Method and device for evaluating radar data from a radar sensor
The method enhances radar data evaluation by reducing data volume and computational effort through targeted parameter selection and cross-cycle processing, improving resolution and sensitivity for long-range and stationary targets.
Patent Information
- Application Number
- DE102024208167
- Authority / Receiving Office
- DE · DE
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2024-08-28
- Publication Date
- 2026-03-05
AI Technical Summary
Existing radar systems face limitations in resolution and data processing efficiency due to bandwidth and measurement duration constraints, leading to increased computational demands and storage requirements for unambiguous distance and velocity measurements.
A method and device for evaluating radar data that reduces data by selecting and processing only relevant parameters within a predetermined range, using digital beamforming and cross-cycle evaluation to enhance signal-to-noise ratio and resolution, applicable to both single and cooperative radar sensors.
Significantly reduces data volume and computational effort while maintaining performance, improving resolution and sensitivity, especially for long-range targets and stationary objects, through targeted data reduction and coherent signal processing.
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Abstract
Description
[0001] The invention relates to a method and a device for evaluating radar data from a radar sensor. State of the art
[0002] Several methods are known for modulating radar signals. The modulated radar signals are emitted, reflected by objects, and the reflected radar signals are received again to determine the distances, relative velocities, and / or angular positions of the objects.
[0003] A well-known modulation method is the so-called chirp sequence method, in which a packet of fast frequency ramps or chirps with a duration T is used. f is sent out. Then there is a pause. g provided for. One cluster of chirps followed by a pause corresponds to one measurement cycle with duration T. f + T P .
[0004] An alternative method for radar modulation is Orthogonal Frequency Division Multiplexing (OFDM), in which the bandwidth BW is sampled using multiple orthogonal subcarriers. Temporal sampling is achieved by transmitting multiple so-called OFDM symbols.
[0005] German patent DE 10 2014 223 990 A1 discloses a method for detecting at least two targets with one radar sensor and a corresponding radar sensor. Furthermore, US patent 10,921,436 B2 discloses a resolution of velocity ambiguity of a reflector by encoding MIMO radar transmitter frequencies. Disclosure of the invention
[0006] The invention provides a method and a device for evaluating radar data from a radar sensor with the features of the independent patent claims.
[0007] Preferred embodiments are the subject of the respective dependent claims.
[0008] According to a first aspect, the invention relates to a method for evaluating radar data from a radar sensor. The radar sensor generates radar data in a multitude of measurement cycles. The radar data is reduced to partial radar data by means of a restriction. The partial radar data corresponds to a predetermined parameter range of a radar spectrum. The partial radar data is then evaluated.
[0009] According to a second aspect, the invention relates to a device for evaluating radar data from a radar sensor, comprising an interface that receives radar data generated by the radar sensor in a multitude of measurement cycles. A computing unit reduces the radar data to partial radar data based on a restriction, wherein the partial radar data correspond to a predetermined parameter range of a radar spectrum. The computing unit further evaluates the partial radar data. Advantages of the invention
[0010] In radar measurements, the resolution at distance (Δd) depends on the bandwidth used (BW). The resolution at relative velocity (Δv) depends on the measurement duration (T). f away: Δd=c2BW,Δv=c2f0Tf.
[0011] Here, c denotes the speed of light and f0 the center frequency of the radar modulation. For unambiguous distance measurement without undersampling up to the maximum distance or range d max must be used in equidistant scanning. N=dmax / Δd
[0012] Sample values are distributed across the bandwidth BW. For an unambiguous measurement of the relative velocity over a relevant relative velocity interval [v] min , v max ] must be used in equidistant sampling M=(vmax−vmin) / Δv temporal samples over the measurement period T f be distributed.
[0013] The maximum measurement duration T f in a single package may be limited, for example due to requirements regarding the maximum clearly measurable relative speed, the maximum permissible latency until radar location data is output, or regarding thermal aspects.
[0014] By jointly evaluating radar data from multiple measurement cycles (e.g., multiple chirp packets), the effective measurement duration can be significantly increased, resulting in a significant improvement in the signal-to-noise ratio and the resolution in relative velocity compared to a single measurement cycle.
[0015] For the joint evaluation of several measurement cycles, the radar data of all measurement cycles must be kept together in the memory of the radar sensor, or, when processing the data on a central control unit, they must be transferred, which places certain demands on the transmission speed.
[0016] The method according to the invention reduces the radar data in a suitable manner for evaluation across multiple cycles. Furthermore, the method according to the invention can be carried out in parallel to a conventional signal processing sequence for a single cycle.
[0017] The invention ultimately proposes reducing the amount of raw data or radar data through suitable criteria and signal processing, such that cross-cycle evaluation is applied only to relevant areas within a specific range, Doppler spectrum, and angle, particularly azimuth and / or elevation angles. The selection of relevant areas is carried out in such a way that the performance advantage for the relevant applications is maintained.
[0018] For example, suitable data reduction can be enabled so that the performance advantage for the relevant use cases is maintained while significantly reducing the required amount of data and the computational effort for cross-cycle evaluation.
[0019] Furthermore, the method is not limited to a single radar sensor, but can also be used in a cooperative radar sensor network.
[0020] According to one embodiment of the method for evaluating radar data from the radar sensor, parameters of the predetermined parameter range include at least one of a distance, a relative velocity, an azimuth angle and an elevation angle.
[0021] According to another embodiment of the method for evaluating radar sensor data, parameters of the predetermined parameter range include a first distance range that is closer to the radar sensor than a second distance range. This improves the signal-to-noise ratio and thus provides increased sensitivity of the radar sensor, particularly for long-range targets. This is especially important because radar reception performance scales with the fourth power of the distance, a phenomenon also known as free-space path loss.
[0022] For example, improved Doppler resolution can help to better or even at all separate two targets at a certain horizontal or vertical distance, since the angular difference between these two targets is usually small, so that they often cannot be separated at an angle.
[0023] According to another embodiment of the method for evaluating radar data from the radar sensor, the first distance range corresponds to a distance range from half of the radar sensor's maximum range to its maximum range. Thus, limiting the cycle-spanning evaluation to, for example, the second half of the range Doppler spectrum does not lead to a significant reduction in performance, while simultaneously approximately halving the amount of radar data to be stored, namely the partial radar data.
[0024] According to a further embodiment of the method for evaluating radar sensor data, parameters of the predetermined parameter range include a relative velocity, wherein the relative velocity is essentially zero and / or essentially corresponds to a velocity of the radar sensor. In this way, a common application, namely the detection and separation of stationary targets or the detection of targets with a relative velocity close to zero, that is, in particular, an adaptive cruise control (ACC) target object, or both, can be provided.
[0025] According to another embodiment of the method for evaluating radar sensor data, modulation sequences of the radar spectrum are coherently summed by digital beamforming in such a way that the predetermined parameter range, in which the relative velocity is essentially zero or essentially corresponds to a velocity of the radar sensor, is amplified. Furthermore, other targets, i.e., those in a parameter range different from the predetermined one, can be suppressed. With typically four modulation sequences, this can lead to a reduction of the radar data by a factor of 4 in the case of one relevant velocity range, or by a factor of 2 in the case of two relevant velocity ranges.
[0026] For example, digital beamforming can be applied using a delay-and-sum beamformer or a minimum-variance distortionless (MVDR) beamformer. Digital beamforming, as described above, can be used with a modulation method from DE 10 2014 212 280 A1, in particular according to paragraphs
[0009] to
[0024] , from DE 10 2014 212 284 A1, in particular according to paragraphs
[0011] to
[0035] , or from DE 10 2017 200 317 A1, in particular according to paragraphs
[0006] to
[0020] . If a conventional chirp sequence method is used, certain Doppler cells can alternatively be selected, which, however, exhibit ambiguity in their relative velocity.
[0027] According to another embodiment of the method for evaluating radar data from the radar sensor, the radar sensor has a plurality of receiving antennas for receiving signals, and the received signals are summed coherently by digital RX beamforming in such a way that the predetermined parameter range is amplified. With typically four receiving antennas, this can lead to a reduction of the radar data by a factor of 4 in the case of one direction or by a factor of 2 in the case of two directions. The digital RX beamforming can be applied, for example, using a delay-and-sum beamformer or a minimum-variance distortionless (MVDR) beamformer. The predetermined parameter range can include, for example, targets in the direction of travel, specific angular ranges during cornering, and / or other arbitrary angles. A preferred angle can also be selected depending on the distance.
[0028] According to another embodiment of the method for evaluating radar data from the radar sensor, the radar sensor has a plurality of receiving antennas and a plurality of transmitting antennas for receiving signals, and the received signals are coherently summed by a common digital TX-RX beamforming system such that the predetermined parameter range is amplified. With typically four transmitting antennas and four receiving antennas, this can lead to a reduction of the radar data by a factor of 16 in the case of one direction or by a factor of 16 / 5 in the case of five directions. The predetermined parameter range can, for example, include targets in the direction of travel, specific angular ranges when cornering, and / or other arbitrary angles. A preferred angle can also be selected based on distance.
[0029] The combined digital TX-RX beamforming can be implemented, for example, using a delay-and-sum beamformer or a minimum-variance distortion-free (MVDR) beamformer. The multiple transmitting antennas in an automotive radar sensor can typically be operated using time-division multiplexing (TDM) or Doppler division multiplexing (DDM). Before coherent processing of the received signals from the multiple transmitting antennas, a relative-velocity-dependent phase compensation must be performed in TDM, and a velocity-dependent correction of the transmitting sequence is required in DDM.
[0030] Often, the chirp intervals are so large that Doppler undersampling occurs, resulting in ambiguous Doppler bins. Therefore, the compensation described above must either be performed for all velocity ambiguities or restricted to a predetermined parameter range, where parameters within the predetermined range include the relative velocity, as described above.
[0031] The embodiments described above, in particular the various variants of the predetermined parameter ranges, can be applied essentially independently of one another. These embodiments, especially the various variants of the predetermined parameter ranges, can be used individually or at least partially in combination. However, combining the common digital TX-RX beam shaping with the digital RX beam shaping might prove difficult and may not be possible.
[0032] For example, a combined application of the predetermined parameter range, wherein the first distance range corresponds to a distance range from half of the maximum range of the radar sensor to the maximum range of the radar sensor, together with the predetermined parameter range, wherein modulation sequences of the radar spectrum are coherently summed by digital beamforming such that the predetermined parameter range where the relative velocity is essentially zero or essentially equal to a velocity of the radar sensor is amplified, and together with the predetermined parameter range, wherein the received signals are coherently summed by a common digital TX-RX beamforming such that the predetermined parameter range where targets are in the direction of travel is amplified, can provide a reduction in the amount of data, i.e., the radar data, by a factor of up to 2*4*16 = 128.
[0033] According to a further embodiment of the method for evaluating radar sensor data, the reduction of the radar data is also performed dynamically. This dynamic generation allows for a further improvement in the reduction to the partial radar data. For example, the reduction of the radar data can additionally be performed based on detections in a single cycle, on information from tracked objects, or on map information.
[0034] For example, the predetermined parameter range in which relevant targets have been detected can be evaluated over several measurement cycles, i.e., the number of measurement cycles can be increased.
[0035] Optionally, the evaluation of the radar data can include a coherent combination of the radar data acquired in the measurement cycles at the spectral level. This can, for example, further increase the Doppler resolution and / or the signal-to-noise ratio. Furthermore, the radar sensor can operate, for example, according to a chirp sequence method or an OFDM method.
[0036] The chirp packets or measurement cycles can internally use any arrangement and encoding, for example, temporally non-equidistant sequences of chirps for an unambiguous relative velocity measurement or Doppler division multiplex (DDM) codes for MIMO methods. Furthermore, the center frequency of the chirps within a chirp packet can be varied, for example, increasing or decreasing linearly.
[0037] Furthermore, the parameters of the chirp packets can be varied from measurement cycle to measurement cycle. For example, the sign of the chirp slope, the sign of any change in the center frequency of individual chirps within the chirp packet, the chirp bandwidth, the magnitude of the change in center frequency, and / or ramp timings can be varied. This has the advantage that measurements from individual measurement cycles are uncorrelated. When evaluating multiple chirp packets together, such changes can be appropriately accounted for.
[0038] The computing unit can, for example, be integrated into the radar sensor or designed as or integrated within a central control unit.
[0039] All or individual process steps of the method according to the invention can be performed on the radar sensor itself or on a central control unit. The central control unit can, for example, have more computing resources or memory than the radar sensor. When performing the process on the central control unit, it is advantageous to transfer the radar data to the central control unit after the reduction process step.
[0040] Further advantages, features and details of the invention will become apparent from the following description, in which various embodiments are described in detail with reference to the drawings. Brief description of the drawings
[0041] They show: Fig. 1 a schematic block diagram of a radar sensor with a device for evaluating radar data from the radar sensor according to an embodiment of the invention; Fig. 2. A flowchart of an exemplary signal processing sequence of cross-cycle processing in parallel to single-cycle processing; Fig. Three exemplary variants of a time and frequency scheme for radar data; and Fig. 4 a flowchart of a method for evaluating radar data from a radar sensor according to a further embodiment of the invention.
[0042] In all figures, identical or functionally equivalent elements and devices are designated with the same reference numerals. The numbering of process steps serves for clarity and generally does not imply a specific chronological order. In particular, several process steps can be performed simultaneously. Description of the exemplary implementations
[0043] The present invention is described by way of example using the chirp sequence method. Alternatively, however, the present invention can also be applied analogously to the OFDM method.
[0044] Fig. Figure 1 shows a schematic block diagram of a radar sensor 1 with a device 5 for evaluating radar data from the radar sensor 1. The device 5 can be part of the radar sensor 1 or external.
[0045] The device 5 comprises an interface 2 which receives radar data generated by a transmitter / receiver unit 6 of the radar sensor 1 in a multitude of measurement cycles. The radar data is stored in a memory 3. A computing unit 4 reduces the radar data to partial radar data based on a restriction, wherein the partial radar data correspond to a predetermined parameter range of a radar spectrum.
[0046] The computing unit 4 can perform radar processing of the radar data using known radar modulation methods, for example the chirp sequence method or the orthogonal frequency division multiplex (OFDM).
[0047] The computing unit 4 determines a radar spectrum. The parameters of the radar spectrum include, for example, a distance, a relative velocity, an azimuth angle, an elevation angle, or a selection (subset) thereof.
[0048] Partial radar data can be stored in memory 3. The radar spectrum can be divided into at least one predetermined parameter range.
[0049] The computing unit 4 evaluates the partial radar data. For this purpose, the radar data stored over the corresponding number of measurement cycles can first be combined for the predetermined parameter range. Multi-frame integration (MFI) methods can be used, such as the chirp sequence 3D method, as described in US 2020 / 0408879 A1, keystone methods, or backprojection methods. In this way, several high-resolution partial radar images can be obtained by combining the radar data from multiple measurement cycles.
[0050] Fig. Figure 2 shows a flowchart of an exemplary signal processing sequence for cross-cycle processing in parallel with single-cycle processing.
[0051] On the right side of the flowchart is a standard signal processing sequence 210 for a single cycle. This standard signal processing sequence 210 can be performed in parallel with a sequence 220 shown on the left side of the flowchart for multi-cycle processing, with a suitable reduction of the radar data.
[0052] Before processes 210 and / or 220 are carried out, a two-dimensional Fourier transform (Fast Fourier Transform, FFT) can be performed for each ramp sequence and optionally for each receiving channel.
[0053] The standard signal processing sequence 210 can, for example, include in step 211 a non-coherent summation of individual spectra of the ramp sequences for each transmitting and receiving antenna. Furthermore, in step 212, the individual spectra from the transmitting antennas can be summed non-coherently, and the individual spectra from the receiving antennas can be summed coherently or non-coherently. In a further step 213, a target can be detected by subdividing a distance / velocity parameter range as a function of the ratio of the signal power of the radar radiation in the corresponding parameter range to a constant false alarm rate (CFAR) threshold, including peak interpolation. Additionally, velocity ambiguities and velocity overlaps can be resolved in step 214.Optionally, a transmitter assignment can also be performed, as described, for example, in the publications DE 10 2014 212 280 A1, DE 10 2014 212 284 A1, DE 10 2017 200 317 A1, or DE 10 2014 223 990 A1. Furthermore, in step 215, an angle estimation can be performed after phase compensation, as described, for example, in DE 10 2014 212 284 A1 or DE 10 2014 223 990 A1. A transmitter assignment can also be performed here, as described, for example, in DE 10 2017 200 317 A1.
[0054] In process 220 for cycle-spanning processing with suitable reduction of the radar data, relevant areas can be defined in step 221, for example, within a range, a Doppler spectrum, and an angle, particularly azimuth and / or elevation angles. In a further step 222, one or more distance ranges for the predetermined parameter range (so-called range bins) can be selected. Furthermore, in step 223, for example, a coherent summation of individual spectra of the ramp sequences for each transmitting and receiving antenna can be provided using velocity beamforming. Alternatively, so-called Doppler bins can be selected. Finally, in step 224, the individual spectra can be summed coherently or incoherently via the transmitting and / or receiving antennas.Of the steps 222, 223 and 224 for reducing radar data, not all need to be carried out; individual steps can be skipped.
[0055] The subsequent step 225 can be performed across the cycles using a Fast Fourier Transform (FFT), taking into account relative object motion, or model-based using a single-target or multi-target model for expected measurement signals of a range Doppler bin of the individual measurement cycle. In a further step 226, particularly a final step 226, target detection, resolution of velocity ambiguities, and angle estimation can be performed, provided these two processes have not already been carried out during radar data reduction. Angle estimation can be further refined if digital beamforming for multiple directions was performed during radar data reduction.
[0056] Fig. Figure 3 shows exemplary variations of a time and frequency scheme for radar data. Specifically, the time and frequency scheme illustrates frequencies f over a time t.
[0057] For example, the center frequency of the chirps within a chirp packet can be varied. In particular, the center frequency can increase linearly, as shown in Figure 31, or decrease linearly, as shown in Figure 32.
[0058] Furthermore, the parameters of the chirp packets can be varied from measurement cycle to measurement cycle. For example, the sign of the chirp slope, the sign of the change in the center frequency of the individual chirps within the chirp packet, the chirp bandwidth, the magnitude of the change in center frequency, and the ramp timings can be varied.
[0059] Fig. Figure 4 shows a flowchart of a procedure for evaluating radar data from a radar sensor, for example the radar sensor 1 described above.
[0060] In a first step S1, the radar sensor 1 generates respective radar data in a large number of measurement cycles.
[0061] In step S2, the radar data is reduced to partial radar data by means of a restriction. The partial radar data corresponds to a predetermined parameter range of a radar spectrum. The parameters of the predetermined parameter range can include at least one of a distance, a relative velocity, an azimuth angle, and an elevation angle.
[0062] In step S3, the partial radar data are evaluated. For this purpose, the radar data corresponding to the predetermined parameter range across the numerous measurement cycles, i.e., the partial radar data, can first be combined.
[0063] In one variant, parameters of the predetermined parameter range can include a first distance range that is closer to radar sensor 1 than a second distance range. For example, improved Doppler resolution can help to better, or even at all, distinguish two targets at a certain horizontal or vertical distance over a long distance, since the angular difference between these two targets is usually small, meaning they often cannot be distinguished at that angle. The first distance range can correspond to a range from half the maximum range of radar sensor 1 up to the maximum range of radar sensor 1.Therefore, limiting the cycle-spanning evaluation to, for example, the second half of the range Doppler spectrum does not lead to a significant reduction in performance, while at the same time the amount of radar data to be stored, namely the partial radar data, can be roughly halved.
[0064] Alternatively or additionally, parameters of the predetermined parameter range can include a relative velocity, where the relative velocity is essentially zero and / or essentially corresponds to the velocity of radar sensor 1. This allows for a common use case, namely the detection and separation of stationary targets or the detection of targets with a near-zero relative velocity, in particular an adaptive cruise control (ACC) target, or both. Modulation sequences of the radar spectrum can be coherently summed by digital beamforming such that the predetermined parameter range, where the relative velocity is essentially zero or essentially corresponds to the velocity of radar sensor 1, is amplified.Furthermore, other targets, i.e., those within a parameter range different from the predetermined one, can be suppressed. With typically four modulation sequences, this can lead to a reduction in radar data by a factor of 4 in the case of one relevant speed range, or by a factor of 2 in the case of two relevant speed ranges.
[0065] Alternatively or additionally, the radar sensor 1 can have a plurality of receiving antennas for receiving signals, whereby the received signals are summed coherently by digital RX beamforming in such a way that the predetermined parameter range in which targets are located in the direction of travel is amplified. With typically four receiving antennas, this can lead to a reduction of the radar data by a factor of 4 in the case of one direction or by a factor of 2 in the case of two directions. The digital RX beamforming can be applied, for example, using a delay-and-sum beamformer or a minimum-variance-distortionless (MVDR) beamformer.
[0066] Alternatively or additionally, the radar sensor 1 can have a plurality of receiving antennas and a plurality of transmitting antennas for receiving signals, wherein the received signals are coherently summed by a common digital TX-RX beamforming system such that the predetermined parameter range in which targets are located in the direction of travel is amplified. With typically four transmitting antennas and four receiving antennas, this can lead to a reduction of the radar data by a factor of 16 in the case of one direction or by a factor of 16 / 5 in the case of five directions.
[0067] The combined digital TX-RX beamforming can be implemented, for example, using a delay-and-sum beamformer or a minimum-variance-distortionless (MVDR) beamformer. The multiple transmitting antennas in an automotive radar sensor can typically be operated using time-division multiplexing (TDM) or Doppler division multiplexing (DDM).
[0068] Before coherent processing of the received signals from the multiple transmitting antennas, relative velocity-dependent phase compensation must be performed for time-division multiplexing (TDM), and velocity-dependent correction of the transmitter order must be performed for DDM. Often, the chirp intervals are so large that undersampling occurs in the Doppler effect, resulting in ambiguous Doppler bins. Therefore, the compensation described above must either be performed for all velocity ambiguities or restricted to a predetermined parameter range, where parameters within the predetermined range include the relative velocity, as described above.
[0069] For example, reducing the S2 value of radar data can also be performed dynamically. This can be done, for instance, based on detections within a single cycle, information from tracked objects, or map data.
[0070] Although the present invention has been explained above by way of example embodiments, it is not limited to these, but can be modified in many ways. In particular, combinations of the preceding embodiments are also conceivable. QUOTES INCLUDED IN THE DESCRIPTION
[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited Patent Literature
[0000] DE 10 2014 223 990 A1 [0005, 0053] US 10,921,436 B2
[0005] DE 10 2014 212 280 A1 [0026, 0053] DE 10 2014 212 284 A1 [0026, 0053] DE 10 2017 200 317 A1 [0026, 0053] US 2020 / 0408879 A1
[0049]
Claims
[1] Method for evaluating radar data from a radar sensor (1), comprising the steps: Generating (S1) respective radar data by the radar sensor (1) in a multitude of measurement cycles; Reducing (S2) the radar data by restricting it to partial radar data corresponding to a predetermined parameter range of a radar spectrum; and Evaluating (S3) the partial radar data. [2] Method according to claim 1, wherein parameters of the predetermined parameter range include at least one of a distance, a relative velocity, an azimuth angle and an elevation angle. [3] Method according to claim 1 or 2, wherein parameters of the predetermined parameter range comprise a first distance range which is closer to the radar sensor (1) than a second distance range. [4] Method according to claim 3, wherein the first distance range corresponds to a distance range from half of a maximum range of the radar sensor (1) up to the maximum range of the radar sensor (1). [5] Method according to any of the preceding claims, wherein parameters of the predetermined parameter range include a relative velocity, wherein the relative velocity is essentially zero and / or essentially corresponds to a velocity of the radar sensor (1). [6] Method according to claim 5, wherein modulation sequences of the radar spectrum are summed coherently by digital beam shaping such that the predetermined parameter range in which the relative velocity is essentially zero or corresponds essentially to a velocity of the radar sensor (1) is amplified. [7] Method according to one of the preceding claims, wherein the radar sensor (1) has a plurality of receiving antennas for receiving received signals, and wherein the received signals are summed coherently by digital RX beamforming such that the predetermined parameter range is amplified. [8] Method according to one of the preceding claims, wherein the radar sensor (1) has a plurality of receiving antennas and a plurality of transmitting antennas for receiving received signals, and wherein the received signals are summed coherently by a common digital TX-RX beamforming such that the predetermined parameter range is amplified. [9] Method according to one of the preceding claims, wherein the reduction (S2) of the radar data is further carried out dynamically. [10] Device (5) for evaluating radar data from a radar sensor (1), comprising: an interface (2) which is configured to receive radar data generated by the radar sensor (1) in a multitude of measurement cycles; and a computing device (4) which is designed to reduce the radar data to partial radar data by means of a restriction, wherein the partial radar data correspond to a predetermined parameter range of a radar spectrum; wherein the computing device (4) is further equipped to evaluate the partial radar data.
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