DE102019204914A1 - Determination of a clear relative speed by means of model adaptation - Google Patents

Abstract

The present invention relates to a device (16) for determining a relative speed of an object (12), having: an input interface (22) for receiving preprocessed sensor data from a frequency-modulated multi-pulse radar sensor (14), the sensor data representing a frequency spectrum of an object in an environment a vehicle (18); an evaluation unit (24) for determining a position of a high point within the frequency spectrum based on the sensor data; a description unit (26) for determining a description parameter which describes a shape of the frequency spectrum in the immediate vicinity of the position of the high point; a modeling unit (28) for adapting a predefined model based on the determined position of the high point and for determining a plurality of model values based on the adjusted model, the model values each describing a form of a frequency spectrum for a speed hypothesis; a comparison unit (30) for comparing the description parameter with the plurality of model values and for selecting a model value with maximum correspondence with the description parameter; and an output unit (32) for outputting the speed hypothesis of the selected model value as the relative speed of the object. The present invention also relates to a system (10) and a method for determining a relative speed of an object (12).

Description

The present invention relates to a device for determining a relative speed of an object. The present invention also relates to a system and a method and a computer program product for determining a relative speed of an object.

Modern vehicles (cars, vans, trucks, motorcycles, etc.) have a large number of sensors that provide the driver with information and control individual functions of the vehicle partially or fully automatically. Radar technology is an important sensor principle for capturing the environment in the area of autonomous and semi-autonomous vehicles. Radar sensors in the vehicle sector typically include several transmitting and receiving elements that form virtual channels of the radar sensor (Rx / Tx antenna pairs). In each reception channel, the baseband signal is downmixed, filtered and then the baseband signal obtained in this way is digitized. By preprocessing the baseband signals for each receiving channel, a target, that is to say an object, can be detected and localized in a field of view of the radar sensor.

Most of the radar sensors used today in the vehicle sector work as multi-pulse radar sensors (also referred to as chirp sequence radar sensors), in which several frequency-modulated pulses are emitted at short intervals. The preprocessing can be a Fourier transformation or optimal filtering of the baseband data for a single radar pulse (so-called fast preprocessing, fast-time processing), a further Fourier transformation for several pulses (so-called slow preprocessing, slow-time processing), beamforming, signal power detection , for example based on the constant-force alarm rate method, as well as a high point determination.

gemessen werden, mit der Wellenzahl K und der Pulswiederholungszeit t_r. Dies bedeutet, dass Geschwindigkeiten im Abstand v_m auf denselben Wert innerhalb des Hauptintervalls abgebildet werden. Aktuelle Radarsensoren im Radarbereich weisen dabei typischerweise Werte von v_m im Bereich von 20 bis 60 m/s auf, sodass es zu mehrdeutigen Geschwindigkeitsmessungen kommen kann. Dies bedeutet, dass gemessene Geschwindigkeiten um Vielfache von v_m von der tatsächlichen Geschwindigkeit abweichen können.One challenge for multi-pulse radar sensors with constant pulse repetition time (PRT) is that they are limited to measurements of a relative speed (or a relative radial speed within the so-called main interval. Only within this main interval between - v _m / 2 and + v _m / 2 can be a maximum unique speed $$v_{m=\frac{1}{2\text{K}{t}_r}}$$

can be measured with the wave number K and the pulse repetition time t _r . This means that speeds at a distance v _m are mapped to the same value within the main interval. Current radar sensors in the radar range typically have values of v _m in the range from 20 to 60 m / s, so that ambiguous speed measurements can occur. This means that measured speeds can deviate from the actual speed by a multiple of v _m .

One approach to solving this problem is to use different pulse repetition times, either between pulses or from one coherent processing interval (CPI) to the next. This allows the maximum unique speed to be increased. A disadvantage of using different pulse repetition times between successive intervals is that a latency time is increased and a link between detections in several intervals becomes necessary. This is prone to errors in particular in the case of multiple and / or rapidly moving targets, as occurs regularly in the vehicle area. Approaches in which the pulse repetition time between pulses is varied within the same interval are fundamentally unsuitable for processing with a fast Fourier transform (FFT) and can have side lobes in the speed spectrum. Staggered pulse-to-pulse methods, in which the pulse repetition time is varied in successive intervals, have the disadvantage that target detection can only be carried out based on half the pulses. This reduces the profit and makes the use of so-called slow-time multiple input multiple output (MIMO) methods more difficult.

In connection with the clear measurement of a relative speed, the DE 10 2014 212 280 A1 discloses a radar measurement method. In particular, an FMCW radar sensor and a method for determining a relative speed of a radar target are disclosed, in which an FMCW radar measurement is carried out with a transmission signal whose modulation pattern includes temporally interleaved sequences of ramps. A two-dimensional spectrum is calculated separately for each of the sequences from the baseband signals. From a position of a high point (peak) in at least one two-dimensional spectrum of the baseband signals, values for the relative speed of a radar target are determined which are periodic at a predetermined speed. A phase relationship between spectral values that are obtained at the same position in each case in the separately calculated two-dimensional spectra is checked for agreement with phase relationships expected for several of the determined periodic values of the relative speed. An estimated value for the relative speed of the radar target is selected from the determined, periodic values of the relative speed.

Disadvantages of previously known methods are the comparatively complex processing and the associated need for computing power. In addition, the previous approaches mostly caused a loss of resolution.

Based on this, the present invention has the object of providing an approach for the unambiguous determination of a relative speed of an object. In particular, it should be made possible to carry out an unambiguous speed measurement without a significantly higher computing power being required and / or the sensitivity and / or reaction time being reduced.

• einer Eingangsschnittstelle zum Empfangen von vorverarbeiteten Sensordaten eines frequenzmodulierten Multipuls-Radarsensors, wobei die Sensordaten ein Frequenzspektrum eines Objekts in einem Umfeld eines Fahrzeugs umfassen;
• einer Auswerteeinheit zum Ermitteln einer Position eines Hochpunkts innerhalb des Frequenzspektrums basierend auf den Sensordaten;
• einer Beschreibungseinheit zum Ermitteln eines Beschreibungsparameters, der eine Form des Frequenzspektrums in einer unmittelbaren Umgebung der Position des Hochpunkts beschreibt;
• einer Modellierungseinheit zum Anpassen eines vordefinierten Modells basierend auf der ermittelten Position des Hochpunkts und zum Ermitteln mehrerer Modellwerte basierend auf dem angepassten Modell, wobei die Modellwerte jeweils eine Form eines Frequenzspektrums für eine Geschwindigkeitshypothese beschreiben;
• einer Vergleichseinheit zum Vergleichen des Beschreibungsparameters mit den mehreren Modellwerten und zum Auswählen eines Modellwertes mit maximaler Übereinstimmung mit dem Beschreibungsparameter; und
• einer Ausgabeeinheit zum Ausgeben der Geschwindigkeitshypothese des ausgewählten Modellwertes als Relativgeschwindigkeit des Objekts.

To achieve this object, the invention relates in a first aspect to a device for determining a relative speed of an object, with:

• an input interface for receiving preprocessed sensor data from a frequency-modulated multipulse radar sensor, the sensor data including a frequency spectrum of an object in the surroundings of a vehicle;
• an evaluation unit for determining a position of a high point within the frequency spectrum based on the sensor data;
• a description unit for determining a description parameter which describes a shape of the frequency spectrum in the immediate vicinity of the position of the high point;
• a modeling unit for adapting a predefined model based on the determined position of the high point and for determining a plurality of model values based on the adjusted model, the model values each describing a form of a frequency spectrum for a speed hypothesis;
• a comparison unit for comparing the description parameter with the plurality of model values and for selecting a model value with maximum correspondence with the description parameter; and
• an output unit for outputting the speed hypothesis of the selected model value as the relative speed of the object.

• einem frequenzmodulierten Multipuls-Radarsensor zum Erfassen eines Objekts in einer Umgebung eines Fahrzeugs mit einer Vorverarbeitungseinheit zum Vorverarbeiten eines Signals eines Empfangskanals des Multipuls-Radarsensors; und
• einer Vorrichtung wie zuvor beschrieben.

In a further aspect, the present invention relates to a system, in particular an automotive radar system, for determining a relative speed of an object, with:

• a frequency-modulated multi-pulse radar sensor for detecting an object in the vicinity of a vehicle, with a preprocessing unit for pre-processing a signal of a receiving channel of the multi-pulse radar sensor; and
• a device as described above.

Further aspects of the invention relate to a corresponding method and a computer program product with program code for carrying out the steps of the method when the program code is executed on a computer, as well as a storage medium on which a computer program is stored that, when executed on a computer, causes the method described herein to be carried out.

Preferred embodiments of the invention are described in the dependent claims. It goes without saying that the features mentioned above and those yet to be explained below can be used not only in the respectively specified combination, but also in other combinations or alone, without departing from the scope of the present invention. In particular, the device, the system, the method and the computer program product can be designed in accordance with the configurations described for the device and the system in the dependent claims.

According to the invention, a distinction between several speed hypotheses is proposed in a multi-pulse radar sensor system by adapting a model in the region of a high point. Data from a frequency-modulated multi-pulse radar sensor are received after preprocessing. A high point is determined in a frequency spectrum. This high point is compared with several high points determined from a model, which correspond to various speed hypotheses. On the basis of the comparison, that speed hypothesis is selected in which there is the smallest deviation between the model and the sensor data. To this extent, the invention makes use of the fact that the shape of high points in a frequency spectrum differ both in the speed dimension and in the distance dimension for different speeds. By means of a comparison with a modeling, the ambiguity in the speed measurement can therefore be resolved and a clear relative speed can be determined.

In comparison to previous approaches, a clear speed measurement is made possible. It is not necessary to adjust the pulse repetition time. A simple processing of the radar sensor data is retained. A reliable, unambiguous measurement of the relative speed of an object results.

In a preferred embodiment, the modeling unit is designed to adapt the predefined model and to determine the plurality of model values based on a look-up table with precalculated model values for different speed hypotheses for different positions of high points. The predefined model can be calculated once. The results can be stored in a look-up table. This has the advantage that a complex calculation does not have to be carried out for each measurement. Efficient data processing is ensured. In addition, rapid predictability is achieved.

In an advantageous embodiment, the immediate vicinity of the position of the high point comprises a predefined number of discrete values. It has been found that the use of a comparatively small number of discrete values enables sufficient accuracy with regard to the differentiation between different speed hypotheses (different forms of high points). Using a predefined number ensures easy comparability. For example, by using 3 to 13 or 9 values, efficient calculability can be achieved.

In a preferred embodiment, the predefined model is based on a calculation of time domain values, in which a transit time of the sampled values within a pulse is taken into account. A single pulse has a certain length, so that the conditions can change during the duration of a single pulse, especially at high speeds. The transit time corresponds to a delay within one pulse. This runtime or this delay is usually neglected by previous models. The additional consideration of the change in transit time per pulse ensures that the shape of the frequency spectrum in the immediate vicinity of the high point changes in accordance with the real data and thus a distinction can be made between speed hypotheses

In a further preferred embodiment, a calculation of the model values is based on an optimal filtering over a pulse and a Fourier transformation over a plurality of pulses if the preprocessed sensor data have been preprocessed based on an optimal filtering of any pulse shape. It is possible to use an optimal filtering (matched filter) in connection with a Fourier transformation over the several pulses of a processing interval (slow-time Fourier transformation). Depending on the configuration of the multi-pulse radar sensor, this results in a modeling that corresponds to the real data processing within the radar sensor. A high level of accuracy is ensured when determining the clear relative speed.

In an advantageous embodiment, a calculation of the model values is based on a first Fourier transformation over a pulse and a second Fourier transformation over several pulses if the preprocessed sensor data were preprocessed based on processing a linearly frequency-modulated pulse sequence. As before, the modeling can also be carried out in accordance with the real data processing if a first Fourier transformation is carried out for one pulse (fast-time Fourier transformation) followed by a Fourier transformation over several pulses (slow-time Fourier transformation). The result is a precise and appropriate modeling with high informative value with regard to the relative speed.

In a preferred embodiment, the multi-pulse radar sensor is designed to transmit radar pulses with a long, coherent processing time. The multi-pulse radar sensor is preferably designed to transmit radar pulses with a high speed resolution. The multi-pulse radar sensor is preferably designed to transmit 512 radar pulses within 25 ms. The use of a high coherent processing time results in an amplification of the difference in the shape of the frequency spectrum in the region of the high point for different speed hypotheses. In this respect, the distinction ensures a high level of informative value.

In a further preferred embodiment, the multi-pulse radar sensor is designed to transmit radar pulses with a high bandwidth. The multi-pulse radar sensor is preferably designed to transmit radar pulses with a bandwidth between 800 MHz and 4,000 MHz, in particular a bandwidth of 1,000 MHz. The use of a high bandwidth over which the frequency change is carried out in the baseband, in particular in combination with a high coherent integration time, results in a more easily distinguishable form of the frequency spectrum in the vicinity of the high point for different relative speeds. The use of a high bandwidth results in a high distance resolution.

In a further advantageous embodiment, the multi-pulse radar sensor is designed for operation in a frequency range between 76 GHz and 81 GHz. Additionally or alternatively, the multi-pulse radar sensor has a constant pulse repetition time. Operation in a released frequency range enables standard-compliant use. It can be used well in the vehicle sector.

In an advantageous embodiment, the preprocessing unit of the multi-pulse radar sensor is designed for the simultaneous processing of 256 or 512 radar pulses. It has been found to be advantageous if a comparatively large number of radar pulses are processed at the same time in order, for example, to carry out a Fourier transformation over the multiple radar pulses.

A radar sensor sends out a radar signal and receives reflections of the radar signal from objects (also known as targets) within a field of view of the radar sensor. The field of view describes an area within which objects can be detected. A multi-pulse radar sensor sends out several radar pulses within a coherent processing interval and can also be referred to as a chirp sequence radar sensor. A radar sensor can comprise several individual sensors which, for example, enable a 360 ° all-round view and can thus record a complete image of the surroundings of a vehicle. Preprocessed sensor data refer to sampled baseband signals that have already been preprocessed. Preprocessing steps can in particular include an optimal filtering or a Fourier transformation of the sampled values per pulse and a Fourier transformation over a plurality of pulses. A description parameter and a model value can be one-dimensional or multidimensional. In particular, a description parameter or a model value in the case of a description of the immediate vicinity of the position of the high point by means of a predefined number of discrete values for each of these values or for each of these positions can include a performance specification. It is possible for a description parameter and a model value to describe the predefined environment of a high point in each case by means of a predefined number of magnitude and phase values. A comparison and an assessment of a match can be carried out based on a determination of a mean square error, for example. In particular, an object can be another vehicle, but also another road user (pedestrian, cyclist, etc.) or a stationary object (tree, house, traffic sign, etc.). A relative speed is to be understood here in particular as a radial speed as measured by a radar sensor.

• 1 eine schematische Darstellung eines Systems gemäß einem Aspekt der vorliegenden Erfindung;
• 2 eine schematische Darstellung einer erfindungsgemäßen Vorrichtung;
• 3 eine schematische Darstellung einer mehrdeutigen Geschwindigkeitsmessung;
• 4 eine schematische Darstellung der Berechnung des erfindungsgemäßen Modells;
• 5 eine schematische Darstellung eines Abstands-Geschwindigkeitsleistungsspektrums mit einer vergrößerten Darstellung einer Umgebung eines Hochpunkts;
• 6 eine schematische Darstellung der sich ergebenden Modellierungen für das Frequenzspektrum in der unmittelbaren Umgebung der Position des Hochpunkts im Vergleich mit den gemessenen Daten; und
• 7 eine schematische Darstellung des erfindungsgemäßen Verfahrens.

The invention is described and explained in more detail below with reference to a few selected exemplary embodiments in conjunction with the accompanying drawings. Show it:

• 1 a schematic representation of a system according to an aspect of the present invention;
• 2 a schematic representation of a device according to the invention;
• 3 a schematic representation of an ambiguous speed measurement;
• 4th a schematic representation of the calculation of the model according to the invention;
• 5 a schematic illustration of a distance-speed power spectrum with an enlarged illustration of a vicinity of a high point;
• 6th a schematic representation of the resulting modeling for the frequency spectrum in the immediate vicinity of the position of the high point in comparison with the measured data; and
• 7th a schematic representation of the method according to the invention.

In the 1 is schematically a system according to the invention 10 for determining a relative speed of an object 12 shown. With the system 10 In the example shown, it is an automotive radar system that is installed in a vehicle 18th is integrated. At the object 12 For example, it can be another vehicle or a tree, a pedestrian or a static object such as a house or a traffic sign. The system 10 includes a multi-pulse radar sensor 14th , which sends out frequency-modulated radar pulses to the object 12 capture. The multi-pulse radar sensor 14th is on the vehicle 18th attached and captured objects 12 within a field of view 20th . The system also includes a device 16 for determining a relative speed of an object 12 . The device according to the invention 16 is also in the vehicle in the illustrated embodiment 18th integrates and communicates with the multi-pulse radar sensor 14th via a vehicle bus system. The device according to the invention 16 allows an unambiguous determination of a relative speed of an object 12 compared to the multi-pulse radar sensor 14th to undertake.

In the 2 is schematically the device according to the invention 16 shown. The device 16 can in particular be integrated into a vehicle control unit of the vehicle. But it is also possible for the device to be implemented as an additional module for the radar sensor itself. It is also possible that the device 16 in software is implemented, which is executed by a processor of the radar sensor or in a processor of the vehicle control unit. The device 16 includes an input interface 22nd , an evaluation unit 24 , a unit of description 26th , a modeling unit 28 , a comparison unit 30th as well as an output unit 32 . The various units and interfaces can in particular be implemented individually or in combination or completely or partially in software and / or in hardware.

The input interface 22nd is connected to a frequency-modulated multi-pulse radar sensor and receives its data after preprocessing raw data within the multi-pulse radar sensor. The received sensor data include a frequency spectrum of an object in the surroundings of a vehicle. A frequency spectrum is understood to mean, in particular, the magnitude and the phase of the Fourier-transformed baseband signals. A frequency spectrum in the speed dimension and / or a frequency spectrum in the distance dimension can be received. If amount and phase are considered separately, one can also speak of an amount or phase spectrum. A frequency spectrum here also includes an output signal of an optimal filter.

The evaluation unit 24 serves to evaluate the received sensor data in order to determine a position of a high point within the frequency spectrum or the magnitude spectrum.

In the description unit 26th a description parameter is determined which describes the shape of the frequency spectrum in the immediate vicinity of the position of the high point. For example, the values of the power for frequencies at a distance of a few (for example two or three) discrete values around the high point are determined as description parameters with several individual values (vector). The immediate surroundings therefore preferably include the frequency value of the high point itself as well as some neighboring frequency values. In particular, the description parameter can thus provide information about the shape of the high point. The description parameter can therefore in particular include the measured values at the high point and in the vicinity of the high point.

In the modeling unit 28 a predefined model is adapted based on the determined position of the high point. The predefined model also describes a frequency spectrum or a form of a frequency spectrum in the vicinity of a high point, assuming model data or a model value. For a given position of a high point, the model offers different frequency spectra or forms of the frequency spectrum, which represent different speed hypotheses. In this respect, a model value preferably corresponds in its format to the description parameter. A model value therefore also includes, for example, several spectral values in the vicinity of the high point. In other words, the model value is a multi-valued vector. Different model values are calculated for different speed hypotheses.

The adaptation of the predefined model and the determination of the multiple model values in the modeling unit 28 can in particular be based on a look-up table. Several model parameters assigned to different speed hypotheses are therefore precalculated for different high point positions, so that when the device according to the invention is in operation, only one lookup is required to determine the model values for a determined position of a high point. This results in efficient predictability.

These calculated model values are then used in the comparison unit 30th compared with the description parameter to determine which model value best reflects reality. Specifically, the measured values in the high point environment (description parameters) are therefore preferably compared with the corresponding elements of the model value. It is examined which model value offers the highest agreement with the description parameter. For this purpose, for example, a mean square error between the distances between individual elements of the description parameter and the model value can be used.

After the comparison is completed, the output unit 32 that speed hypothesis (or the model value) is output which belongs to the smallest model deviation. In this respect it is possible to determine a clear speed of an object.

In the 3 an example of an ambiguous speed measurement using a conventional multi-pulse radar sensor, as used in the automotive sector, is shown schematically. The real relative speed (v _real ) is plotted on the X axis. The relative speed (v _meas ) measured by the sensor is plotted on the Y-axis. Based on a constant pulse repetition time, the relative speed can only be measured within the so-called main interval between − v _m / 2 and + v _m / 2. The maximum unambiguous speed v _m results from 1 / (2Kt _r ) based on the wave number K and the pulse repetition time t _r . Like in the 3 shown, so if a maximum unique Speed of v _m = 30 m / s is assumed, only a measurement between -15 and +15 m / s can be made.

In the 3 is shown as an example that a moving vehicle is approaching a stationary target at a speed of 26 m / s. In the case of an autonomous braking system or an autonomous driving system, emergency braking or an evasive maneuver should be initiated in this case. Like in the 3 the relative speed of the stationary target is shown 34 however, mapped to a measured speed of v _meas = 4 m / s. This measured speed corresponds to a vehicle moving at a relative speed of a moving target 36 moves a little faster than your own vehicle. The required reaction of the autonomous system, i.e. the initiation of an emergency braking or evasive maneuver, would not take place.

According to the invention, it is now proposed to keep the pulse repetition time constant and to differentiate between several speed hypotheses based on a model adaptation in the immediate vicinity of a high point. The model adaptation takes place after preprocessing, i.e. after the application of an optimal filtering or a Fourier transformation via a pulse (fast-time Fourier transformation), a Fourier transformation via several pulses (slow-time Fourier transformation), a beamforming, a power detection and a high point determination. A model is formulated for each speed hypothesis and a selection is made based on the deviation between the various models and the measurement.

in der ersten Variante (links) und gemäß $$e^{j\frac{4\pi Br}{Lc}l}{e}^{j4\pi \text{K}v{t}_{r}m}{e}^{j\frac{4\pi Bv{t}_r}{Lc}lm}{e}^{j4\pi \text{K}v{t}_{s}l}$$

in der zweiten Variante (rechts). Dabei bezeichnet x_b das bekannte Basisbandsignal, t_s die Abtastzeit, c die Wellenausbreitungsgeschwindigkeit, t_r die Pulswiederholungszeit, B die effektive Pulsbandbreite, L die Anzahl der Abtastwerte pro Puls, I=0, ... ,L-1 die Indices der Abtastwerte pro Puls, M die Anzahl an Pulsen und m=0,...,M-1 die Pulsindices.. Der folgende Schritt S2 umfasst in der ersten Variante auf der linken Seite eine Optimalfilterung (fast-time zero-velocity-matched filter) oder eine Fouriertransformation über einen Puls (fast-time Fouriertransformation) in der zweiten Variante auf der rechten Seite. In beiden Fällen wird im dritten Schritt S3 eine Fouriertransformation über mehrere Pulse vorgenommen (slow-time Fouriertransformation). Relevant ist, dass in beiden Fällen der zweite Schritt S2 und der dritte Schritt S3 lediglich für eine unmittelbare Umgebung der Position des Hochpunkts (peak neighborhood) durchgeführt werden.In the 4th two variants of a model calculation according to the invention are shown schematically. The first variant shown on the left is used for an optimal filtering of any multipulse waveform. The second variant on the right is used for processing a linear frequency-modulated pulse train. In the 4th the calculations for both model variants for distance r and relative speed v are shown. First, in a first step S1 Samples simulated according to $${\text{X}}_{\text{b}}\left(t_{s}l-\frac{2r}{c}-\frac{2v{t}_r}{c}\text{m}\right)e^{j\mathrm{4th}\pi \text{K}v{t}_{r}m}{e}^{j\mathrm{4th}\pi \text{K}v{t}_{s}l}$$

in the first variant (left) and according to $$e^{j\frac{\mathrm{4th}\pi \mathrm{B.}r}{\mathrm{L.}c}l}{e}^{j\mathrm{4th}\pi \text{K}v{t}_{r}m}{e}^{j\frac{\mathrm{4th}\pi \mathrm{B.}v{t}_r}{\mathrm{L.}c}lm}{e}^{j\mathrm{4th}\pi \text{K}v{t}_{s}l}$$

in the second variant (right). Here x _b denotes the known baseband signal, t _s the sampling time, c the wave propagation speed, t _r the pulse repetition time, B the effective pulse bandwidth, L the number of sampled values per pulse, I = 0, ..., L-1 the indices of the sampled values per pulse, M the number of pulses and m = 0, ..., M-1 the pulse indices .. The following step S2 The first variant on the left includes an optimal filtering (fast-time zero-velocity-matched filter) or a Fourier transformation via a pulse (fast-time Fourier transformation) in the second variant on the right. In both cases the third step is S3 a Fourier transformation carried out over several pulses (slow-time Fourier transformation). It is relevant that in both cases the second step S2 and the third step S3 can only be carried out for an immediate vicinity of the position of the peak neighborhood.

für die erste Variante und $$e^{j\frac{4\pi Br}{Lc}l}{e}^{j4\pi \text{K}v{t}_{r}m}$$

für die zweite Variante. Jeweils der erste Term beschreibt die Fast-Time-Abtastwerte und der zweite Term die Slow-Time-Abtastwerte. Die Fast-Time-Abtastwerte beziehen sich dabei auf die Basisbandabtastwerte eines Pulses, die Slow-Time-Abtastwerte auf die Basisbandabtastwerte mehrerer aufeinanderfolgender Pulse. Der optimale Verarbeitungsansatz für derartige Modellierungen ist entweder eine Optimalfilterung oder eine Fouriertransformation über einen Puls, gefolgt von einer Fouriertransformation über mehrere Pulse.This modeling extends models of the conventional processing of radar signals $${\text{X}}_{\text{b}}\left(t_{s}l-\frac{2r}{c}\right)e^{j\mathrm{4th}\pi \text{K}v{t}_{r}m}$$

for the first variant and $$e^{j\frac{\mathrm{4th}\pi \mathrm{B.}r}{\mathrm{L.}c}l}{e}^{j\mathrm{4th}\pi \text{K}v{t}_{r}m}$$

for the second variant. The first term describes the fast-time sample values and the second term describes the slow-time sample values. The fast-time sampled values relate to the baseband sampled values of a pulse, the slow-time sampled values to the baseband sampled values of a plurality of successive pulses. The optimal processing approach for such modeling is either an optimal filtering or a Fourier transformation over a pulse, followed by a Fourier transformation over several pulses.

With this modeling, however, a pulse-dependent delay of the fast-time sample values of a pulse is not mapped. If this delay is included in the modeling, the aforementioned modeling results in equation (1) and in equation (2). If, in this case, the preprocessing that is optimal for the models in equation (3) and equation (4), i.e. an optimal filtering and Fourier transformation per pulse followed by a Fourier transformation over several pulses, is used, a form of a neighborhood of a high point changes into the preprocessed data based on a unique speed.

In the 5 In this context, an example of a distance-speed power spectrum is depicted. The speed frequency is plotted on the x-axis, the distance frequency is plotted on the y-axis. For illustration, exactly one target is shown, so that the spectrum shown has exactly one high point 38 having. The representation corresponds to a distance-speed power spectrum according to the Fourier transformation over one pulse and over several pulses. The high point 38 is shown enlarged. In the area of the enlarged display, in addition to the two-dimensional enlarged display, a corresponding one-dimensional section is shown at the position of the high point in the speed dimension and in the distance dimension.

In the 6th the adaptation of a predefined model in the immediate vicinity of the high point is shown as an example. The two illustrations on the left show the dimension of the distance. The two representations on the right show the speed dimension. The two upper representations show the power (in decibels) on the y-axis over the frequency on the x-axis. The illustrations below show the phase (π) on the y-axis versus the frequency on the x-axis. The measured values (the description parameter) are with circles 40 marked. The (multi-dimensional) model value for the applicable relative speed of -26 m / s is marked with a cross 42 and the model value for the speed hypothesis of 4 m / s is with squares 44 marked. As shown, the applicable model, i.e. the speed hypothesis of -26 m / s, meets the measured values in the vicinity of the high point much better. The relevant speed hypothesis can therefore be selected based on a comparison.

In the 7th a method according to the invention is shown schematically. The method includes steps of receiving S10 of preprocessed sensor data, the determination S12 a position of a high point, of determining S14 a description parameter, adapting S16 of a predefined model, of comparison S18 the description parameter with the plurality of model values and the selection of a model value and the output S20 the speed hypothesis. The method can be implemented, for example, as software that is executed on a vehicle control device or in a radar sensor. The method is preferably used during the operation of a radar sensor.

The invention has been comprehensively described and explained with reference to the drawings and the description. The description and explanation are to be understood as examples and not restrictive. The invention is not limited to the disclosed embodiments. Other embodiments or variations will become apparent to those skilled in the art after using the present invention and after carefully analyzing the drawings, the disclosure and the following claims.

In the claims, the words “comprising” and “having” do not exclude the presence of further elements or steps. The undefined article “a” or “an” does not exclude the presence of a plural. A single element or a single unit can perform the functions of several of the units mentioned in the patent claims. An element, a unit, an interface, a device and a system can be implemented partially or completely in hardware and / or in software. The mere mention of some measures in several different dependent patent claims should not be understood to mean that a combination of these measures cannot also be used advantageously. A computer program can be stored / distributed on a non-volatile data carrier, for example on an optical memory or on a semiconductor drive (SSD). A computer program can be distributed together with hardware and / or as part of hardware, for example by means of the Internet or by means of wired or wireless communication systems. Reference signs in the claims are not to be understood as restrictive.

List of reference symbols

10

system

12

object

14th

Multipulse radar sensor

16

contraption

18th

vehicle

20th

Field of view

22nd

Input interface

24

Evaluation unit

26th

Description unit

28

Modeling unit

30th

Comparison unit

32

Output unit

34

Relative speed of the stationary target

36

Relative speed of the moving target

38

High point

40

circle

42

cross

44

square

QUOTES INCLUDED IN THE DESCRIPTION

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Patent literature cited

• DE 102014212280 A1 [0006]

Claims (13)

Device (16) for determining a relative speed of an object (12), with: an input interface (22) for receiving preprocessed sensor data from a frequency-modulated multipulse radar sensor (14), the sensor data comprising a frequency spectrum of an object in the surroundings of a vehicle (18); an evaluation unit (24) for determining a position of a high point within the frequency spectrum based on the sensor data; a description unit (26) for determining a description parameter which describes a shape of the frequency spectrum in the immediate vicinity of the position of the high point; a modeling unit (28) for adapting a predefined model based on the determined position of the high point and for determining a plurality of model values based on the adjusted model, the model values each describing a form of a frequency spectrum for a speed hypothesis; a comparison unit (30) for comparing the description parameter with the plurality of model values and for selecting a model value with maximum correspondence with the description parameter; and an output unit (32) for outputting the speed hypothesis of the selected model value as the relative speed of the object. Device (16) after Claim 1 wherein the modeling unit (28) is designed to adapt the predefined model and to determine the plurality of model values based on a look-up table with precalculated model values for different speed hypotheses for different positions of high points. Device (16) according to one of the preceding claims, wherein the immediate vicinity of the position of the high point comprises a predefined number of discrete values. Device (16) according to one of the preceding claims, wherein the predefined model is based on a calculation of time domain values in which a transit time of the sampled values within a pulse is taken into account. Device (16) according to one of the preceding claims, wherein a calculation of the model values is based on an optimal filtering over a pulse and a Fourier transformation over several pulses if the preprocessed sensor data were preprocessed based on an optimal filtering of any pulse shape. Device (16) according to one of the preceding claims, wherein a calculation of the model values is based on a first Fourier transformation over a pulse and a second Fourier transformation over several pulses if the preprocessed sensor data was preprocessed based on processing a linearly frequency-modulated pulse sequence. System (10), in particular an automotive radar system, for determining a relative speed of an object (12), with: a frequency-modulated multipulse radar sensor (14) for detecting an object in the vicinity of a vehicle (18) with a preprocessing unit for preprocessing a signal of a reception channel of the multipulse radar sensor; and an apparatus (16) according to any preceding claim. System (10) Claim 7 , wherein the multi-pulse radar sensor (14) is designed to transmit radar pulses with a high coherent processing time, preferably to transmit 512 radar pulses within 25 ms. System (10) according to one of the Claims 7 to 8th , wherein the multi-pulse radar sensor (14) is designed to transmit radar pulses with a high bandwidth, preferably a bandwidth between 800 MHz and 4000 MHz, in particular a bandwidth of 1000 MHz. System (10) according to one of the Claims 7 to 9 , wherein the multi-pulse radar sensor (14) is designed to operate in a frequency range between 76 GHz and 81 GHz; and / or has a constant pulse repetition time. System (10) according to one of the Claims 7 to 10 , wherein the preprocessing unit of the multipulse radar sensor (14) is designed for the simultaneous processing of 256 or 512 radar pulses. A method for determining a relative speed of an object (12), comprising the steps of: receiving (S10) preprocessed sensor data from a frequency-modulated multi-pulse radar sensor (14), the sensor data including a frequency spectrum of an object in the surroundings of a vehicle (18); Determining (S12) a position of a high point within the frequency spectrum based on the sensor data; Determining (S14) a description parameter which describes a shape of the frequency spectrum in the immediate vicinity of the position of the high point; Adapting (S16) a predefined model based on the determined position of the high point and for determining a plurality of model values based on the adapted model, the model values each describing a form of a frequency spectrum for a speed hypothesis; Comparing (S18) the description parameter with the plurality of model values and for selecting a model value with maximum correspondence with the description parameter; and outputting (S20) the speed hypothesis of the selected model value as the relative speed of the object. Computer program product with program code for performing the steps of the method according to Claim 12 when the program code is executed on a computer.

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