Patent Description:
Driver assistance systems and autonomous driving rely on a reliable perception of the environment of a vehicle. If objects in the environment of the vehicle are detected, angles of these objects with respect to the host vehicle, i.e. azimuth and elevation angles with respect to a longitudinal axis of the vehicle, are often important parameters for a proper performance of assistant systems. For autonomous driving, a reliable and precise angle determination is even essential.

In order to determine azimuth and/or elevation angles of objects within the environment of the vehicle, Lidar systems may be used. Lidar systems provide a high angular resolution and accuracy since they scan the instrumental field of view of the system with a sharp beam. However, Lidar systems are expensive, e.g. in comparison to radar systems. Therefore, it is desirable to perform the angle determination of objects in the environment of the host vehicle based on radar systems only without the need for an expensive Lidar system.

Angle estimation based on radar systems, however, is a very important process which determines the system performance. Existing methods for angle estimation based on radar systems are e.g. Fourier transform techniques or an iterative adaptive approach (IAA), amongst others. For improving the angular resolution, however, the cost for the required radar system may strongly increase, since a higher number of antennas and therefore a higher package size are required. Moreover, an increased package size for a radar system may prevent the installation of such a system in certain vehicles, e.g. in the region of the bumper. In addition, approaches like IAA require a high computational effort.

Artefacts of the used antenna configuration, the vehicle integration and the signal processing cause a broadened response of the "true" angle in angular responses of signals reflected by the environment of the vehicle, and additionally unwanted sidelobes. That is, there might be some ambiguity regarding the correct determination of the angle and a limited resolution for separating multiple target objects when using the known technologies. Similar issues may occur in Doppler processing containing a broadened response and sidelobe problems. However, these effects are different from those occurring during antenna processing so that they might compensate each other.

<CIT> discloses a method and a device for estimating an angle of a target object with respect to a host vehicle by using a radar system of the host vehicle. The radar system includes at least one radar transmit element adapted to send a radar signal towards the target object, and a plurality of antenna receiver elements, wherein each antenna receiver element is adapted to receive radar signals reflected by the target object. A transformation of the reflected signals is calculated, and a result of the transformation depends on a range with respect to the host vehicle. For each of a set of range bins provided by the transformation, a beam vector is generated for determining the angle of the target object.

<NPL>, discloses a method and a device for determining a target angular position via a high frequency radar system by computing a set of reference vectors and by applying a correlation of the reference vectors with a vector related to signals of apparent targets.

Accordingly, there is a need to provide a method and a device which are able to accurately determine an angle of a target object with respect to a host vehicle and to resolve multiple target objects by using an inexpensive radar system.

The present disclosure provides a computer implemented method, a computer system and a non-transitory computer readable medium according to the independent claims. Embodiments are given in the subclaims, the description and the drawings.

In one aspect, the present disclosure is directed at a computer implemented method for estimating an angle of a target object with respect to a host vehicle by using a radar system of the host vehicle. The radar system includes at least one radar transmit element adapted to send a radar signal towards the target object, and a plurality of antenna receiver elements, or a plurality of radar transmit elements and at least one antenna receiver element, each antenna receiver element being adapted to receive radar signals reflected by the target object. According to the method, a transformation of the reflected signals is calculated, wherein a result of the transformation depends on a range with respect to the host vehicle via a processing unit of the host vehicle. A long beam vector is generated for each of a set of range bins provided by the transformation via the processing unit by rearranging the result of the transformation such that the respective long beam vector comprises elements of the transformation from all receiver elements for the respective range bin. Via the processing unit, a reference vector is calculated for each of the set of range bins based on a signal model which depends on the motion of the target object relative to the radar system and which is parameterized regarding the angle of the target object. The long beam vector and the reference vector are correlated via the processing unit for a predefined range of angles. Finally, the angle of the target object is determined based on the correlation result via the processing unit.

The angle with respect to the host vehicle may be defined with respect to a longitudinal axis of the host vehicle, i.e. with respect to a driving direction of the host vehicle if a steering angle is zero. Furthermore, the angle may be an azimuth angle defined in a plane parallel to the ground on which the vehicle is currently driving, wherein an origin of a coordinate system may be located at the antenna receiver elements of the radar system in order to define the azimuth angle. A vehicle coordinate system may also be used. Additionally or alternatively, an elevation angle may be considered which is defined in a plane perpendicular to the plane in which the azimuth angle is defined and with respect to the same origin of the coordinate system. For the estimation of the azimuth and/or elevation angles, the transmit and receive antennas may form a virtual array which extends in the azimuth and/or elevation plane and whose elements are not located at identical azimuth and/or elevation angles.

Information regarding the relative motion may include a range rate of the target object, i.e. a temporal change of the distance between the target object and the host vehicle. Antennas for transmitting and receiving radar signals may include a plurality of physically separated antenna devices and/or a virtual plurality of antennas which may be provided by a single physical device and which may be separated virtually by mechanical and/or electronic technologies. The number of transmit antennas and the number receiver antennas has to be selected such that the product of these numbers is at least two.

The transformation of the reflected signals regarding the range may be a one-dimensional Fourier transform which provides a transformation result as a function of range bins, i.e. discretized range steps. Usually, when performing a Fourier transform of a time dependent signal numerically, this transform provides complex values as a function of discretized frequencies, i.e. frequency bins. However, an alternative to the Fourier transform may be used for the transformation of the reflected signals regarding the range, e.g. other correlation procedures.

For detecting an environment of a host vehicle, the radar signal sent by the radar transmit element may have a frequency modulated continuous wave (FMCW) waveform which is usually referred to as a chirp. That is, the sent radar signal is frequency modulated on a fast time scale t within a so-called chirp period T. The transformation of the reflected signals regarding the range may therefore be performed on this fast time scale providing transformation values depending from discretized range steps or range bins.

Usually, a further Fourier transform regarding a Doppler frequency is performed for the reflected chirp radar signals on a slower time scale which usually results in a so-called range-Doppler spectrum. However, the method according to the disclosure differs from this standard way of processing reflected chirp radar signals in that the first transformation regarding the range is performed only before the further method steps follow. Instead of the second Fourier transform, the long beam vector is generated as a rearrangement of the result of the transformation and includes information over all receiver elements and chirps for the respective range bin.

In addition, the reference vector is calculated based on a signal model, wherein the reference vector includes the same dimension or number of elements as the long beam vector. The correlation of the beam vector and the reference vector is performed by using known correlation procedures, e.g. by calculating an inner product as in the common discrete Fourier transform, as will be described below. The angle of the target object with respect e.g. to the longitudinal axis of the host vehicle, i.e. the azimuth angle and/or the elevation angle, is directly determined based on the correlation since the signal model includes the respective angle as a parameter. For example, the angle may be varied over a predefined angle range in predefined steps, and for each step the respective result may be calculated for the correlation of the long beam vector and the reference vector.

In comparison to the angle estimation known from the background art, i.e. based on Fourier transform techniques or based on an iterative adaptive approach (IAA), the method according to the disclosure provides an angle estimation having suppressed sidelobes and a reduced width of a peak at the angle to be determined. Therefore, ambiguities regarding the angle estimation are strongly reduced by the method according to the disclosure, and in summary, the accuracy of the angle estimation is improved without significantly increasing the computational effort required or the cost for the required hardware. The improved accuracy of the angle estimation also enhances the ability to resolve multiple target objects.

The method according to the disclosure is performed for each range bin separately, i.e. for one range bin after the other. In order to reduce the computational time required, a region of interest for the range bins, i.e. a subset of all available range bins, may be predefined. Accordingly, the method may be performed for the subset of the range bins or for subsets of other parameters, e.g. azimuth angle or elevation angle, only.

The method may comprise one or more of the following features:
The transformation of the reflected signals may include a Fourier transform. The correlation of the long beam vector and the reference vector may include calculating an inner product of the long beam vector and the reference vector. The angle of the target object may be identified by finding at least one maximum of the correlation of the long beam vector and the reference vector.

A region of interest may be defined for the range of angles, and the long beam vector and the reference vector may be correlated for the region of interest only. An additional angle finding procedure may be combined with the correlation of the long beam vector and the reference vector in order to determine the angle. The additional angle finding procedure may be based on an iterative adaptive approach.

The motion of the target object relative to the radar system may be measured by an additional detection unit installed in the host vehicle. Alternatively, information regarding the motion of the target object relative to the radar system may be derived from former measurements which have been performed via the radar system.

According to an embodiment, the transformation of the reflected signals may include a Fourier transform. In this case, the transformation may require a low computational effort.

Furthermore, the correlation of the long beam vector and the reference vector may include calculating an inner product of the long beam vector and the reference vector. This correlation procedure is a straightforward means for performing the correlation and requires a low mathematical and computational effort. For example, for calculating the inner product each element of the long beam vector may be multiplied by the corresponding element of the reference vector, and the correlation result may be simply the sum over all of these multiplications or products.

The angle of the target object may be identified by finding at least one maximum of the correlation of the long beam vector and the reference vector. Since it turned out that the sidelobes in the correlation results as a function of the angle are strongly suppressed and the width of the peaks within the correlation result is reduced, as mentioned above, a straightforward maximum finding procedure may be sufficient in order to determine the proper angle of the target object from the correlation result. This may again reduce the computational requirements of the method.

In addition, a region of interest may be defined for the range of angles, and the long beam vector and the reference vector may be correlated for the region of interest only. As mentioned above, the reference vector is calculated depending from the angle as a parameter, wherein the angle is varied over the predefined angle range, e.g. in steps of one degree. If a special region of interest is known or defined for the angle to be estimated, the angle may be varied over this region of interest only when calculating the reference vector. Therefore, the computational time required for calculating the reference vectors for the different angles may be reduced. The region of interest may be known from measurements provided by further systems of the vehicle or may be predefined based on the construction of the vehicle.

According to a further embodiment, an additional angle finding procedure may be combined with the correlation of the long beam vector and the reference vector in order to determine the angle. In detail, the additional angle finding procedure may be based on an iterative adaptive approach (IAA). It turned out that the method described above may be compatible to be combined with other frequency estimation concepts, e.g. the iterative adaptive approach. It may also be compatible with subsequent estimation processes requiring complex valued responses, e.g. azimuth elevation estimation as a separate process. The additional angle finding procedure may further increase the resolution of the angle estimation by further suppressing sidelobes and reducing the width of peaks in the correlation result depending from the angle as a parameter. The iterative adaptive approach may focus on certain angle ranges and provide lower sidelobes and a lower peak width.

The motion of the target object relative to the radar system may be measured by an additional detection unit installed in the host vehicle. Generally, the method requires an independent determination of the relative motion of the target object. At least one parameter which relates to the relative motion of the target object is necessary for applying the signal model being required for calculating the reference vector. If the relative motion of the target object is measured by an additional detection unit of the vehicle, e.g. as part of a further component of a driver assistant system, the reliability when calculating the reference vector may be improved since the information regarding the relative motion is provided by an independent measurement. On the other hand, if information regarding the relative motion is derived from former measurements of the radar system which is also used by the method, no additional hardware may be required for providing the information regarding the relative motion. In addition, a plurality of relative motions may be considered which may extend a parameter vector of the signal vector. This may lead to an increase in the dimensionality of the response in order to enable subsequent processes which may handle multiple hypotheses.

In another aspect, the present disclosure is directed at a device for estimating an angle of a target object with respect to a host vehicle. The device comprises a radar system which is installed in the host vehicle and which includes at least one radar transmit element adapted to send a radar signal towards the target object, and a plurality of antenna receiver elements, or a plurality of radar transmit elements and at least one antenna receiver element, wherein each antenna receiver element is adapted to receive radar signals reflected by the target object. The device further comprises a processing unit and which is configured to calculate a transformation of the reflected signals, wherein a result of the transformation depends on a range with respect to the host vehicle, to generate a long beam vector for each of a set of range bins provided by the transformation by rearranging the result of the transformation such that the respective long beam vector comprises elements of the transformation from all receiver elements for the respective range bin, to calculate a reference vector for each of the set of range bins based on a signal model which depends on the motion of the target object relative to the radar system and which is parameterized regarding the angle of the target object, to correlate the long beam vector and the reference vector for a predefined range of angles, and to determine the angle of the target object based on the correlation result.

As used herein, the terms processing module and processing unit may refer to, be part of, or include an Application Specific Integrated Circuit (ASIC); an electronic circuit; a combinational logic circuit; a field programmable gate array (FPGA); a processor (shared, dedicated, or group) that executes code; other suitable components that provide the described functionality; or a combination of some or all of the above, such as in a system-on-chip. The term module or unit may include memory (shared, dedicated, or group) that stores code executed by the processor.

In summary, the device according to the disclosure includes a radar system and a processing unit which are configured to perform the steps as described above for the corresponding method. Therefore, the benefits, the advantages and the disclosure as described above for the method are also valid for the device according to the disclosure. The processing unit may be installed in the host vehicle, but as an alternative, it may also by an external unit which may be related e.g. to a cloud system.

The processing unit may further be configured to perform an additional angle finding procedure based on an iterative adaptive approach. The device may further comprise an additional detection unit which is configured to measure the motion of the target object relative to the radar system. Alternatively, the processing unit may be further configured to derive information regarding the motion of the target object relative to the radar system from former measurements which have been performed via the radar system.

In another aspect, the present disclosure is directed at a computer system, said computer system being configured to carry out several or all steps of the computer implemented method described herein.

The computer system may comprise a processing unit, at least one memory unit and at least one non-transitory data storage. The non-transitory data storage and/or the memory unit may comprise a computer program for instructing the computer to perform several or all steps or aspects of the computer implemented method described herein.

The computer readable medium may be configured as: an optical medium, such as a compact disc (CD) or a digital versatile disk (DVD); a magnetic medium, such as a hard disk drive (HDD); a solid state drive (SSD); a read only memory (ROM); a flash memory; or the like.

<FIG> depicts a vehicle-based radar system <NUM>. The system <NUM> includes an antenna array <NUM> that includes at least one transmit element <NUM> and an array of at least two receive elements, also referred to as a plurality of antennas <NUM>. One or more of the receive elements or antennas <NUM> may also be used to both transmit a radar signal <NUM>, and they output a detected signal <NUM> indicative of reflected radar signals <NUM> reflected by a first target object 24A or a second target object 24B in an instrumental field of view of the system <NUM>. The transmit element <NUM> and the plurality of antennas <NUM> are illustrated as distinct elements in this example only to simplify the explanation of the system <NUM>.

The system <NUM> includes a controller or processing unit <NUM> configured to output a transmit signal <NUM> to the transmit element <NUM>, and configured to collect the receive signals <NUM> from each antenna <NUM>, for example a first signal 30A from a first antenna 16A and a second signal 30B from a second antenna 16B. Each of the detected signals <NUM> correspond to the reflected radar signal <NUM> that was detected by one of the plurality of antennas <NUM>. The controller <NUM> includes a processor <NUM> such as a microprocessor, digital signal processor, or other control/signal conditioning circuitry such as analog and/or digital control circuitry including an application specific integrated circuit (ASIC) for processing data. The controller <NUM> also includes memory (not shown), including non-volatile memory, such as electrically erasable programmable read-only memory (EEPROM) for storing one or more routines, thresholds and captured data.

Furthermore, the controller <NUM> includes a receiver <NUM> configured to receive an antenna signal (e.g. the first signal 30A and the second signal 30B) from each antenna (e.g. the first antenna 16A and the second antenna 16B) corresponding to the reflected radar signal <NUM> that was collected from each of the plurality of antennas <NUM>. The controller <NUM> may include a mixer (not shown) and a local oscillator (not shown) in order to demodulate the detected signals <NUM>. The mixer and the local oscillator may be part of the receiver <NUM>.

The transmit element <NUM> radiates or emits the radar signal <NUM> toward the first target object 24A and/or to the second target object 24B in the instrumental field of view <NUM>, and each of the plurality of antennas <NUM> detects a reflected radar signal reflected by the first target object 24A and/or the second target object 24B. Characteristics of the reflected radar signal <NUM> depend on a backscatter property or radar cross section (RCS) of the first target object 24A or the second target object 24B. The characteristics also depend on distance, direction, and relative motion of the first object 24A and/or the second object 24B relative to the antenna array <NUM>, which influences the Doppler shift of the reflected radar signal <NUM>.

The first target object 24A is located at a range or distance r1 with respect to the antenna array <NUM> of the system <NUM> and therefore with respect to a host vehicle (not shown) in which the system <NUM> is installed, whereas the second target object 24B is located at a range or distance r2 with respect to the antenna array <NUM> of the system <NUM>. A relative position difference between the first target object 24A and the second target object 24B is illustrated as Δrx and Δry. In addition, the second target object 24B is located at an azimuth angle θ with respect to a longitudinal axis of the host vehicle or a normal line with respect to the antenna array <NUM>. Since the first object 24A is aligned with this normal line, the azimuth angle is almost zero for the first object 24A and therefore not shown in <FIG>. The focus of the method according to the disclosure is on precisely estimating the azimuth angle θ of objects in the environment of the host vehicle.

<FIG> schematically depicts the frequency of the transmitted radar signal <NUM> and of the reflected radar signal <NUM> over time and the processing of these signals according to the background art. The diagrams of <FIG> have been taken from <NPL>. The transmitted and reflected radar signals <NUM>, <NUM> have a FMCW (frequency modulated continuous wave) waveform which is also referred to as a chirp. That is, both signals include a complex sinusoid for which the frequency linearly increases within a time interval T according to <MAT> wherein B is the signal bandwidth and fc is a carrier frequency. For the carrier frequency, a typical frequency band of <NUM> to <NUM> is used for an automotive radar system like the system <NUM> as shown in <FIG>.

The reflected radar signals <NUM> which are also referred to as echo chirps are a delayed and attenuated copy of the transmitted signal or chirp <NUM>. For a target object 24A, 24B which is located at a range R and moves with a radial speed v, the delay time <NUM> (see <FIG>) is given by <MAT> wherein the time t is running over multiple periods T of the chirp signals <NUM>, <NUM>, and c is the speed of light.

Usually, the reflected radar signal <NUM> is mixed with the transmitted signal <NUM> or transmitted chirp, which results in a complex sinusoid known as a beat signal. The beat signal has a frequency fb = fR + fD, wherein fR = 2RB/(Tc) is the so-called range frequency, and fD = (2v/c) fc is the so-called Doppler frequency.

For processing the beat signal, the time during one period or chirp is usually referred to as the fast time, while the time across multiple periods T or chirps is referred to as the slow time. When the beat signal is sampled, the samples of each chirp or antenna <NUM> is arranged in columns of a matrix, wherein the row indices of the matrix correspond to the fast time and the column indices correspond to the slow time, as shown in <FIG>. Since fD is usually much smaller than fR, fD may be taken as constant within each chirp. Therefore, a Fourier transform is usually applied to the sampled beat signal along the fast time for each antenna or channel <NUM>, which allows to identify the respective range of the target object 24A, 24B with respect to the antenna array <NUM> being used as a reference point at the host vehicle. In detail, the range or distance of the objects 24A, 24B is obtained as <MAT>.

In order to obtain the velocity of the objects 24A, 24B, a second Fourier transform is usually carried out subsequently along the slow time. The application of the first and second Fourier transform is equivalent to a two-dimensional Fourier transform of the beat signal in the fast and slow times, and the result is usually called a range-Doppler spectrum.

According to the background art, an angle estimation may be further performed based on the range-Doppler spectrum. For the angle estimation, an angle is defined with respect to a longitudinal axis of the host vehicle and is an azimuth angle and/or an elevation angle. Furthermore, the angle estimation according to the background art may be based on a further Fourier transform or on an iterative adaptive approach (IAA).

However, such an angle estimation based on the range-Doppler spectrum mostly entails high computational and/or hardware cost. In addition, there might be some ambiguities regarding the angle estimation due to sidelobes which are generated by the respective angle finding procedures. In order to overcome these disadvantages, the method according to the disclosure is based on a different approach which does not rely on the range-Doppler spectrum. After the first Fourier transform as described above over the fast time which is related to the determination of the range, the result of the first Fourier transform is rearranged such that for each range bin (i.e. the discretized range resulting from the first Fourier transform) a vector is generated which runs over all chirps or antenna channels <NUM> (see <FIG>). This vector is called a long beam vector and carries the antenna information together with the Doppler information regarding the velocity of target objects.

The generation of a long beam vector <NUM> for each range bin <NUM> is schematically depicted in <FIG> illustrates again the generation of the range-Doppler spectrum which is shown as a beam vector depending from the respective range bins and Doppler bins, in accordance with <FIG>. The beam vector is based on the result of e.g. a two-dimensional Fourier transform over the fast and slow times performed for the beat signal as described above.

In contrast, <FIG> schematically depicts a corresponding beam vector after the first Fourier transform over the fast time which includes the range bins for the respective chirps or antenna channels <NUM> (see <FIG>). For generating the long beam vector <NUM>, the beam vector elements for all chirps are rearranged one after the other over all chirps in order to generate one vector which is called the long beam vector <NUM> and which is shown schematically in the lower part of <FIG>.

For the angle estimation based on the long beam vector <NUM>, a reference vector <NUM> (see <FIG>) is calculated based on a signal model which considers the motion of the target objects 24A, 24B relative to the radar system <NUM> (i.e. relative to the antennas <NUM> being installed in the vehicle) and which depends on the angle to be determined, i.e. the azimuth angle and/or the elevation angle. The concept is explained in detail for a Uniform Linear Array (ULA) and a linear relative motion of one of the target objects 24A, 24B. For more complex antenna arrangements and a more complex object motion, the signal model may be extended as is known in the background art.

The signal model is based on the following formula: <MAT> wherein T is the slow time represented by a slow time index relative to the first chirp. n is the antenna channel index relative to the first antenna 16A (see <FIG>). ṙ is the range rate of the respective target object 24A, 24B in m/s. α is an electric angle which is defined for an interval from -<NUM> to +<NUM>, wherein α = sinθ and θ is the mechanical angle to be determined in rad, with θ = <NUM> defining boresight. a is a complex amplitude. The respective coefficients k are defined by the following formulas: <MAT> wherein Tchirp is a doppler sampling period in s or chirp period, and TSpace is a spatial sampling period in m which corresponds to the spacing of the antennas <NUM>. The factor of <NUM> which is included in the formulas for the coefficients is due to the two-way propagation of the radar signals, i.e. from the respective antenna <NUM> to one of the target objects 24A, 24B and back (see <FIG>).

The method steps for generating reference vectors depending from the angle θ and correlating the reference vectors with the long beam vector <NUM> are depicted schematically in <FIG>. The angle θ is used as a parameter and is defined for a predetermined angle range. For the present example, the angle range extends from -<NUM>° to +<NUM>°, and the angle θ is varied in steps of one degree. That is, <NUM> reference vectors are generated based on the signal model in order to cover the entire angle range. In order to calculate the respective reference vector <NUM>, the range rate of the target object 24A, 24B has to be given from a further measurement. The relative motion of the target object may be determined via a further measurement device or detection unit installed in the host vehicle or may rely on a former measurement performed by the radar system as shown in <FIG> for which the further Fourier transform based on the slow time is performed in order to determine the velocity.

Based on the given range rate or velocity <NUM> of the respective target object 24A, 24B and based on the pre-set angle θ as a parameter, elements of the respective reference vector <NUM> are calculated which correspond to the respective elements of the long beam vector <NUM>.

For each angle step as shown in <FIG>, the respective reference vector <NUM> is correlated with the long beam vector <NUM>. This correlation is indicated by <NUM> in <FIG>. The correlation is performed by calculating the inner product of the respective reference vector <NUM> with the long beam vector <NUM>, i.e. by multiplying pairs of corresponding elements and summing-up all products of the respective elements. The result of this correlation provides a value for the respective angle or angle bin, i.e. for discretized angle steps which run from -<NUM>° to +<NUM>° for the present example.

The entire result for correlating the long beam vector <NUM> and the reference vectors <NUM> over all angle bins <NUM> is depicted in <FIG>, wherein the angle bins are represented on the x-axis, whereas the correlation result is represented by the y-axis. Regarding <FIG>, it is noted that <NUM> angle bins cover the angle range from -<NUM>° to +<NUM>° to provide a greater angle resolution than for the schematic illustration of <FIG> for which <NUM> steps of one degree have been assumed.

The iteration of the angle θ over the predefined angle range is performed for each range bin <NUM> (see <FIG>) separately. That is, a diagram like <FIG> representing the correlation result for the long beam vector <NUM> and the reference vectors <NUM> could be plotted for each range bin <NUM>. In <FIG>, the angle θ to be determined for the respective range bin <NUM> is given by the maximum <NUM> of the correlation curve which is located at angle bin <NUM> corresponding approximately to boresight, i.e. <NUM> degrees.

In order to reduce the computational time required for performing the method according to the disclosure, respective regions of interest may be predefined for the angle θ and for the range or distance of the target objects 24A, 24B. Such regions of interest may be based on the detection of the target motion being performed by further systems of the host vehicle which also provide e.g. the range rate or velocity <NUM>.

In <FIG> the results of two classical angle finding procedures are shown which are based on the range-Doppler spectrum as described above. Curve <NUM> represents the result of the angle finding via a further Fourier transform, whereas curve <NUM> represents the result of an iterative adaptive approach (IAA) as known in the background art. While one maximum of both curves <NUM>, <NUM> occurs at the correct angle of approximately <NUM> degrees (angle bin <NUM>), both curves include many additional maxima and strong sidelobes which are indicated by <NUM>. This complicates a proper angle estimation based on the result according to the background art as shown in <FIG>, which especially holds true for the angle estimation based on the further Fourier transform. Although the sidelobes <NUM> are reduced for the angle finding via IAA, the curve <NUM> also includes a strong maximum at small angles. Hence, <FIG> demonstrates the ambiguities which may occur if the angle finding procedures according to the background art are applied.

In contrast, <FIG> depicts the result of the correlation of the long beam vector <NUM> with the reference vectors <NUM> over all angle bins. The sidelobes as indicated at <NUM> are strongly suppressed in comparison to <FIG>. In addition, the maximum as shown at <NUM> in <FIG> relies on a peak which has a smaller width, especially in comparison to the result of angle finding by the Fourier transform as shown in <FIG>.

Claim 1:
Computer implemented method for estimating an angle (θ) of a target object (24A, 24B) with respect to a host vehicle by using a radar system (<NUM>) of the host vehicle, wherein the radar system (<NUM>) includes at least one radar transmit element (<NUM>) adapted to send a radar signal (<NUM>) towards the target object (24A, 24B), and a plurality of antenna receiver elements (<NUM>) or a plurality of transmit elements (<NUM>) and at least one antenna receiver element (<NUM>), each antenna receiver element (<NUM>) being adapted to receive radar signals (<NUM>) reflected by the target object (24A, 24B),
the method comprising:
calculating, via a processing unit (<NUM>) of the host vehicle, a transformation of the reflected signals (<NUM>), wherein a result of the transformation depends on a range with respect to the host vehicle,
generating, via the processing unit (<NUM>), a long beam vector (<NUM>) for each of a set of range bins (<NUM>) provided by the transformation by rearranging the result of the transformation such that the respective long beam vector (<NUM>) comprises elements of the transformation from all receiver elements (<NUM>) for the respective range bin (<NUM>),
calculating, via the processing unit(<NUM>), a reference vector (<NUM>) for each of the set of range bins (<NUM>) based on a signal model which depends on a motion of the target object (24A, 24B) relative to the radar system (<NUM>) and which is parameterized regarding the angle (θ) of the target object (24A, 24B),
correlating, via the processing unit (<NUM>), the long beam vector (<NUM>) and the reference vector (<NUM>) for a predefined range of angles (θ), and
determining, via the processing unit (<NUM>), the angle (θ) of the target object (24A, 24B) based on the correlation result.