阅读说明：本技术 用于探测运动对象的系统 (System for detecting moving objects ) 是由 M·施洛瑟 H·布登迪克 于 2018-05-09 设计创作，主要内容包括：一种用于探测运动对象(200)的系统(100)，所述系统具有：?雷达设备(10)，所述雷达设备用于以至少一个角度接收由所述对象(200)反射的至少一个信号；?处理装置(20)，所述处理装置用于求取所述雷达设备(10)与所述对象(200)之间的至少一个相对速度以及针对每个所求取的相对速度的至少一个角度；?其中，能够借助所述处理装置(20)对从所述对象(200)接收的信号执行微多普勒分析；?其中，根据针对所述接收信号所确定的角度来执行所述微多普勒分析；?其中，能够借助所执行的微多普勒分析来求取所述对象(200)的类型。(A system (100) for detecting a moving object (200), the system having: -a radar device (10) for receiving at least one signal reflected by the object (200) at least one angle; -processing means (20) for finding at least one relative speed between the radar device (10) and the object (200) and at least one angle for each found relative speed; -wherein a micro-doppler analysis can be performed on the signals received from the object (200) by means of the processing device (20); -wherein the micro-doppler analysis is performed as a function of the determined angle for the received signal; -wherein the type of the object (200) can be found by means of the performed micro-doppler analysis.)

1. A system (100) for detecting a moving object (200), the system having:

-a radar device (10) for receiving at least one signal reflected by the object (200) at least one angle;

-processing means (20) for finding at least one relative speed between the radar device (10) and the object (200) and at least one angle for each found relative speed;

-wherein a micro-doppler analysis can be performed on the signals received from the object (200) by means of the processing device (20);

-wherein the micro-doppler analysis is performed as a function of the angle determined for the received signal;

-wherein the type of the object (200) can be found by means of the performed micro-doppler analysis.

2. The system (100) according to claim 1, wherein the reception angle can be found for different relative speeds.

3. The system (100) according to claim 1 or 2, wherein the angle can be found by correlation of the received signals.

4. The system (100) according to any of the preceding claims, wherein the angles found are used for simultaneous micro-doppler analysis of a plurality of objects (200) as follows: the plurality of objects have overlapping distributions in relative velocity.

5. The system (200) according to any one of the preceding claims, characterized in that the width of the frequency spread of the received signal and the temporal course of the frequency spread of the received signal can be ascertained by means of the processing device (20).

6. The system (100) according to claim 5, wherein the periodicity of the spread of Doppler frequencies is found by means of the processing means (20).

7. The system (100) according to any of the preceding claims, wherein limiting the angle estimation to a defined small frequency/velocity range is performed.

8. The system (100) according to any one of the preceding claims, wherein the radar device (10) is configured as a continuous wave radar device.

9. The system (100) as claimed in any of the preceding claims, further having a second radar device (30), which is preferably constructed as an FMCW radar device.

10. The system (100) according to claim 9, wherein the radar devices (10, 30) each have at least one transmitting antenna and each have at least two receiving antennas, wherein receiving signals from different receiving directions can be received by means of the receiving antennas.

11. A method for detecting a moving object (200), the method having the steps of:

-receiving, by means of a radar device (10), at least one signal reflected by the object (200) at least one angle;

-finding at least one relative speed between the radar device (10) and the object (200);

-performing a micro-doppler analysis on the received signals by means of the processing means (20), wherein the micro-doppler analysis is performed according to the angle determined for the received signals;

-finding the type of the object (200) by means of the performed micro-doppler analysis.

12. A computer program product with program code means for carrying out the method as claimed in claim 11, when the computer program product is run on a system (100) for detecting a moving object (200) or stored on a computer-readable data carrier.

Technical Field

The invention relates to a system for detecting a moving object. The invention also relates to a method for detecting a moving object. The invention also relates to a computer program product.

Background

The radar system is arranged to transmit radar signals and to compare the radar signals reflected on the object with the transmitted radar signals. In this case, a plurality of different categories are known, by means of which different information about the object can be collected. A known variant is an FMCW (frequency modulated continuous wave) radar in which the transmitted radar signal is modulated by means of a sawtooth function. The object's distance from the radar system can then be determined with good accuracy. The object angle may be obtained by: the antennas are used or controlled in such a way that a signal is emitted in a predetermined direction, the object angle indicating in which direction an object can be found starting from the radar sensor.

A doppler shift relative to a radar signal reflected by a transmitted radar signal may indicate a relative velocity of an object relative to the radar system. Objects moving within themselves (e.g., pedestrians whose arms and legs are swinging back and forth) exhibit characteristic, usually periodic fluctuations in the measurable doppler frequency. These fluctuations can be analyzed so that the object can be further classified.

DE 102015109759 a1 proposes controlling a radar system on board a motor vehicle in such a way that a micro-doppler analysis can be performed.

In order to classify objects by means of radar systems that are mobile in themselves (e.g., on board a motor vehicle), complex modulation with, for example, a chirp sequence can be used. However, the processing here can be very costly. For example, a two-dimensional fourier analysis of the difference signal between the transmitted signal and the received signal may be required, so that a processing device with excellent performance is absolutely necessary.

Disclosure of Invention

One of the tasks on which the invention is based is to provide a simple radar-based technique for detecting moving objects.

According to a first aspect, the invention proposes a system for detecting a moving object, having:

-a radar device for receiving at least one signal reflected by an object at least one angle;

-processing means for finding at least one relative velocity between the radar device and the object and at least one angle for each found relative velocity;

-wherein a micro-doppler analysis can be performed on the signals received from the object by means of the processing means;

-wherein the micro-doppler analysis is performed as a function of the determined angle for the received signal;

-wherein the type of object can be found by means of the performed micro-doppler analysis.

In the proposed system a micro-doppler analysis is performed on the basis of which the type of object is classified. A pedestrian moving by itself has different body parts moving at different speeds relative to the radar device, whereby the speed profile over time thus produced can be characterized for the pedestrian. As a result, it is advantageously possible with the proposed system to provide pedestrian protection or rider protection for a motor vehicle, for example, based solely on radar.

According to a second aspect, the invention proposes a method for detecting a moving object, having the following steps:

-receiving at least one signal reflected by the object at least one angle by means of the radar device;

-finding at least one relative velocity between the radar device and the object;

-performing a micro-doppler analysis on the received signal by means of the processing means, wherein the micro-doppler analysis is performed in dependence on the determined angle for the received signal;

-finding the type of object by means of the performed micro-doppler analysis.

In a preferred embodiment of the system, provision is made for the reception angle to be able to be determined for different relative speeds. Thus, the micro-doppler analysis can also be performed more accurately.

In a preferred embodiment of the system, it is provided that the angle determination can be carried out by correlation of the received signals. Thereby, reliable acquisition of the reception signals obtained from different angles is performed.

A preferred embodiment of the system provides that the determined angle is used for a simultaneous micro-doppler analysis of a plurality of objects: the plurality of objects have overlapping distributions in relative velocity. This makes it possible to distinguish different objects from one another according to the spatial direction. In this case, for example, a plurality of pedestrians can advantageously be distinguished from one another.

A further preferred embodiment of the system is characterized in that the processing device is able to determine the width of the frequency spread (frequeffpreshrinkg) of the received signal and the time profile of the frequency spread of the received signal. In this way, the classification of moving objects is advantageously further improved.

A further preferred embodiment of the system provides that the periodicity of the spread of the doppler frequency is determined by means of a processing device. In this way, for example, a periodic movement of a pedestrian's limb can be detected.

A further preferred embodiment of the system is characterized in that the limiting of the angle estimation to a defined small frequency/velocity range is performed. Thereby, the detection performance of the system can be advantageously focused on the region of interest.

A further preferred embodiment of the system is characterized in that the radar device is designed as a continuous-wave radar device. With this type of radar apparatus, a distinction of the received signals can be achieved well.

A further preferred embodiment of the system is characterized in that it also has a further radar device, which is preferably designed as an FMCW radar device. Thus, the FMCW radar apparatus can be favorably used for finding the distance and the first relative speed, and the continuous wave radar can be favorably used for high speed resolution of the object.

A further preferred embodiment of the system is characterized in that the radar devices each have at least one transmitting antenna and each have at least two receiving antennas, wherein reception signals from different reception directions can be received by means of the receiving antennas. In this way, reliable angle finding of the received signal can be performed.

The disclosed device features are analogously derived from the corresponding disclosed method features and vice versa. This means, in particular, that features, technical advantages and embodiments relating to a system for locating objects in the surroundings of a motor vehicle result in a similar manner from corresponding embodiments, features and advantages relating to a method for locating objects in the surroundings of a motor vehicle and vice versa.

Drawings

The invention is described in detail below with the aid of further features and advantages according to the several figures, which show:

fig. 1 shows an embodiment of the proposed system;

fig. 2 shows another embodiment of the proposed system;

fig. 3 shows a schematic flow chart of the proposed method;

fig. 4 shows a schematic diagram for illustrating the mode of action of an advantageous embodiment of the proposed system;

FIG. 5 shows a cross-section of the diagram of FIG. 4;

FIG. 6 shows a partial view of the diagram of FIG. 4;

fig. 7 shows a partial view of fig. 6 in a time-frequency gridding (Zeit-Frequenz-Rasterung) for finding a direction or an angle of an object.

Detailed Description

The invention is based on the idea of analyzing the spectrum of relative velocity for one or more objects by means of a radar apparatus by means of micro-doppler analysis. In this way, accurate analysis or classification of single and/or multiple objects may be achieved even though they may have similar spacing and velocity but different directions in a complex scene.

The system may allow a combination of the advantages of different radar devices to analyze not only accurate information about the type of motion of an object, but also the position and change in position of the object. The evaluation of more accurate speed information of an object can be achieved in particular if the motor vehicle having the radar device moves relative to the surroundings.

In this way the classification of objects can be significantly improved. The classification of the object as a pedestrian/a rider can be performed in particular in an improved manner, so that, for example, a driving assistance system and/or an active and/or passive accident protection device on board the motor vehicle can be controlled in an improved manner. For example, if it is determined that a pedestrian is in a collision course with a motor vehicle (kollionskurs), a signal may be issued to alert the driver or the pedestrian. In an advantageous variant, automatic braking of the motor vehicle can be initiated by means of the system.

The processing means is arranged to perform a micro-doppler analysis of the signals received by the radar apparatus. It can be determined by micro-doppler analysis whether the motion pattern of the object coincides with the known motion pattern of the pedestrian. Depending on the detailed refinement of the performed micro-doppler analysis, it may even be advantageous to determine which activity the pedestrian is performing.

A radar device designed as a continuous wave radar device can be operated in a continuous wave operating mode, for example, over a period of about 15ms to about 25ms, and in other variants over a period of about 10ms to about 15ms or about 25ms to about 30 ms. By means of the evaluation of the doppler frequency, the accuracy of the velocity determination can be significantly increased.

In this way, the system can be well matched to the requirements for the detection of pedestrians, wherein, for example, in the case of a transmission duration of the continuous wave signal of approximately 20ms, an object speed resolution of approximately 0.1m/s can be achieved, which is sufficient for a more accurate analysis of the typical speed of a pedestrian. The typical speed of a pedestrian is about 1m/s for the trunk and up to 4m/s for the forward swinging legs, which results in about 10 to 40 frequency bins (freqenzbins). In contrast, a significant reduction in relative velocity occurs for a pedestrian crossing.

In the micro doppler analysis, the spread of the doppler spectrum with respect to the moving object is analyzed, in which a stationary object and a moving rigid body that does not generate a spread in the doppler spectrum are ignored.

By means of the micro-doppler analysis, a difference signal between the transmitted continuous wave radar signal and the continuous wave radar signal reflected at the object can be analyzed with respect to the frequency distribution of the difference signal. The analysis is preferably carried out by means of a fourier transformation. In this case, the signal energy can be calculated in a predetermined frequency range. The frequency distribution can also be analyzed over the course of its time, so that, for example, the movement patterns of walking or running pedestrians can be distinguished from one another.

In an advantageous embodiment of the proposed system, a further radar device can be provided, which can be designed according to any desired measurement principle (preferably according to the FMCW principle), which generally uses a continuous frequency ramp of the radar signal. Other embodiments are also possible, for example the following radar devices may be used: the respective spatial angles are scanned in the radar apparatus mechanically or electronically one after the other to determine the object angle.

Preferably, the signals of the individual FMCW ramps of the further radar device are processed separately from one another. For this purpose, the FMCW ramp is preferably analyzed by means of a known one-dimensional fourier transform. The computational overhead of this approach is much lower than for two-dimensional fourier analysis in the case of a chirp sequence. In order to separate different objects, the detected frequency peaks separated by different slopes can be combined with each other after fourier analysis. As a result, the two radar apparatuses can be operated alternately, whereby scanning can be performed more easily in the same frequency range.

Alternatively, the two radar devices can also be integrated into a single radar device, the integrated radar devices being operated successively with different signals. At one point in time, the integrated radar device can be operated, for example, with an FMCW signal or with a continuous wave signal. The operating types can in particular be activated alternately. Cost savings can be achieved by saving radar equipment. Known radar apparatuses can be retrofitted to the described system with simple expenditure.

Preferably, only frequencies below a predetermined limit frequency (Grenzfrequenz) should be considered, wherein the limit frequency is determined on the basis of the speed of the radar device relative to the surroundings. Thus, preferably only the signal components assigned to the following objects are considered: the object approaches the radar device, i.e. the object moving relative to the surroundings itself, faster than the movement of the radar device relative to the surroundings. The doppler frequencies of these objects are correspondingly smaller (or greater in magnitude) than the doppler frequencies corresponding to negative natural velocities.

Fig. 1 shows a basic variant of the proposed system. A radar device 10 can be identified, which is functionally connected to the processing means 20. A transmission signal which is at least partially reflected at an object 200 (for example a pedestrian) is transmitted by means of the radar device 10 and received at different, very similar angles as a reception signal. The received signals are subjected to a micro-doppler analysis by means of the processing means 20 and the type of object 200 is classified accordingly.

The proposed system can be advantageously used in motor vehicles as radar-based pedestrian protection. Radar-based applications in stationary monitoring systems (e.g. in the military domain) are also envisaged.

Fig. 2 shows a useful exemplary application of the above-described advantageous embodiment of the proposed system 100 for a motor vehicle 50, which comprises a radar device 10, a further radar device 30 and a processing device 20. Each of the radar devices 10, 30 has at least one transmitting antenna and in each case at least two, preferably four, receiving antennas (not shown), with the aid of which received signals from spatially different directions can be received and then correlated, from which direction information can be derived for the received signals. The two radar devices 10, 30 may also be designed integrally as one radar device, in which case they preferably operate alternately as the first radar device 10 and the other radar device. In the surroundings 210 of the motor vehicle 50, a moving object 200 is present, which is represented in the case of fig. 1 by a pedestrian.

With the aid of the system 100, the object 200 is scanned with the aid of radar signals and position information, movement information and classification information of the object 200 are determined. The determined information can be made available for further use by means of an interface 40, which can be designed as a warning device and/or as a control device (not shown) on board the motor vehicle 50.

Moveable object 200 may move relative to ambient environment 210. In addition, the object 200 may move or perform micro-motion inside thereof. Here, portions of the moveable object 200 (in the case of a pedestrian: arms and legs) may move at a different speed relative to the surrounding environment 210 than the object 200. In this case, not only the doppler frequency but also the doppler frequency of the entire range can be measured by means of the radar devices 10, 30.

The movable object 200, which is configured as a pedestrian, for example, can move with respect to the surroundings 210 at a speed of about 5 km/h. Due to the periodic movement of the leg (and in most cases also the arm) of the pedestrian, the doppler frequency spread of the leg thus also fluctuates in a periodic manner. When both feet are standing on the ground, the maximum speed is given by the upper body (Torso). The velocity decreases along the leg until it decreases to zero at the foot. Thus, each doppler frequency corresponding to a velocity between zero and the velocity of the upper body may be measurable. This is also the time instant of minimum doppler frequency spread. Conversely, in the case of forward swing, the speed of the foot reaches about 3 to 4 times the speed of the upper body.

By means of the doppler frequency range or frequency bin range thus determined, correlation of the received signals of all receiving antennas can be performed. In this way, a so-called "multi-objective estimator" can be implemented, in which a plurality of objects arranged at different angles are determined in a single frequency bin. In order to determine the velocity spectrum of the object 200 sufficiently accurately without complex modulation and complex evaluation of the radar signals, it is proposed that the distance and/or the rough movement of the object 200 is determined by means of a first radar device 20, which uses known FMCW signals. In order to obtain a high speed resolution of the object 200, the micromotion of the object 200 is additionally determined and analyzed by means of the radar device 10, preferably by means of a micro-doppler analysis. In this case, the radar device 10 preferably uses a continuous wave signal ("CW ramp"), so that the transmitted radar signal is not modulated in time. The determination by means of the continuous wave signal can be performed longer than the prevalent ramp definition of the FMCW method and lasts, for example, about 20ms to achieve a sufficient speed resolution for the object 200.

For each frequency bin, the correlation of the received signal may be performed in relation to the received power therein or independently. In this way, either a detection of a power increase or a correlation between the individual received signals of different receiving antennas can be carried out, wherein the computational overhead is higher in the latter case.

For continuous wave signals, only the doppler effect has an influence on the received signal. Conversely, the distance of the object 200 has no effect. The difference frequency and thus the doppler frequency corresponds directly to the physical velocity of the object 200 relative to the motor vehicle 50. Since the distance cannot be determined for continuous wave signals, it is necessary to continue to separate the scene into individual objects 200 by the conventional FMCW method. However, both radar devices 10, 30 can determine the velocity and the angle of the object 200 relative to the radar devices 10, 30, so that in general the micro-doppler effect can be unambiguously assigned to one of the detected objects 200.

Finally, the continuous wave signal can be analyzed in the basic form of the proposed system almost completely separately from the conventional FMCW ramp.

Fig. 3 shows a flow chart 300 of a method for determining information about a movable object 200, which also uses a further radar device 30, wherein the information comprises, in particular, the position or movement of the object 200 and the frequency distribution of the micromotion.

In step 305, the object 200 is scanned by means of a further radar device 30, preferably based on FMCW signals. Alternatively, other radar methods are possible. The transmitted and reflected signals are qualitatively indicated in a time diagram by step 305. The determination is known in the radar art and may be performed in any known type. As a result of the scanning, a first distance d (t) to the further radar device 30 and a first relative velocity v1(t) between the object 200 and the further radar device 30 are preferably determined.

In step 310, which may be performed alternately with step 305, the object 200 is scanned by means of the radar device 10 on the basis of a radar signal (continuous wave signal) having a constant frequency. The diagram indicated by step 310 outlines the transmitted and reflected signals. As a result of the scanning, a second relative velocity v2(t) between the object 200 and the radar device 10 is preferably determined. Here, the second relative velocity is preferably very high resolution, and thus enables efficient performance of the micro-doppler analysis.

In step 315, the information determined in steps 305 and 310 are mutually distributed. The first and second information, which each comprise the same angle, preferably also the same temporal development of the angle, relate to the same object 200 and can be assigned to one another. As a combination of the first and second information, step 315 preferably provides a distance d (t), a velocity v (t), and an angle

In step 320, the frequency distribution of the second relative velocity may be analyzed to determine whether the resulting pattern is indicative of a pedestrian.

For this purpose, the spread of the relative velocity or the spread of the doppler frequency representing the relative velocity is found and analyzed. In the case of a broad expansion, the object 200 is classified as a pedestrian by means of temporal analysis, wherein the respective pattern or a feature of such a pattern can be predetermined and can be taken into account for the comparison.

In the case of analyzing the received power, it is possible to simply sum up (English "nick-

Integration ", non-coherent Integration) of each individual received power of all receive antennas, or may alternatively try to determine one or more objects at respective angles in the frequency bin to what extent with sufficiently high quality. This can be achieved in order to save on the high overhead for the multi-target estimator, if only more powerful objects can be determined in each frequency bin (due to the strong power difference of the received signals) or only one angle should be determined in a simple manner.

The processing of the continuous wave signal of the radar apparatus 10 is substantially the same as the processing of the FMCW ramp (e.g. of the further radar apparatus 30). After non-coherent integration on all receive channels, spectral analysis is preferably performed by means of a fast fourier transform. In this case, the signal is decomposed into frequencies, which consist of the frequencies. The power of the frequency components in each frequency bin is then determined, wherein the frequency bins respectively correspond to defined frequency intervals of the total spectrum.

However, here, contrary to the FMCW ramp, no frequency peaks need to be detected (and mutually allocated). Each frequency bin having a power above the noise threshold directly indicates the presence of a physical object 200 having a corresponding velocity (in the radial direction). This is naturally found for objects 200 with micro-doppler effect, even for the whole spectrum. The angle estimation is also practically the same as in the case of an FMCW ramp. This again omits the detection of individual frequency peaks only. Furthermore, there is only a single continuous wave signal that can determine the angle, so the angle calculation for each ramp is also omitted. However, in the presence of micro-doppler, the individual frequency bins appear at different ramp locations.

In the automotive field, the self-movement of the radar apparatus 10 may make it difficult to perform micro-doppler analysis for detecting pedestrians. This appears to the moving radar apparatus 10: the stationary object 200 moves directly towards the radar device at its own speed in front. In the case of a lateral offset, the viewing direction velocity (scheinbare geschwidtigkeit) decreases by the cosine of the viewing angle. The image object 200 stops briefly before moving behind the radar device 10 at the moment of overtaking (i.e. in the case of 90 °). Thus, the reflected power of the stationary object 200 is spectrally limited to the following frequencies: this frequency corresponds to a speed between zero and a negative self-speed. The speed of the motor vehicle 50 relative to the surroundings 210 is referred to as the self speed.

These relationships are illustrated in diagram 400 of fig. 4. Time t is plotted in the horizontal direction and according to the Doppler frequency f in the vertical direction_{Doppler device}(t) plot velocity v. The base signal 405 represents an object that moves relative to the radar apparatus 10 at a speed lower than the negative self-speed, and therefore the object is regarded as stationary. The peaks (english peaks)410 correspond to the objects 200 in the form of pedestrians. Here, each peak 410 represents the maximum relative velocity generated by the pedestrian's step relative to the second radar device 30.

Curve 420 represents stopped oncoming traffic for motor vehicle 50. The boundary line of the region 405 represents the negative self-speed v of the motor vehicle 50_Self-body。

All other frequencies outside this region are not disturbed by stationary objects. In contrast, in other FMCW ramps, the background noise (hind ground-Clutter) is distributed over a significantly larger frequency range.

Crossing pedestrians are particularly important for pedestrian protection or rider protection within the scope of driver assistance. The radial component of motion in the direction of the radar apparatus 10 is significantly reduced-but not zero-compared to a pedestrian oncoming from the front. Even if the pedestrian vertically crosses the road on which the motor vehicle 50 moves, the pedestrian does not move vertically to the radar apparatus 10. However, for a pedestrian crossing, the relative speed of the leg that normally swings only forward is higher than the relative speed of an object standing directly in the direction of travel in front.

Therefore, only the corresponding frequency components can be analyzed spectrally without interference. Due to the slow but active movement of the pedestrian in the direction of the radar device 10, the micro doppler effect to be analyzed falls directly in a frequency range below the doppler frequency corresponding to the negative self-velocity. There is generally a high quality estimate of the speed of the vehicle 50 on board the vehicle. Thus, regions of the spectrum that are important to pedestrians can be directly selected.

In a turn, the individual points of the motor vehicle 50 have different speeds due to the rotational movement. The speed of the motor vehicle 50 itself is typically determined with respect to the rear axle of the vehicle. The respective speed of the front-mounted radar device 10 can also be derived simply from the commonly known yaw rate (girrating) of the motor vehicle 50.

Since the pedestrian approaches the carriageway from the side, the measurable speed is also reduced by the lateral offset relative to the direction of movement of the radar devices 10, 30. At the same viewing angle, the pedestrian obtains a reduction equal to the apparent velocity of the stationary object 200. On the other hand, the radial component of the actual pedestrian movement increases due to the larger viewing angle with the same direction of movement of the pedestrian.

A similar approach in principle to that for stationary radar systems with constant transmit frequency is applied for the actual analysis of micro-doppler. However, due to the coverage of a large part of the micro-doppler spread, the intensity of the micro-doppler power, the width of the uncovered spread, the amplitude of the fluctuation of this width over time, the time span/period between the two maximum spreads (and thus the measured step frequency of the pedestrian) are the main determinants.

Fig. 5 shows a diagram of a section along time t τ of fig. 4. On the left side of the region of the peak 410, a broad spread of the frequency of the peak 410 of the pedestrian can be seen. The peak 410 is due to the pedestrian's forward swinging foot at the high relative velocity generated thereby relative to the radar apparatus. One can also see the peak 430, which is generated by the stopped vehicle 50, which is stopped and therefore has a small relative speed similar to a pedestrian. Since the chassis is made of metal, the received power of the chassis is thereby increased considerably. In this way, the pedestrian can be well distinguished, and the object 200 can be classified as a pedestrian and the information can be subjected to subsequent processing.

Fig. 6 shows a partial view B of fig. 5, with respect to which time-frequency gridding is performed.

Fig. 7 shows the ungrid region B of the diagram in diagram a) and the time-frequency gridding of the region B in diagram B), wherein the frequency bins are shown horizontally across all measurement cycles and all frequency bins are shown vertically for a single measurement cycle. The time-frequency-meshed square grids B1, B2, B3, B4 correspond to frequency bins in the discrete domain or defined frequency intervals in the analog domain.

No analysis is performed in frequency bin B1, since only substantially stationary objects relative to the radar device 10, 30 can be expected there (or the received power of stationary objects can be expected to dominate).

In frequency bin B2, the received power is correlated as follows: this results in an object at an angle, wherein the object is arranged in the form of a pedestrian relative to the radar device 10, 30.

In frequency bin B3, the received power is correlated as follows: this results in an object at an angle, wherein the object 200 is arranged in the form of a vehicle relative to the radar devices 10, 30.

In frequency bin B4, the object 200 is not detected due to the correlation of the received signals.

Additionally, it should be noted at the time of this analysis that the pedestrian has a stationary part (standing foot) by definition and gives maximum power through the upper body. Accordingly, there is no gap (no signal power) between the doppler frequency belonging to the negative self-velocity and the micro doppler spread of the pedestrian. If the maximum of the spectrum is far from the doppler frequency belonging to a negative self-velocity, the object is not classified as a pedestrian accordingly.

Advantageously, the method may be implemented as software running on the radar apparatus 10, 30 and the processing means 20, thereby enabling simple changeability of the method.

Advantageously, no consideration of the effect of raindrops is required for the proposed system, since the power reflected by raindrops typically overlaps with the micro-doppler effect of pedestrians. Since spatially distributed events are involved here, it appears that: despite the absolutely significant power in part, the angle of incidence can often still not be determined. Thus, the rain water only effectively reduces the signal-to-noise ratio, wherein in particular the entire width of the power expansion of the pedestrian can be determined without interference.