, Volume 2012, No. 1, p. 44, February 2012 is used. The method involves converting the phase signals of the sensor array into an angular spectrum using a Fourier transform. Subsequently, the secondary elevations present in the angular spectrum, which are close to the actual signal values ​​but have lower amplitudes, are excluded using a signal value threshold that is directly dependent on the amplitude of the largest elevation. In order to obtain a processed phase signal from this processed angular spectrum using an inverse Fourier transform of the angular components that exceed the specified signal value threshold.This revision process is repeated iteratively, with each pass reducing the unwanted spurious peaks in the angular spectrum, allowing for finer tuning of the specified signal threshold. These iterations continue until a radar signal or angular spectrum has been calculated that is as free of spurious peaks as possible.

[0005] In addition to the IMAT algorithm, other methods for eliminating the influence of secondary elevations are known. For example, the CLEAN algorithm searches for the highest elevation in the angular spectrum, transforms this value back into the spatial phase signal, removes the corresponding components in the spatial phase signal at the existing locations, and thus generates a phase signal for a second detection that no longer contains the initially detected target.

[0006] Another iterative algorithm is RELAX for solving nonlinear optimization problems. It searches for a signal that matches both the measured data and a defined model, applying a penalty function to favor solutions with a small number of non-zero elements (sparsity). Disclosure of the invention

[0007] According to the present invention, a method for radar sensor data processing is proposed, having the features of claim 1. This allows the computational effort and time to be reduced. Signal data processing can be performed more efficiently, quickly, and simply.

[0008] The carrier system can be movable, in particular mobile. The carrier system can be a vehicle, in particular a motor vehicle, two-wheeled vehicle, or truck. The vehicle can be a mobile robot.

[0009] The target object can be a living being, a facility, an object, a vehicle, a building, a plant and / or a road feature.

[0010] The receiving unit can be a single radar sensor and / or a receiving channel of a radar sensor. The receiving unit can be a physical or virtual receiving channel.

[0011] The radar sensor system can be constructed as a spatial network of multiple radar sensors, in which the radar sensors form the receiving units. The radar sensor system can have multiple temporally distributed receiving units, formed by the individual radar sensors at different times, by moving a radar sensor. The radar sensor system can comprise a radar sensor that has multiple receiving channels and at least one, in particular multiple, transmitting channels. The receiving channels can form the receiving units. The radar sensor can be a MIMO radar sensor.

[0012] The sparse distribution of the receiving units means that at least one defect exists in the otherwise uniform, regular, consistent, harmonious, and / or ordered distribution of receiving units. The sparse distribution can also extend to the multiple transmission channels. Apart from the at least one defect, the receiving unit distribution can also be disordered, irregular, uneven, and / or non-uniform.

[0013] The phase signal can indicate the phase shift depending on the spatial and / or temporal position of the receiving unit in the receiving unit distribution of the radar sensor system.

[0014] The main elevation may have a greater or lesser amplitude than a secondary elevation. All secondary elevations are caused directly or indirectly by the defect(s). All main elevations are directly or indirectly related to the object objective(s).

[0015] In addition to the selection criterion, a further selection criterion can be provided for selecting the angular spectrum component.

[0016] The selection criterion or additional selection criteria can be a specified signal threshold. The signal threshold can be set to decrease with increasing iteration steps. Elevations in the angular spectrum whose amplitudes reach or exceed the signal threshold can be included in the angular spectrum component. Signal components in the angular spectrum whose amplitudes fall below the signal threshold can be excluded from the angular spectrum component. The selected angular spectrum component can be limited exclusively to elevations in the angular spectrum that have amplitudes above the signal threshold.

[0017] The additional selection criterion can be applied in at least one iteration step in addition to the selection criterion. The additional selection criterion can be applied in at least one iteration step without the selection criterion. However, the selection criterion is applied in at least one iteration step.

[0018] The further selection criterion can be a signal value threshold that is directly dependent on the amplitude of the largest elevation in the angular spectrum.

[0019] In a Fast Fourier Transform (FFT)-based angle estimation, for example, the well-known IMAT method, the inverse transformation is typically performed as an inverse Fast Fourier Transform (iFFT) over the entire angular spectrum. In the case of the first iteration step, the modified angular spectrum to be transformed back and limited to the selected angular spectrum component can consist of just one bin; in all subsequent iteration steps, it can consist of a few bins that actually contain spectral information, while all other bins that do not lie above a predetermined signal value threshold are set to zero. The inverse transformation can be implemented as a restricted inverse transformation that does not encompass the entire angular spectrum, for example, as an inverse Discrete Fourier Transform (iDFT), in particular as follows: x(tn)=X(ωmax,n)⋅ej⋅ωmax,n⋅tn with the time signal x(t n) of the n-th receiving unit, the Fourier transform X(ω max,n ) and the angle ω max,n the survey to be transformed.

[0020] In a preferred embodiment of the invention, it is advantageous if the selection criterion comprises an amplitude change behavior over at least one iteration step of at least one of the elevations in the angular spectrum. The selection criterion can be the amplitude change behavior. The selection criterion can include the amplitude change behavior of multiple amplitude changes.

[0021] In a specific embodiment of the invention, it is advantageous if a change in amplitude that reduces the amplitude of one of the elevations is used to identify it as a secondary elevation. This allows elevations to be excluded depending on the amplitude change.

[0022] In a preferred embodiment of the invention, it is advantageous if an amplitude change that increases the amplitude of a peak, or no amplitude change, meaning a constant amplitude, is used to identify it as a primary peak. This allows peaks to be included depending on the amplitude change. Excluding peaks as secondary peaks and including them as primary peaks can be applied separately or in combination.

[0023] In an advantageous embodiment of the invention, the selection criterion is dependent on a previously known maximum possible amplitude of any possible secondary elevations of the radar sensor system. The selection criterion can be a predetermined signal value threshold dependent on the previously known maximum possible amplitude. The previously known amplitude can be calculated using the radar sensor system through previous measurements and / or simulations.

[0024] By incorporating prior knowledge of the sensor array, for example, by knowing the maximum possible amplitude of the highest, constructively superimposed secondary elevation, especially in the case of two targets with identical amplitudes in the angular spectrum, the selection criterion can be selected such that significantly more spectral angle bins are included. For example, the signal value threshold, which depends on the previously known amplitude, can correspond to the previously known amplitude, preferably including a safety margin. This allows more information to be used for the inverse transformation already in the first iteration step. This prior knowledge can ensure that such an approach uses only information from real targets and not angular information from any constructively superimposed secondary elevations.

[0025] In a specific embodiment of the invention, it is advantageous if the selection criterion is a selection angle range that depends on an individual angle range specified by at least one individual receiving unit and delimited from the total angle range covered by the radar sensor system. The selection angle range can encompass the individual angle range or correspond to the individual angle range. The individual angle range can be the maximum angle range that can be covered by a single receiving unit. The receiving units of the radar sensor system can all have the same maximum angle range that can be covered and / or a different maximum angle range that can be covered from one another.

[0026] The individual angle range can be specified by a number of receiving units, whereby the number of receiving units is smaller than the total number of receiving units of the radar sensor system. The individual angle range can be formed as the sum of the respective individual angle ranges of the receiving units included in the number of receiving units.

[0027] In an advantageous embodiment of the invention, the selection angle range is specified as dependent on the individual angle range if the at least one target object is detected in the individual angle range. The selection criterion can be the selection angle range, in particular only when the at least one target object is detected in the individual angle range.

[0028] To resolve the number of target objects in the individual angular range, the individual signals from multiple receiving units can be processed. If the elevations of multiple receiving units coincide, an angular range surrounding the respective common elevation can be defined and isolated, in particular, at most, over the span of the individual angular range of a receiving unit. This isolation can be achieved by specifying a signal value threshold below the amplitude of the elevation. This isolated angular spectrum can be converted into a modified phase signal by inverse transformation, in particular by iFFT, and the modified phase signal can then be superimposed on the measured phase signal of the other, in particular the entire virtual, receiving units of the radar sensor system.The modified phase signal based on the at least one receiving unit can pre-initialize the respective measured phase signal of the entire set or subset of all receiving units. Preferably, the modified phase signal is normalized and / or attenuated before being superimposed with the measured phase signal, in particular in order to avoid or minimize the change in the measured phase information of the additional receiving units. The measured phase signal can have priority at the actually measuring receiving units, in particular be free of the superposition. The modified phase signal can be superimposed on the measured phase signal exclusively at the virtual positions of the receiving unit distribution.

[0029] A preferred embodiment of the invention is advantageous in which the individual angle range plus at least one unilateral tolerance angle forms the selection angle range. The unilateral tolerance angle can extend the individual angle range in one direction. The tolerance angle can be added on both sides, thus extending the individual angle range in both directions.

[0030] For example, the single angle range can be 7° and the double-sided tolerance angle 3.5°.

[0031] A preferred embodiment of the invention is advantageous in which a plurality of first receiving units are divided into a first receiving unit group and a plurality of second receiving units are divided into a second receiving unit group. A first angular spectrum is created for the first receiving unit group and a second angular spectrum is created for the second receiving unit group, and the selection criterion is dependent on a spectrum comparison of the first and second angular spectra. The first receiving unit group can have at least one first receiving unit that is not a second receiving unit. The first receiving unit group can have a first receiving unit that is a second receiving unit.

[0032] The second receiving unit group may include at least one second receiving unit that is not a first receiving unit. The second receiving unit group may include a second receiving unit that is a first receiving unit.

[0033] At least one further receiving unit group can also be formed from the receiving units, for which a further angular spectrum is created. The selection criterion can depend on a spectrum comparison of the first, second, and further angular spectrum.

[0034] In a specific embodiment of the invention, it is advantageous if the selection criterion is a matching identification, which is used to identify those elevations in the spectrum comparison that are present in the first and second angular spectra with respect to the angle of incidence. The matching identification can depend on the amplitude, the angle, the shape of the elevation, and / or the area enclosed by the elevation.

[0035] The method for radar sensor data processing may be a computer-implemented method for execution on a processing unit. The processing unit may have a processor for at least partially executing the method.

[0036] According to the present invention, a radar sensor data processing system for processing radar sensor data is further proposed, comprising a radar sensor system that provides radar sensor data detecting at least one target object in an environment of a carrier system and a processing unit that is configured to process the radar sensor data by a method for radar sensor data processing having at least one of the features described above.

[0037] Further advantages and advantageous embodiments of the invention emerge from the description of the figures and the illustrations. Character description

[0038] The invention is described in detail below with reference to the figures. They show in detail: Fig. 1: A method for radar sensor data processing in a specific embodiment of the invention. Fig. 2: An angular spectrum when applying the method for radar sensor data processing in a specific embodiment of the invention. Fig. 3: A phase signal when applying a method for radar sensor data processing in a specific embodiment of the invention. Fig. 4: An angle spectrum to the phase signal from Fig. 3. Fig. 5: An angular spectrum when applying a method for radar sensor data processing in another specific embodiment of the invention. Fig. 6: An angular spectrum when applying a method for radar sensor data processing in another specific embodiment of the invention. Fig. 7: A target object resolution when applying a method for radar sensor data processing in another specific embodiment of the invention. Fig. 8: A spectrum comparison when applying a method for radar sensor data processing in another specific embodiment of the invention.

[0039] Fig. 1 shows a method for radar sensor data processing in a specific embodiment of the invention. The method for radar sensor data processing 10 processes radar sensor data 12 from a radar sensor system 20 detecting at least one target object 14 in an environment 16 of a carrier system 18, here a vehicle. The radar sensor system 20 comprises a plurality of temporally and / or spatially distributed receiving units 22, each for receiving the radar signals reflected from the target object 14 as an individual signal 24. The distribution of the receiving units 22 in the radar sensor system 20 is sparse, with at least one missing point 26 in the receiving unit distribution 28.

[0040] First, the radar sensor system 20 is provided 30. Subsequently, a phase signal 34 is provided 32, which is formed from phase shifts of the individual signals 24 that depend on an angle of incidence φ of the radar signals reflected by the target object 14 with respect to the radar sensor system 20.

[0041] With a subsequent conversion 38, the phase signal 34 is converted into an angular spectrum 40 which has at least one main elevation at the angle of incidence φ of the individual signal 24 arriving most strongly from the target object 14 and at least one secondary elevation triggered by the defect 26.

[0042] In a first iteration step 42.1, signal data processing is carried out at least by isolating the at least one main elevation by converting the angle spectrum 40 into a modified angle spectrum 46 by selecting an angle spectrum component 44, converting the modified angle spectrum 46 into a modified phase signal 48, and converting the modified phase signal 48 again into an angle spectrum 40.

[0043] In subsequent iteration steps 42, the sequence of the first iteration step 42.1 is repeated. In at least one of the iteration steps 42, the angular spectrum component 44 is selected depending on at least one selection criterion 50 that is independent of, or at most indirectly dependent on, the amplitude of the largest elevation in the angular spectrum. This allows signal data processing to be performed more efficiently, quickly, and simply.

[0044] Fig. Figure 2 shows an angular spectrum when applying the radar sensor data processing method. The angular spectrum 40 shows the signal value S as a function of the angle of incidence φ of the radar signals. The cause of secondary elevations 54 in the angular spectrum 40 are defects in the sparse reception unit distribution in the radar sensor system. In the angular spectrum 40, these defects manifest themselves as constructive superpositions in the secondary elevations 54, whereby the two main elevations 56, each assigned to a target object, have a lower amplitude than the secondary elevations 54. This leads to a reduction in the dynamic range in the angular spectrum 40.

[0045] Fig. Figure 3 shows a phase signal when applying a method for radar sensor data processing in a specific embodiment of the invention. The phase signal P depends on the position D relative to the antenna array of the radar sensor system. A measured phase signal 60, represented as points, at the locations D(n) of the virtual antenna array, a first modified phase signal 48.1 after a first iteration step, and a further modified phase signal 48.n after at least one further iteration step are shown.

[0046] The measured phase signal 60 is filled in the first modified phase signal 48.1 and in the further modified phase signal 48.n with approximate values ​​that replace the defect influences as faithfully as possible.

[0047] Fig. 4 shows an angle spectrum to the phase signal from Fig. 3. In the angle spectrum 40, which specifies the signal value S as a function of the angle of incidence φ, a signal value threshold 66 is defined as a selection criterion in each iteration step. In a first iteration step, a first signal value threshold 66.1 is applied to the first modified angle spectrum 46.1 present at that time, and in a further iteration step, a reduced further signal value threshold 66.n is applied to the further angle spectrum 46.n present at that time, whereby the final modified angle signal 46.x is obtained after the inverse transformation via the modified phase signal.

[0048] In each iteration step, the spectral signal values ​​S above the respective signal value threshold 66 are transformed back into the changed phase signal and the previously missing values ​​are replaced there, thus filling the missing positions in the phase signal with a complex estimated value generated based on the spectral information taken into account, as in Fig. 3. The modified phase signal thus completed can be used in further iteration steps as the basis for the modified angle spectrum 46, to which a reduced signal value threshold 66 is then iteratively applied as a selection criterion.

[0049] Fig. 5 shows an angular spectrum when applying a method for radar sensor data processing in another specific embodiment of the invention. By observing the amplitude change behavior 68 of the elevations 70 in the angular spectrum 40 and thus the gradient of the amplitudes 72 of the elevations 70 over the iteration steps, the selection criterion can comprise an amplitude change behavior 68 of the amplitudes 72 of the elevations 70 changing over the iteration steps, which in this example include the main elevations 56 and the secondary elevations 54. The amplitude 72 of the secondary elevations 54 becomes smaller starting from a respective first amplitude 72.1 up to respective further amplitudes 72.n through the iteration steps and the amplitude 73 of the main elevations 56 becomes larger starting from respective first amplitudes 73.1 up to respective further amplitudes 73.n or remains constant.An amplitude change 74 that reduces the respective amplitude 72, 73 of the elevation 70 can be used to identify it as a secondary elevation 54 and an amplitude change 74 that increases the respective amplitude 72, 73 of the elevation 70 can be used to identify it as a main elevation 56.

[0050] If a signal value threshold 66 that decreases with increasing iteration steps is applied as a further selection criterion 75, the main elevations 56 can already be included in the angular spectrum portion by the selection criterion of the amplitude change behavior 68, even if the amplitude 73 of the main elevation 56 is still smaller than the signal value threshold 66 applied in the respective iteration step. Conversely, the secondary elevations 54 can already be excluded in the angular spectrum portion by the selection criterion of the amplitude change behavior 68, even if the amplitude 72 of the secondary elevation 54 is still greater than the signal value threshold 66 applied in the respective iteration step. The information about the amplitude change behavior 68 can also be used for detection or for plausibility checking and evaluation of the number of target objects in the angular spectrum 40.Alternatively, the application of the further selection criterion 75 with the signal value threshold 66 can be omitted. Alternatively, after a reliable identification of main and secondary elevations after n iterations, further iterations could either be omitted entirely, as a termination criterion, and / or the signal value thresholds could be limited only in the selected areas, for example, to the left and right of the identified main elevations, for further reducing the noise level before detection and continuing to observe the elevations during this time.

[0051] Fig. 6 shows an angle spectrum when applying a method for radar sensor data processing in another specific embodiment of the invention. The angle spectrum 40 is depicted with a selection angle range 78, which represents the selection criterion 50. The selection angle range 78 is dependent on an individual angle range 82 specified by at least one individual receiving unit and delimited from the total angle range 80 covered by the radar sensor system as a whole. The selection angle range 78 is specified as dependent on the individual angle range 82, in particular as corresponding to the individual angle range 82, if the at least one target object is detected in the individual angle range 82.

[0052] Fig. 7 shows a target object resolution when applying a method for radar sensor data processing in another specific embodiment of the invention. To resolve the number of target objects in the individual angular range, the individual signals from multiple receiving units 22 can be processed. In this case, if elevations 70 in the angular spectrum 40 of the multiple receiving units 22 coincide, an angular surrounding range 86 enclosing the respective common elevation 70 can be defined and isolated, in particular, at most over the span of the individual angular range of a receiving unit 22. This isolation can be achieved by specifying a signal value threshold 66 below the amplitude 72 of the elevation 70.This isolated angular spectrum can be converted into a modified phase signal 34 by inverse transformation, in particular by iFFT 87, and the modified phase signal 34 can then be superimposed on the measured phase signal of the further, in particular all, receiving units 22 of the radar sensor system. The modified phase signal 34 can pre-initialize the respective measured phase signal of the receiving units 22. Preferably, the modified phase signal 34 is normalized and / or attenuated before being superimposed on the measured phase signal, in particular in order to avoid changing the measured phase information of the further receiving units 22 or to change it as little as possible. The superimposition can be limited to the unoccupied spatial positions of the virtual sensor array of the radar sensor system. The measured phase information at previously occupied spatial, virtual positions of the sensor array is not changed.

[0053] Superimposing or averaging specifically means that the various individual sensors in the sensor array may provide slightly different phase signals. These can be superimposed or averaged. Since the individual sensors have far fewer virtual antenna positions than the overall aperture, the signal curve from the individual sensors must be extrapolated to the entire array.

[0054] Fig.8 shows a spectrum comparison when applying a method for radar sensor data processing in a further specific embodiment of the invention. First, a plurality of first receiving units 88 are divided into a first receiving unit group 90, and a plurality of second receiving units 92 are divided into a second receiving unit group 94. A first angular spectrum 96 is created for the first receiving unit group 90 and a second angular spectrum 98 is created for the second receiving unit group 94, and the selection criterion is dependent on a spectrum comparison 100 of the first and second angular spectra 96, 98. The selection criterion is in each case a match identification 102, with which those elevations 70 are identified in the spectrum comparison 100 that are present in the first and second angular spectra 96, 98 with a matching angle of incidence φ. QUOTES CONTAINED IN THE DESCRIPTION

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

[0000] A Unified Approach to Sparse Signal Processing", F. Marvasti, A. Amini, F. Haddadi, M. Soltanolkotabi, BH Khalaj, A. Aldroubi, S. Sanei and J. Chambers, EURASIP Journal on Advances in Signal Processing, Volume 2012, No. 1, p. 44, February 2012

[0004]

Claims

[1] Method for radar sensor data processing (10) of radar sensor data (12) of a radar sensor system (20) detecting at least one target object (14) in an environment (16) of a carrier system (18), comprising Providing (30) the radar sensor system (20) comprising a plurality of temporally and / or spatially distributed receiving units (22) each for receiving the radar signals reflected from the target object (14) as individual signals (24), in which the distribution of the receiving units (22) is sparse with at least one defect (26) in the receiving unit distribution (28), Providing (32) a phase signal (34) which is formed from phase shifts of the individual signals (24) dependent on an angle of incidence (φ) of the radar signals reflected by the target object (14) with respect to the radar sensor system (20), Conversion (38) of the phase shifts summarized in a phase signal (34) into an angular spectrum (40) having elevations (70), which has at least one main elevation (56) assigned to the target object (14) and at least one secondary elevation (54) triggered by the defect (26), iterative signal data processing over several iteration steps (42) at least by isolating the at least one main elevation (56) by converting the angular spectrum (40) into a modified angular spectrum (46) by selecting an angular spectrum component (44), converting the modified angular spectrum (46) into a modified phase signal (48), and converting the modified phase signal (48) again into an angular spectrum (40), characterized by , that at least in one iteration step (42) the angular spectrum component (44) is selected as a function of at least one selection criterion (50) which is independent of or at most indirectly dependent on the amplitude (72, 73) of the largest elevation (70) in the angular spectrum (40). [2] Method for radar sensor data processing (10) according to claim 1, characterized by that the selection criterion (50) comprises an amplitude change behavior (68) over at least one iteration step (42) of at least one of the elevations (70) in the angular spectrum (40). [3] Method for radar sensor data processing (10) according to claim 2, characterized by that a change in amplitude which reduces the amplitude (72) of one of the elevations (70) is used to identify it as a secondary elevation (54). [4] Method for radar sensor data processing (10) according to claim 2 or 3, characterized bythat an amplitude change increasing the amplitude (72) of one of the elevations (70) or no amplitude change, i.e. a constant amplitude, is used to identify it as the main elevation (56). [5] Method for radar sensor data processing (10) according to one of the preceding claims, characterized by that the selection criterion (50) is dependent on a previously known maximum possible amplitude (72, 73) of any possible secondary elevations (54) of the radar sensor system (20). [6] Method for radar sensor data processing (10) according to one of the preceding claims, characterized by that the selection criterion (50) is a selection angle range (78) which is dependent on an individual angle range (82) which is predetermined by at least one individual receiving unit (22) and delimited from the total angle range (80) covered by the radar sensor system (20). [7] Method for radar sensor data processing (10) according to claim 6, characterized by that the selection angle range (78) is specified as dependent on the individual angle range (82) when the at least one target object (14) is detected in the individual angle range (82). [8] Method for radar sensor data processing (10) according to claim 6 or 7, characterized by that the individual angle range (82) plus at least one one-sided tolerance angle forms the selection angle range (78). [9] Method for radar sensor data processing (10) according to one of the preceding claims, characterized bythat a plurality of first receiving units (88) are divided into a first receiving unit group (90) and a plurality of second receiving units (92) are divided into a second receiving unit group (94), and a first angular spectrum (96) is created for the first receiving unit group (90) and a second angular spectrum (98) is created for the second receiving unit group (94), and the selection criterion (50) is dependent on a spectrum comparison (100) of the first and second angular spectrum (96, 98). [10] Method for radar sensor data processing (10) according to claim 9, characterized by that the selection criterion (50) is a match identification (102) with which those elevations (70) are identified in the spectrum comparison (100) which are present in the first and second angular spectra (96, 98) with respect to the angle of incidence (φ). [11] Radar sensor data processing system for processing radar sensor data (12), comprising a radar sensor system (20) which provides radar sensor data (12) detecting at least one target object (14) in an environment (16) of a carrier system (18), and a processing unit which is configured to process the radar sensor data (12) by a method for radar sensor data processing (10) according to one of the preceding claims.

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