Radar unit for determining the position and / or speed of an object in road traffic

Abstract

Radar unit, in particular vehicle radar unit, for determining the position, in particular direction and / or distance, and / or speed of an object (1) in road traffic, comprising an antenna unit (3) with several antenna elements (4-10), wherein the antenna elements (4-10) are arranged in an irregular pattern, wherein output signals (11) can be emitted using the irregularly arranged antenna elements (4-10) and wherein reflection signals (12) can be detected using the irregularly arranged antenna elements (4-10), and comprising a computing unit (17) which is designed and / or configured to evaluate the detected reflection signals (12) to determine the position and / or speed of the object (1) by means of a non-regular Fourier transform, which processes the signals, in particular the detected reflection signals (12),can be evaluated from the antenna elements (4 - 10) arranged in an irregular pattern.

Description

The present invention relates to a radar unit, in particular a vehicle radar unit, for determining a position, in particular direction and / or distance, and / or a speed of an object in road traffic, having an antenna unit having a plurality of antenna elements, wherein the antenna elements are arranged in an irregular pattern, in which output signals can be transmitted with the aid of the irregularly arranged antenna elements, in which reflection signals can be detected with the aid of the irregularly arranged antenna elements, and having a computing unit which is designed and / or configured such that said computing unit can evaluate the detected reflection signals for determining the position and / or the speed of the object by means of a non-regular Fourier transformation, which can evaluate the signals from the antenna elements arranged in the spatially irregular pattern.Radar systems are known which have a plurality of antenna elements with which signals are transmitted and received. However, the number of antenna elements is quite high.Modern driver assistance systems (ADAS="advanced driver-assistance systems") are intended to improve the safety of the driver and to enable autonomous driving. Ultimately, such systems are aimed at enabling autonomous driving. The most important sensor technologies include ultrasound, lidar, cameras and radar. Lidar and cameras provide high resolution images, but have problems in adverse weather conditions, while radar is more robust, but has lower image quality due to the low angular resolution. To increase the feasibility of radar systems for autonomous driving, large physical apertures are needed, which presents a challenge in increasing the aperture of radar arrays.A typical frequency modulated continuous wave radar (FMCW) achieves high angular resolution with a large aperture. Antenna elements of the radar system or radar unit normally form uniform linear arrays (ULAs) separated by half the wavelength, but this results in arrays with hundreds of antenna elements.Reducing the number of elements without changing the aperture results in sparse arrays. The design of such arrays has gained attention because the antenna elements are strategicly positioned to avoid ambiguous detection.It is an object of the invention to reduce the number of antenna elements in a radar system, wherein an object in road traffic can furthermore be reliably detected.The object is achieved by a radar unit, a vehicle, a computer program and a computer-readable storage medium having the features of the independent claims.A radar unit, in particular a vehicle radar unit, for determining a position and / or a speed of an object in road traffic by means of a radar unit in a vehicle is proposed. The radar unit may also be a vehicle radar unit. The position of the object can be, for example, a direction and / or distance. Direction and / or distance can be related here with respect to the radar unit or the vehicle. The direction means, for example, that it is possible to establish whether the object is located in front of the vehicle or to the left or right of the vehicle. The distance is also measured or determined to the radar unit and thus to the vehicle. By determining the position and / or a speed of an object in road traffic, driving safety is increased and accidents are avoided. The method described here can thus be used in driving assistance systems. The objects can also be other road users, such as other cars, trucks, bicycles, pedestrians, or solid objects such as trees, poles or columns, etc. The radar unit can be located, for example, in a bumper, in particular in a front and / or rear region of the vehicle, and / or in another vehicle component. The driving assistance systems are also referred to in English as "advanced driver assistance systems" or abbreviated as ADAS.The radar unit comprises an antenna unit having a plurality of antenna elements, the antenna elements being arranged in an irregular pattern. Moreover, the antenna elements are sparsely arranged. That is, there are fewer antenna elements compared to antenna units whose antenna elements are arranged in a regular pattern. Such antenna units are referred to in English as "sparse (antenna) arrays". If the antenna elements are arranged, for example, in a regular pattern, then these are all arranged, for example, at a distance from one another which corresponds to half the wavelength of output signals.Furthermore, output signals are emitted with the aid of the irregularly and / or sparsely arranged antenna elements. The output signals are here electromagnetic waves.In addition, reflection signals are detected with the aid of the irregularly and / or sparsely arranged antenna elements. After the output signals have been transmitted, they strike objects if objects are present. The electromagnetic waves are reflected on the object, and reflection signals are reflected back to the antenna unit. These reflection signals are detected by the antenna elements arranged in the irregular and / or sparse pattern.Furthermore, the radar unit comprises a computing unit which is designed and / or set up such that it can evaluate the detected reflection signals for determining the position and / or the speed of the object by means of a non-regular Fourier transformation. The non-periodic Fourier transform may evaluate the reflection signals detected by the antenna elements arranged in the spatially irregular pattern. The non-regular Fourier transform is also referred to in English as a "non-uniform Fourier transform". With the aid of the non-regular Fourier transformation or a non-regular fast and / or discrete Fourier transformation, a tool is provided which can evaluate the reflection signals at a sufficient speed, wherein the reflection signals have been detected by the antenna elements in the irregular and / or sparse pattern. The non-regular fast and / or discrete Fourier transform is also referred to as nuFFT (non-uniform fast Fourier transform). The position and / or the speed of the object is determined here by means of a corresponding algorithm.An improvement results if an antenna unit is used in which the antenna elements are arranged on grid points of a grid, in particular a two-dimensional grid, wherein some grid points are unoccupied.It is useful if mutually juxtaposed grid points have a spacing λ / 2.It is advantageous if the antenna elements are arranged in a circle around the grid points, wherein the circle amounts to a radius of 5%-20% of λ / 2.It is advantageous if the antenna elements are arranged in such a way that the array or arrangement of antenna elements delivers a unique response and preferably corresponds to or comes close to the grid points, some elements being unoccupied. The pitch is preferably λ / 2.It is advantageous if the antenna elements are arranged in such a way that they provide unambiguous results, in particular after the non-uniform fast Fourier transformation. In this case, no further signal peaks other than those of objects are to be generated.It is advantageous if an antenna unit with a sparse grid is used. In addition, an antenna unit having a sparse distribution of the antenna elements may be used. The antenna elements preferably match a sparsely filled / populated grid.It provides advantages if positions of the antenna elements are stored in a data memory and the positions of the antenna elements are obtained from the data memory for carrying out the non-regular Fourier transformation. Here, the positions of the antenna elements are related with respect to a reference point, for example a center of the antenna unit. The positions of the antenna elements can be used as parameters for the non-regular fast Fourier transformation or the corresponding algorithm. The positions of the antenna elements allow the non-regularity of the antenna elements to take into account the determination of the position and / or the distance of the objects.It is advantageous if the direction, in particular an angle, of the object to the antenna unit is determined with the aid of the non-regular Fourier transformation and the antenna elements arranged in the irregular pattern.It provides advantages if a distance of the object from the antenna unit is determined with the aid of the non-regular Fourier transformation and the antenna elements arranged in the irregular pattern.It is advantageous if a non-regular fast Fourier transformation algorithm is used to determine the position, in particular the direction, and / or the distance of the object.It provides advantages if the antenna elements are operated by means of a MIMO method ("multiple input multiple output").It is useful if an antenna unit with antenna elements arranged in such a way is used that, in the case of a virtual arrangement of the antenna elements, all antenna elements are spaced apart from one another. The antenna elements of the array are arranged so that in the virtual array setting in the multiple input multiple output (MIMO) configuration, the following two points are satisfied: a) the elements fit onto a uniformly spaced pattern (preferably at the distance of λ / 2) and b) two virtual antennas are avoided at the same location (this provides only redundant information to the system). This occurs within the framework of arrays with minimal redundancy. They simultaneously minimize the blurs in the field of view and the redundancies in the information acquired by the array.It is furthermore advantageous if a selected antenna element emits the output signal at one point in time and at least some other, in particular all, antenna elements record the reflection signals.An advantage results if a sequence is carried out in which a selected antenna element transmits the output signal at respective times and at least some other, in particular all, antenna elements detect the reflection signals, wherein at successive times other antenna elements emit the output signals and at least some other, in particular all, antenna elements detect the reflection signals.It is advantageous if the output signals have at least one output pulse, wherein the output pulse is frequency-modulated, so that a frequency of the output pulse, in particular from an initial frequency, preferably linearly, increases by a signal bandwidth (B).According to an advantageous development of the invention, it is useful if the output signals are generated with a frequency between 76 and 81 GHz.It provides advantages if the output signals have a plurality of output pulses. The output pulses are also referred to herein as chirps.It is advantageous if a plurality of product values are formed by multiplication from the respective output signals and the respective reflection signals.According to an advantageous development of the invention, it is useful if the product values are filtered, in particular by means of a low-pass filter, so that filter values are formed.It is advantageous if quadratic terms are neglected in the simplification and / or geometric relationships between the antenna elements are taken into account.It is advantageous if the output signals are continuously transmitted and / or the reflection signals are continuously detected. This is the operating mode of a continuous wave radar or an FMCW radar.An improvement results when the approximations are shifted to a common point in time. The MIMO operating mode and coherence and stationarity of the radar unit enable the time shift to be carried out.It provides advantages if the approximation values x̂mkn(t) are Fourier transformed with respect to time, wherein a fast Fourier transformation is preferably used.It is advantageous if a maximum of X̂mkn[f R] is determined for determining the distance. By the sincfunction indicated above, the maximum is where f Rk= f R applies. The distance can thereby be determined.It is advantageous if the approximation values x̂mkn(t) are Fourier transformed with respect to the location, wherein a fast Fourier transformation is preferably used.It is furthermore advantageous if the approximation values x̂mkn(t) are first Fourier transformed with respect to time and then Fourier transformed with respect to location.It is advantageous if, after the application of the Fourier transformation with respect to time, the non-regular discrete Fourier transformation with respect to the location is applied, withIt is also advantageous if the associated result is output after the determination of a position, in particular direction and / or distance, and / or a speed of an object in road traffic. The result of the determination of the position, the direction, the distance or the distance and / or the speed can be output, for example, in such a way that it is displayed on a display in the vehicle. As a result, the driver of the vehicle receives the feedback about the position and / or the speed of the object and can tune his driving behavior to this. Additionally or alternatively, the result can advantageously also be output to a higher-order vehicle control system. This superordinate vehicle control system can then initiate a braking process, for example, in order to avoid an accident.Furthermore, a computer program is proposed which, when executed by the computing unit, causes the computing unit to execute a method according to one or more method steps of the preceding and / or subsequent description.Furthermore, a computer-readable storage medium comprising a computer program is proposed, wherein the computer program, when executed by means of the computing unit, causes the computing unit to execute a method according to one or more method steps of the preceding and / or subsequent description.The radar unit or a radar system can carry out the method according to one or more method steps of the preceding and / or subsequent description. In particular, the radar unit or the radar system comprises the antenna unit having a plurality of antenna elements, wherein the antenna elements are arranged in an irregular and / or sparse pattern. The radar unit or the radar system further comprises the computing unit, which can execute the method with at least one method step of the preceding and / or subsequent description.It is advantageous if the radar unit comprises a microcontroller. In this case, the microcontroller can be the arithmetic unit. Alternatively, it is advantageous if the computing unit is integrated in the microcontroller. The microcontroller and / or the arithmetic unit of the radar unit can be used to perform the calculations to be carried out for the method quickly and efficiently. In this case, a computer program can be installed and / or arranged on the microcontroller, which computer program causes the microcontroller and / or the arithmetic unit to carry out the method for determining a position, in particular direction and / or distance, and / or a speed of an object in road traffic and / or the calculations required for this purpose. Additionally or alternatively, the microcontroller can be designed, for example by means of a corresponding architecture, in such a way that the microcontroller can carry out the method for determining a position, in particular direction and / or distance, and / or a speed of an object in road traffic and / or the calculations required for this purpose.The microcontroller and / or the arithmetic unit can be designed here as a so-called "system on a chip".The microcontroller and / or the arithmetic unit can thus be used to carry out the method steps explained in the preceding and / or subsequent description. These method steps comprise in particular and at least the actuation of the components in order to generate the output signals with the aid of the antenna unit. The reflection signals can advantageously also be detected with the aid of the antenna unit, and the microcontroller and / or the arithmetic unit can advantageously carry out and / or control the evaluation and / or the processing of the electrical signals based on the reflection signals. In addition, the microcontroller and / or the arithmetic unit can output a result of the position measurement, the distance measurement and / or the speed measurement, which is then displayed, for example, on a vehicle display as position information, distance information and / or speed information, for example, relating to a car driving ahead.Additionally or alternatively, the microcontroller and / or the computing unit can also be connected to a superordinate control system of the vehicle. For example, the microcontroller and / or the arithmetic unit can transmit the result of the position measurement, the distance measurement and / or the speed measurement to the higher-level control system of the vehicle. The superordinate control system can, on the basis of this result, actuate a brake system, for example, and initiate a braking process, in order to avoid a rear-end collision, for example.The microcontroller and / or the computing unit are preferably designed and / or configured in such a way that they can control and / or control the components of the radar unit involved in the method and advantageously also evaluate and / or process the signals. Additionally or alternatively, the microcontroller and / or the arithmetic unit can output the result of the position measurement, the distance measurement and / or the speed measurement and / or transfer it to other components in the vehicle.The microcontroller and / or the arithmetic unit can advantageously be designed as a semiconductor chip and / or as a microprocessor. The microcontroller and / or the arithmetic unit can also be incorporated in an "embedded chip".It is likewise advantageous if the computing unit and / or the microcontroller are connected to the antenna unit. Furthermore, the computing unit and / or the microcontroller can also be connected to the antenna elements. As a result, the computing unit and / or the microcontroller can emit the output signals and obtain the reflection signals for evaluation. In this case, the arithmetic unit and / or the microcontroller can transmit the output signals directly to the antenna unit for transmission. Alternatively, the computing unit and / or the microcontroller can cause a further element of the radar unit, for example the signal generator explained below, to emit the output signals.It is also advantageous if the radar unit comprises a data memory. Data required for the method can be stored in the data memory.Additionally or alternatively, it is advantageous if the radar unit has a signal generator. The signal generator can, for example, receive control signals from the computing unit and / or the microcontroller. The signal generator can then transmit corresponding signals to the antenna unit, which then emits the output signals.Additionally or alternatively, it is advantageous if the radar unit has a multiplier. Signals can be combined and / or processed with one another with the aid of the multiplier in order to obtain processed signals for the method described here.Additionally or alternatively, it is advantageous if the radar unit comprises a low-pass filter. Signals can be filtered with the aid of the low-pass filter.Additionally or alternatively, it is advantageous if the radar unit comprises a switching unit. The switching unit can form a connection between the signal generator and a respective antenna element, so that the signal from the signal generator is guided to a specific antenna element. The switching unit can switch back and forth between the antenna elements. The switching unit may be a demultiplexer, for example.It is furthermore advantageous if the data memory, the signal generator, the multiplier, the low-pass filter and / or the switching unit are integrated in the arithmetic unit and / or in the microcontroller. In this case, at least one of the elements mentioned here can be integrated in the arithmetic unit and / or in the microcontroller. Additionally or alternatively, at least one of the elements mentioned here can also be arranged outside the computing unit and / or the microcontroller. For example, the data memory can be designed as a separate component, for example as a chip.Additionally or alternatively, it is advantageous if the data memory, the signal generator, the multiplier, the low-pass filter and / or the switching unit are connected to the arithmetic unit and / or to the microcontroller. For example, the data memory can be designed as a separate component from the computing unit and / or from the microcontroller. Data connection and / or signal connections can be arranged between the elements mentioned here, so that the elements can communicate with one another and / or exchange data and / or also signals.Furthermore, it is advantageous if the arithmetic unit, the microcontroller, the data memory, the signal generator, the multiplier, the low-pass filter and / or the switching unit are arranged on a printed circuit board. As a result, all elements are connected to one another. Additionally or alternatively, the antenna unit can also be coupled to the printed circuit board. In this case, it is also possible for the antenna unit, for example with a data cable and / or signal cable, to be connected to the printed circuit board, for example via a plug arranged on the printed circuit board.A vehicle having a radar unit is also proposed. The radar unit can be designed according to a feature of the preceding and / or subsequent description. The radar unit can furthermore be designed in such a way, in particular comprise the computing unit, that it can execute at least one method step of the preceding and / or subsequent description.In the vehicle radar system, a so-called linear frequency modulated continuous wave (LFMCW) radar is used in a multiple input multiple output (MIMO) configuration. Here, the signal processing generally performed by beamforming techniques is modeled as a discrete Fourier transform (DFT) term. In the context of far-field approximation, both methods are fundamentally equivalent.The DFT calculation for distance information conjugated to the time variable is a default operation in this environment. However, when this identical process (DFT) is applied to the angle variable, this results in nonlinearity in conjugation between the angles and angular frequencies. Therefore, it is important to ensure accurate sampling of the angular frequency information. For a + / - 90 degree field of view (FOV), a half wavelength spacing between the elements is required. This compliance with the Nyquist criterion guarantees accurate signal sampling and thus prevents the introduction of "ambiguities" during the sampling phase.The angular resolution of the array results from the aperture of the array in conjunction with the wavelength. From a practical point of view, it is often advantageous to combine a large aperture with a sparsely distributed array. However, this results in violation of the Nyquist criterion, which affects the quality of the resulting processing. In most cases, although the DFT may still be calculated because we only operate with phasors or limited terms, the target identification may become ambiguous or even erroneous. Here, the expression array is used for the arrangement of the antenna elements or for the antenna unit.In the case of sparse systems or antenna units, it may be expedient to use the formalism and the techniques of compressed sensing. This approach involves a new series of signal processing and recovery techniques that are anchored in "greedy algorithms" such as orthogonal matching purity (OMP). Another way that should be considered is to ensure well-controlled convergence of the DFT in handling minimum redundancy arrays (MRA). Although this approach results in a higher geometric noise background, strategic antenna positioning can minimize side lobe levels throughout the FOV of interest. This can be achieved through comprehensive system tuning and careful array design techniques.With the introduction of nonlinearity in angular coordinate space and sparse, irregular positioning of the antenna elements for sampling angular frequencies, the problem can be formulated as a non-uniform DFT calculation (NuFT). The NuFT can be calculated more quickly with the aid of an FFT-based method-the NuFFT algorithm. The approach can be extended to 3D imaging by including the elevation angle, whose formulation and processing is similar to the azimuth angle. The FOV is also adapted to the requirements in this case.The NuFFT algorithm may require an oversampling step followed by interpolation in which the signal is aligned to the grid coordinates. This phase is the most resource intensive part of the algorithm in which the signal accuracy can be most adversely affected. To rationalize this step, the array can be designed so that the elements of the sparse array in the virtual environment are directly aligned with the oversampling grid. This grid can be computed during the design phase of the array. This alignment optimizes processing when the NuFFT grid matches the uniform linear array (ULA) grid in the virtual environment. The result is that the NuFFT requires fewer additional points and oversampling is minimized. Depending on the specific constraints and design decisions, oversampling may be increased but limited (e.g., to a lambda / 4 grid spacing, doubling the points used by the NuFFT algorithm). Despite this complexity, this approach still offers significant advantages with respect to the complexity of the Order(V*logV) algorithm and the acceleration associated with FFT-based processing.Finally, the use of a NuFT provides flexibility in handling real radar systems that may have slight registration errors in the positions of the antenna elements. In this phase of signal processing, calibration information can be easily applied to the signal. In such scenarios, it is important to carefully select the interpolation function and method of the NuFFT to match the shape of the radar signal, thus ensuring precise and efficient signal processing.The array is designed to meet requirements for NuFFT processing to enable both an efficient configuration that avoids a large oversampling grid and signal degradation. This makes it possible, after a low formulation outlay, to realize the entire signal processing under the same formalism.A random sparse array is the worst case setting for the application of the NuFFT algorithm. Even if the NuFT is well defined and the arrangement is unique, the processing efficiency cannot be improved significantly by such an arrangement. To be able to apply the NuFFT algorithm, it is usually good to find a grid spacing that accommodates all or most antenna elements. It is often the case that, in the case of a random arrangement, pairs of elements scarcely share a common multiple. A sufficiently dense grid is then provided so that all signals can be interpolated to some of the grid points. In this step, most of the signal is distorted and the accuracy of the signal is lost.Among the many sensors in modern vehicles, automotive radar systems provide high resolution estimates of position and velocity of targets. Moreover, higher angular accuracy can be achieved by using larger radar apertures that efficiently combine multiple transmitters and receivers. Sparse antenna groups, i.e. the sparsely and / or irregularly arranged antenna elements, are intended to offer such a high angular resolution and at the same time to avoid the occurrence of ambiguities which arise as a result of irregular distances between the antenna elements. In such arrays, the computational cost for real-time applications is high. Here, considering the non-uniform structure of the signal under consideration, it is shown that processing methods based on non-uniform Fast Fourier Transformations (NuFFT) can efficiently and accurately estimate the direction of arrival (DOA) of targets.With a multiple input multiple output (MIMO) configuration, large virtual arrays are formed with a smaller number of antenna elements.The fast processing of FMCW radar signals typically includes a Fourier transform (FT) of the digitized mixed signal for each channel. For ULA arrays with a distance of λ / 2, Fourier transforms can also calculate the direction of incidence (DOA) by integration over the virtual array dimension. Multi-dimensional FFT processing strategies are implemented in commercial solutions, but are constrained by sampling topics that require equidistant sampling points and pose a challenge to sparse arrays.More recent methods of non-uniform fast Fourier transformation or non-regular, in particular fast, Fourier transformation (NuFFT) make it possible to process data on irregular grids. NuFFT enables direct, efficient multidimensional processing of FMCW radar signals with sparse arrays. NuFFT is of critical importance for the processing of synthetic aperture radar (SAR) data and generates high resolution radar images by efficiently processing non-uniformly sampled data and compensating for Doppler shift, resulting in focused images of targets.Consider a signal transmitted from an antenna element n at a time t so that its waveform is. This waveform undergoes linear frequency modulation (LFM) over time. The frequency starts at a value f 0 and increases linearly to f 0+ B, where B is the signal bandwidth. This frequency modulation forms a pulse or even a chirp of duration T C with a slopeIf a target k is located in front of the radar unit or the radar system, a portion of the transmitted radiation is backscattered to the system. A receiving antenna m receives an echo signal from the target k in the form s mk( t)=A k s n( t-τ). The received signal is the transmitted signal s n( t) which is delayed by τ and subject to attenuation described by the amplitude coefficient A k.The transmitted signal s n( t) and the received echo s mk( t) from the target k are mixed by direct multiplication so that xmkn(t)=s n( t)*s mk( t). Only the low frequency, the so-called beat frequency f IF, is maintained after the high frequency component has been filtered out of xmkn(t). The resulting filtered mixed signal x̂mkn(t)=γ IF cos(2πf IF t+φ IF) is again a periodic function. This filtered mixed signal can also be referred to as a filter value. The beat frequency f IF is the difference between the transmission and the echo frequency. Since the echo delay time τ=2 cR is proportional to the distance R traversed by the wave, f IF= S*τ results. For automotive applications, the delay is short and therefore the expression for the intermediate frequency phase simplifies to φ IF= 2 πf 0 τ - πSτ 2 ≅ 2πf 0 τ. The amplitude term γ IF takes into account the different losses of the transmitted signal intensity and the radar cross section of the target k at this wavelength. In the following, the delay is written as τmknand the complex amplitude as γ k since the predominant contribution is the target k. In practice, it is common to consider both quadratures of the mixed signal separately so that xmkn(t)=γ k exp(j2πf 0 τmkn)exp(j2πSτmknt).Both terms of the signal depend mainly on the delay time τmkof the propagation between the transmitters, the targets and the receivers. This affects both the intermediate frequency f IF and the constant phase term φ IF. The time delay results from the total propagation distance with the speed c from the transmitting antenna n and the back scattering by a target k to the receiver antenna m, so that the following applies.The positions of the transmitter n and the receiver m are at a distance dx Tn and dx Rm respectively from a center of the array. The distance between antennas m and n and a target k with respect to the center of the array is given by the cosine law and has the following expressions.The summation of both terms yields the total approximate distance between the antennas and the target k, Rmkn=R kn+ R mk= 2 R k- ( dx n+ dx m) sin θ k. If the term for the time delay is simplified to dx RTmn= dx Rm+ dx Tn, the term for the time delay is obtainedThe received signal xmkn(t) has the following approximation expressions: with the wavelength of the radiation. Additional constant phase contributions independent of θ can be accommodated in the complex amplitude γek. Starting from (3) describing the signal expression of a single target k for a given pair n and m of transmitting and receiving antennas, respectively, we can formulate the received signals more predictively in the case of multiple antennas and targets. The present system uses time domain multiplexing (TDM) in which only one antenna is transmitting at a time and all receiver antennas listen simultaneously. This approach allows the use of multiple input multiple output (MIMO) formalism.In the TDM method, the signals are not transmitted simultaneously. However, due to the stationarity of the generated signals, they can be converted to a transmission time for processing.The antenna position coordinates of the simulated sparse array are multiples of λ / 2. according to the MIMO approach, the total signal x mn( t) transmitted by an antenna n and received by an antenna m is collected and transformed into a vector x(t). The signal received by an antenna m is the coherent sum of the echo contributions of all K targets in front of the antenna, so that at a given time t the received signal is the vector x(t)=[x 11( t), x 21( t),..., x (M-1)N( t), x MN( t)] T ∈ C MNx1, where the raised T is the transposition operator. The entire received signal comprises the forward and return signal between all combinations of transmitters and receivers and is transmitted into the signal vector:The scan vector A(θ k) describes the response of the array with respect to the azimuth position of the targets. A complex additive white Gaussian noise vector such that w(t) ∈C MNx1, is added to the signal model. The temporal waveform s(t) is the FMCW mixed echo signal. For a given target k of interest, we can express the departure direction (DoD) a T( θ k) and the arrival direction (DOA) a R( θ k) as follows:They join one another to form the scanning vector A(θ k) = a R( θ k) a T( θ k)T ∈C MNx1, which comprises all combinations of transmitting and receiving antennas and covers the entire virtual antenna area. This vector encodes the topography of the array. The complete sample vector is then as follows:In the following, a received signal vector x(t) is considered as described in equation (4). Since the intermediate frequency signal consists of a sum of sine terms, it is expedient to carry out the Fourier transformation first via the time variable. Numerically, this amounts to performing a fast Fourier transform (FFT) of the temporal data of each virtual array element. The azimuth spectrum with the parameter θ is then estimated for each range bin. This is generally carried out by digital beamforming (DBF). The expression is where R x is the covariance matrix of the signal x(t). Peaks from the resulting scan are sought as potential targets DOA (direction of arrival).In the case of a ULA (uniform linear array), the DOA calculation can be carried out directly by applying the FFT over the dimension of the virtual antenna positions. It is shown that for a sparse array, an equivalent strategy for FMCW radars can be applied by using the NuFFT (non-uniform fast Fourier transform) instead of the regular FFT. Next, the identification of the sources of received signal power (targets) by calculation of the 2D range-azimuth spectral density will be discussed. Considering a 1D time signal y(t) with its Fourier transform Δf(f), the power spectral density (PSD) is the squared modulus of the Fourier transform, S yy( f)=|F(f)| 2, where t and f are conjugate Fourier variables of time and frequency, respectively.The PSD over the time variable is first considered with a single component xmkn(t) of x(t). We also assume that we have a target k and that the noise contributions are negligible. Starting from (3), the frequency f Rk is defined such that,The FT of x̂mkn(t) with parameters f R and t as conjugated Fourier variables is:We restrict the signal to the duration of a chirp (from t0=0 to Tc), i.e. the period where the signal is measured. The calculation of the integral part of (11) yields:The range frequency f R is directly proportional to the range parameter R, and if a frequency f R= f Rk, at which the spectral density of X̂mkn[f R] is maximum, the range R k of a target k is determined.Then, the processing is extended to the azimuth direction θ. The extreme positions of the antennas in the virtual group define the aperture A = max(dx RTmn) - min(dx RTmn). The origin of the array is at its center and Δ = dx RTmn and are defined. For the moment, Δ ∈[-A / s, A / 2] is a continuous variable.The adjusted Fourier transform is applied to equation (13) with Δ and fθ as conjugate parameters.Calculating the integral as before and considering all K goals yields:In practice, the signal points of (16) are recorded for particular discrete values. Specifically, the signal is sampled at equal time intervals Δt by a digitizer so that a certain recorded time is given by t = t0 + l Δt, where l is the sampling number and t0 is the start time. This allows the calculation of the previous Fourier integrals by discrete Fourier transforms (DFT). Knowing f R= f Rk directly indicates the range of the detected target. According to the theory of regular scanning, the radar system has a maximum detection range of m and a range resolution of cm at numerical values such as Δt=10 ns, Tc=33 μs and B=1 GHz.Similarly to the range, the DOA of a target is determined by the determination of fθ=fθk, and it becomes possible to determine the angle parameter associated with the various targets. The radiation over the aperture A is scanned by the various virtual antennas. To obtain high resolution DOA estimates, large arrays are required. It is attractive to scan the signal with strategic positioned antennas. The DOA calculation requires that the estimate of a target at a particular angle be unique over the entire field of view. This can be optimized by minimizing the side lobe levels (SLL) of a sparse array with irregular positioning of the antennas.An array with minimal redundancy is created. It has 59 degrees of freedom and a redundancy value of 1.08. From the calculation of the array factor, it is clear that the detection of a target in front of the radar is unique, although the SLL is higher than a ULA with the same aperture size.The DOA of targets is determined directly by beamforming using equation (8). This DOA estimation method has a quadratic complexity with the number of evaluated azimuth angles. In analogy to the ULA case, it is also possible to calculate the azimuth spectral density from equation (14) with the aid of non-uniform discrete Fourier transformation methods. For a given sparse array with antenna positions dx RTmn NuFFT efficiently calculates p Fourier coefficients fθpthat are distributed within and provided by the following non-uniform DFTΔ mn can correspond to the positions of the antenna elements dx RTmn in this case. The NuFFT algorithm uses the fast Fourier transform (FFT) in its kernel calculation by using an oversampling factor and an interpolation step. The oversampling factor ensures that the non-uniform samples are correctly represented in the frequency domain, while the interpolating step bridges the gap between the non-uniformly distributed points and the oversampled grid required for applying a regular FFT. Thus, the computational complexity of the NuEV order is (V*logV), where V represents the number of Fourier coefficients after oversampling. This complexity is comparable to the standard FFT and makes the NuFFT a computationally efficient method.To illustrate the foregoing discussion, signal data is generated using equation (4) with the exact time delays τ, while processing is performed with the approximation expressions of equation (2). The range FFT is first applied to the time traces, followed by DBF or azimuth NuFFT on the range regions over the virtual array channels.The NuFFT is numerically calculated with a specific library. For the sparse array, the results of non-uniform Fourier processing are similar to those achieved with DBF. Individual targets are well resolved, as are the two extended obstacles. This illustrates the applicability of the non-uniform Fourier transform based processing to the angular resolution of sparse FMCW radar systems. Also, velocity estimation could benefit from the use of non-uniform sampling, as the sampling is not continuous with TDM-MIMO. We assume that the direct use of processing techniques that take into account irregularities in the scan parameters, whether spatially or temporally sparse, is extended to other dimensions to efficiently detect range, velocity (Doppler), azimuth, and elevation by performing a 4D NuNB.Exemplary values are f 0= 70 to 80 GHz, B=1 to 4 GHz, T c= 5 to 75 μs and / or Δt=2 to 20 ns. Advantageous values are f 0= 77 GHz, B=1 GHz, T c= 33 μs and / or Δt=10 ns.With the advent of larger arrays consisting of sparse antennas, radar systems are aiming to simultaneously provide high resolution range, velocity, and angle estimates for potential targets in front of a vehicle. This results in large amounts of data having to be processed to achieve target capture in real time. Efficient processing methods are required for this purpose. This work demonstrates that known azimuth FFT-based processing techniques can be extended to a sparsely and non-uniformly populated field for an FMCW radar system. To this end, the angle FFT is replaced by an angle NuFFT that takes into account the dispersion and irregularity of the array and signal structure. Both range and azimuth processing are then calculated with the same complexity as the regular FFT. In the automotive field, the approach presented could be extended to also improve the Doppler effect processing in MIMO radars.Starting from the MIMO signal model in matrix form, the covariance matrix R x of the signal vector can easily be calculated. It will be used later for a variety of operations. With this approach, the amount of data can be reduced by computing out the time dependency.The covariance matrix is: where σ 2 is the noise power and I 0 is the identification matrix and the unit matrix, respectively. From this we can then calculate the pseudo periodogram as estimated by the digital beamforming approach having an intensity peak when θ = θ k,This method is more general, but slower than the Fourier transform based approach. In beamforming, a good delay is sought (scanned) which causes a peak. The approach is closer to a cross-correlation, while the FFT-based spectral density is an autocorrelation of the signal, which can furthermore be evaluated numerically efficiently.In the following section, using the expression about the NuFT, we briefly review the usual steps performed in applying the NuFFT. Since this is a new numerical approximation method, there are many variants. The usual approach is to regulate the signal to match the conditions to be used with the regular FFT algorithm.The signal model is transcribed using our notations as follows:This gives the following NuFT formulation:Given the non-uniform DFT (NuFT="non-uniform discrete Fourier transform") term according to equation (23), to simplify the term and without loss of generality to the present problem, the range contributions are not taken into account and the signal of interest (for a single target k and a virtual antenna v) can be formulated as y v( t)=exp(-j2πfθkdx v). This results in the following NuFT:Here, X[f p] is the DFT coefficient at the frequency point f p, V is the number of virtual antennas, dx v is the position of the v-th antenna in the virtual antenna grid, f k is the angular frequency of the k-th target, and f p is the frequency point in the DFT.The number of virtual antennas V is obtained from the product V=N×M of the number of transmitter antennas and receiver antennas. To calculate the NuFFT along the array aperture direction, it is important that it be scanned along the 1D aperture. As described by the signal model according to equation (3), in the far field the phase effect of the position of transmitter antenna and receiver antenna can be combined into a single variable dx v. This is advantageous because it can reduce the calculation along the aperture (to obtain the DOA) to a single variable instead of the two positions of transmitter and receiver.For a MIMO system and in the far field, the virtual array or antenna array or antenna grid is formed by considering all possible pairs of transmitting and receiving antennas. If there are M transmit antennas and N receive antennas, a virtual array of M×N elements results. Since the information of all antenna combinations is used, this larger virtual array or antenna grid can provide better resolution and greater coverage compared to a physical array with the same number of elements.In the signal model according to equation (3), this amounts to the factorization of the angle contributions with factor dx RTmn= dx Rm+ dx Tn, the virtual array coordinate, which is parameterized by the number of transmitters n and receivers m. The signal model is then RTmn. using the virtual field coordinate dx. This allows extension of regular radar processing techniques for MIMO arrays.For the NuFFT algorithm, the following elements may be provided as input (in a 1D formulation):Non-uniform data points y v, for v=1, 2,..., V.Corresponding non-uniform locations dx v, for v=1, 2,..., V.desired Fourier frequencies f p(k), for k=1, 2,..., K.A first step of the algorithm is rasterization. This step is essentially an interpolation process. The rastered data Y p serves as an approximation of the original signal at the newly defined raster points. We map our non-uniform data to a uniform grid. For each non-uniform data point y v at location dx v we calculate its contribution to the adjacent grid points. The rastered data Y p is calculated as follows: where the offset function and R is the oversampling factor. The grid kernel φ(u) using a Kaiser-Bessel function is given by: where W is the kernel width and I 0 is the modified Bessel function of the first type.The Kaiser-Bessel function is generally used as a grid kernel because of its advantageous properties.Characteristics in Preserving Signal Integrity during Redistribution.Next, and because the rastered data is evenly distributed, we perform a standard fast Fourier transform (FFT) on the rastered data. We form the grating index p to the Fourier frequency index k by finally correcting the convolution with the Fourier transform of the grating kernel.In this step, since the raster function refers to the signal during the raster process, the Fourier transformed data is de-related by being divided by the Fourier transformed raster function, G(f p(k)). We perform deconvolution by dividing the FFT result by the Fourier transform of the grid kernel G(f p(k)) : where G(f p(k)) is the Fourier transform of the grid kernel and is given by: for |f p(k)| ≤ W / 2, and otherwise 0.The corrected Fourier transform X k is a numerical estimate of the original signal data at the desired Fourier frequencies f p(k), for k = 1, 2,..., K.A short list of the various symbols and their meaning:y v: Non-uniform data points.dx v: non uniform locations corresponding to yv.f p(k): desired Fourier frequencies.Y p: Rastered data.A p(k): FFT of the rastered data.X k: Corrected Fourier Transform, the final result.u vp: Offset function.R: oversampling factor.φ(u): Gridding kernel function.G (f p(k)): Fourier Transform of the Kernel.W: half the width of the screening core in the frequency range.In the following, a linear frequency modulation for so-called LFMCW systems (LFMCW=linear frequency modulated continious wave) is explained. This is a linear modulation of the frequency and a continuous wave operating mode. The signal is a sequence of frequency chirps. The linear frequency modulation (chirp) has the following form: f(t)=f 0+ St, where f 0 is the carrier frequency, S=B / T c is the modulation rate and t is the time variable.The phase of the signal of the transmitting antenna n or of a transmitting antenna element n is the time integral of the frequencyIt follows that the transmitted and received signals are as follows:The received signal x mk( t) is delayed by the flight time τ mk between the individual targets and the receiver. The index n stands for a transmitting antenna element, namely the nth transmitting antenna element. The index m stands for a receiving antenna element, namely the m-th receiving antenna element. The index k represents an object.The received signal is directly multiplied with the transmitted signal to mix or dechirp the obtained signal. The result is a mixed signal with two contributions at high and low frequencies. The high-frequency contribution is then filtered out, so that only the low beat frequency of the signal, i.e. the frequency difference between the two signals, is retained.The quadratic term in τ mk can be neglected because the delay τ mk in the far field of the radar system makes no substantial contribution or because τ mk is short. This is followed by,In this section, 3D imaging with the radar system will be described. In addition to the range and azimuth, the elevation information is considered. The elevation is analogous to the azimuth and functions similarly in a sparse array. Both dimensions are orthogonal and hence terms and contributions have similar terms (with respectively own variables). The field of view with respect to elevation is also generally much smaller.The 3D spectral density taking into account the elevation at the angular frequency fφand in conjunction with the contributions of targets in fφkand across an aperture or aperture B is:We indicate that for a full 3D description of the present signal DFT, it may be necessary to introduce the two electrical angles depending on the usual spherical coordinates and define the two independent frequencies fθand fφ, as well as the expressions given below, in order to obtain the representation with a 2D sparse antenna array.As a rule, a signal model can be assumed which includes the range R k, the azimuth θ k and the elevation φ k with respect to the target k and which is as follows:The virtual array is extended in 2D in the plane perpendicular to the propagation of the radiation. Here, the coordinates of the virtual group may be indexed by two variables, one for the horizontal coordinates of the antenna elements dx RTmn= dx Rm+ dx Tn and the other for the vertical coordinates dy RTmn= dy Rm+ dy Tn. Then we introduce a variable change for the angular coordinates so that they become independent for the two orthogonal directions. We define p k= sin(θ k) cos(φ k) and q k= sin(φ k). With this change, the signal model (with dx RTmn= dx and dy RTmn= dy) is:With this equation, the variables associated with both angular directions are separated, and the same scheme as described above using the NuFFT is applicable to the conjugate variables dx and p_k and the conjugate variables dy and q k.The inverse transformation to restore θ k and φ k is also performed directly from the knowledge of p k and q k. We have φ k= arcsin(q k) and this allows the use of sparse 2D arrays with the NuFFT processing described above for the 1D case and the performance of 3D static case imaging and 4D dynamic case imaging with range, doppler velocity, azimuth and elevation.Finally, the processing presented herein is fully compatible with sparse array 4D imaging. The time component of the signal model can be supplemented by the contribution of the Doppler velocity phase. The signal model then becomes xmkn(t)= x̂mkn(t)ej2π Δf t, where the frequency shift resulting from the radial velocity is. In most radar systems, the signal is sampled by the digitizer at regular intervals. The range and the Doppler velocity both depend on the time variable t and can be processed with a regular common 2D FFT for the fast (range) and the slow (Doppler velocity) contribution of the signal. We can also remember that the regular FFT is a boundary case of the NuFFT with regular sample spacings. This allows the radar system to operate even in irregular time samples by using a 2D-NuFFT for the time variable.Finally, the proposed processing formalism may include 4D processing (azimuth, elevation, range, velocity) with a sparse array and potentially irregular time domain samples in a single formalism using a 4D NuFFT. In the usual case of regular sampling of the signal by the detection system, the NuFFT is reduced to the regular FFT.Further advantages of the invention are described in the following exemplary embodiments. The following are shown: FIG. 1 shows a schematic view of a radar unit for determining a position and / or a speed of an object, FIG. 2 shows a section from the signal generation, the signal detection and the evaluation, and FIG. 3 is a frequency-time diagram of the output signal and the reflection signal.FIG. 1 shows a schematic view of a radar unit 2 for determining a position and / or a speed of an object 1. the object 1 is, for example, a vehicle, a pedestrian, a bicycle, a tree or a column. The object 1 can be detected with the aid of the radar unit 2. This is used for driving assistance systems in order to make road traffic more safe. In particular, accidents can be avoided or prevented.The radar unit 2 is furthermore arranged on and / or in a vehicle. The radar unit 2, or also called radar system, comprises a computing unit 17 and / or a data memory 18. the computing unit 17 can execute the method described here and data required for this purpose, such as a program and / or the positions of antenna elements 4- 10, can be stored in the data memory 18.The radar unit 2 further comprises an antenna unit 3 comprising a plurality of antenna elements 4-10. The antenna elements 4-10 are arranged in an irregular and / or sparse pattern. However, the pattern is not random. Rather, the antenna elements 4- 10 are arranged in such a way that the signals detected therewith can be evaluated using the method described here, in particular by means of non-uniform fast Fourier transformation.By means of the antenna elements 4-10 arranged in the irregular pattern, output signals 11 can be transmitted. These output signals 11 strike the object 1 and are reflected by the latter. As reflection signals 12, they are fed back to the radar unit 2 and are detected by the antenna elements 4-10 arranged in an irregular pattern. The antenna elements 4-10 can thus be operated as transmitting and receiving antennas.According to the antenna unit 3 shown, it also comprises unoccupied antenna positions. In an antenna unit 3 having antenna elements 4-10 in a regular pattern, all antenna positions are occupied. These can then have a spacing of λ / 2, where λ is the wavelength of the signals 11, 12. Such antenna units 3 are also referred to as ULAs, which means uniform linear arrays.In the method described here, in particular a computer-implemented method, however, an antenna unit 3 is used, wherein the antenna elements 4- 10 are arranged in an irregular pattern. The antenna elements 4- 10 are arranged here in such a way that in a virtual arrangement of the antenna elements 4- 10, in particular in a MIMO (multiple input multiple output) operation, ambiguity in the detection of the object 1 is prevented. In some scenarios, two objects 1 may be detected in a random pattern after the evaluation, even though only one object 1 is present. In the method described here, so-called sparse (antenna) arrays are used.Furthermore, an unoccupied antenna position 13 is shown here. Due to the unoccupied antenna positions 13 (the antenna unit 3 has a plurality of unoccupied antenna positions 13), an irregular pattern of antenna elements is formed. Additionally or alternatively, the antenna elements 4- 10 are hereby sparsely arranged. As a result, fewer antenna elements 4- 10 are required in comparison with ULAs (uniform linear arrays).To determine the position and / or the speed of the object 1, a non-regular Fourier transformation, in particular a non-regular discrete Fourier transformation and / or a non-regular fast Fourier transformation algorithm, is carried out. This method can evaluate the signals, in particular the detected reflection signals 12, which are detected by the antenna elements 4- 10 arranged in the irregular pattern.An angle 14 can be determined as the position of the object 1, wherein the angle is also designated as θ in the preceding description. The angle 14 or θ is measured here with respect to a center line 16 of the radar unit 2 and / or of the antenna unit 3. If the radar unit 2 is arranged, for example, in a front bumper on a car, the object 1 is located to the right in front of the car.Additionally or alternatively, a distance 15 from the object 1 can also be determined with the method described here. The distance 15 is also denoted by R in the present description. The distance 15 or R is measured here between the object 1 and the intersection point between the center line 16 and the radar unit 2 and / or antenna unit 3.FIG. 2 shows a section relating to the transmission, the reception of the signals and the evaluation of the signals, in particular of the reflection signals. The output signals 11 are generated with the aid of a signal generator 19, which are emitted by the antenna elements 4-10. In this case, the signal generator 19 does not generate the output signals 11 directly, but instead generates electrical signals corresponding thereto, which are converted by the antenna elements 4- 10 into the output signals 11. The signal generator 19 can be connected to the computing unit 17 by a connection not shown here. As a result, the computing unit 17 can transmit control commands to the signal generator, so that the signal generator can cause the antenna elements 4- 10 to emit the output signals 11.Furthermore, a switching unit 22 is shown here, which forwards the signals coming from the signal generator 19 to the corresponding antenna elements 4- 10. The switching unit 22 can form a connection to one antenna element 4- 10 in each case, so that the signal from the signal generator 19 can be conducted to the corresponding antenna element 4- 10. The switching unit 22 can switch back and forth between the antenna elements 4- 10. The switching unit 22 may be, for example, a demultiplexer.At the object 1, which is a car here, they are reflected and pass back as reflection signals 12 and are detected again by the antenna elements 4- 10. As electrical signals, the output signals 11 and the reflection signals 12 have the forms s n( t) and s m( t) as shown in FIG. 2. The antenna elements 4- 10 convert electrical signals into the output signals 11. In addition, the antenna elements 4-10 convert the reflection signals 12 into corresponding electrical signals. These two signals are supplied to a multiplier 20 which multiplies the two signals s n( t) and s m( t) representing the output signals 11 and the reflection signals 12. The index n stands for an output signal 11 and the index m stands for a reflection signal 12.The signals s n( t)*s m( t)=x mn( t) multiplied by one another are filtered with the aid of a low-pass filter 21. The arithmetic unit 17 then follows, which executes the further method. Alternatively, the multiplier 20 and / or the low-pass filter 21 and / or the signal generator 19 can also be integrated in the arithmetic unit 17. Furthermore, a connection, for example for data exchange, can also be present between the arithmetic unit 17 and the multiplier 20, the low-pass filter 21, the signal generator 19, the switching unit 22 and / or the data memory 18, not shown here.The arithmetic unit 17 can also be designed as a microcontroller or as a microprocessor. The arithmetic unit 17 can also be integrated in the microcontroller or in the microprocessor. The elements shown here can be connected to one another by means of data connections and / or signal connections. Additionally or alternatively, at least some of the elements shown here can be integrated in the computing unit 17 and / or in the microcontroller.At least some of the elements shown here can, however, also be arranged outside the computing unit 17 and / or the microcontroller. For example, the data memory 18 can be arranged outside and / or can be embodied as a separate chip.Furthermore, the elements mentioned and shown here can be arranged on a printed circuit board. The antenna unit 3 and / or the antenna elements 4- 10 can likewise be arranged on the printed circuit board. Alternatively, the antenna unit 3 and / or the antenna elements 4- 10 can also be connected to the circuit board by a data connection and / or signal connection, for example in the form of a cable.FIG. 3 shows a frequency-time diagram of the output signal 11 and the reflection signal 12. The pulse is defined as increasing in frequency from f o to f 0+ B, as shown herein. After the maximum frequency f 0+ B is reached, the output signal 11 can begin again at f 0. Since the reflection signal 12 is based on the output signal 11, the reflection signal 12 has substantially the same shape. The output signal 11 and reflection signal 12 shown here are also referred to as chirp, as is also partially made in the preceding description. The output signal 11 and the reflection signal 12 have a time duration T C here. Here, τ denotes the time until the reflection signal 12 is detected again after the emission of the output signal 11. At c of the speed of light, a compound for removal 15 or R is produced.List of reference characters1 Object 2 Radar unit 3 Antenna unit 4 First antenna element 5 Second antenna element 6 Third antenna element 7 Fourth antenna element 8 Fifth antenna element 9 Sixth antenna element 10 Seventh antenna element 11 Output signals 12 Reflection signal 13 Unoccupied antenna position 14, θ Angle 15, R Distance 16 Center line 17 Computing unit 18 Data memory 19 Signal generator 20 Multiplier 21 Low-pass filter 22 Switching unit

Claims

Radar unit, in particular a vehicle radar unit, for determining a position, in particular direction and / or distance, and / or a speed of an object (1) in road traffic, having an antenna unit (3) having a plurality of antenna elements (4-10), wherein the antenna elements (4-10) are arranged in an irregular pattern, wherein output signals (11) can be emitted with the aid of the irregularly arranged antenna elements (4-10), and wherein reflection signals (12) can be detected with the aid of the irregularly arranged antenna elements (4-10), and having a computing unit (17) which is designed and / or configured such that said computing unit can evaluate the detected reflection signals (12) for determining the position and / or the speed of the object (1) by means of a non-regular Fourier transformation which evaluates the signals, in particular the detected reflection signals (12), from the antenna elements (4-10) arranged in the irregular pattern can be evaluated.Radar unit according to the preceding claim, characterized in that the antenna elements (4-10) are arranged on grid points of a grid, in particular a two-dimensional grid, some grid points being unoccupied.Radar unit according to one or more of the preceding claims, characterized in that grating points arranged next to one another have a spacing λ / 2.Radar unit according to one or more of the preceding claims, characterized in that the antenna elements (4-10) are arranged in a circle around the grid points, wherein the circle amounts to a radius of 5% - 20% of λ / 2.Radar unit according to one or more of the preceding claims, characterized in that the antenna unit (3) has a sparse grating.Radar unit according to one or more of the preceding claims, characterized in that positions of the antenna elements (4-10) are stored in a data memory (18), and the positions of the antenna elements (4-10) can be obtained from the data memory (18) for carrying out the non-regular Fourier transformation.Radar unit according to one or more of the preceding claims, characterized in that the computing unit (17) is designed and / or set up in such a way that it can determine the direction, in particular an angle (14; θ), of the object (1) to the antenna unit (3) with the aid of the non-regular Fourier transformation and the antenna elements (4-10) arranged in the irregular pattern.Radar unit according to one or more of the preceding claims, characterized in that the computing unit (17) is designed and / or set up in such a way that it can determine a distance (15; R) of the object (1) from the antenna unit (3) with the aid of the non-regular Fourier transformation and the antenna elements arranged in the irregular pattern.Radar unit according to one or more of the preceding claims, characterized in that the computing unit (17) is designed and / or set up in such a way that it can use a non-regular fast Fourier transformation algorithm for determining the position, in particular the direction, and / or the distance (15; R) of the object (1).Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) is designed and / or set up in such a way that it can operate the antenna elements (4-10) by means of a MIMO method.Radar unit according to one or more of the preceding claims, characterized in that the antenna elements (4-10) are arranged in such a way that, in the case of a virtual arrangement of the antenna elements (4-10), all the antenna elements (4-10) are spaced apart from one another.Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) is designed and / or set up in such a way that a selected antenna element (4-10) can emit the output signal (11) at one point in time and at least some other, in particular all, antenna elements (4-10) can record the reflection signals (12).Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) is designed and / or configured such that it can carry out a sequence in which a selected antenna element (4-10) can each transmit the output signal (11) at respective times and at least some other, in particular all, antenna elements (4-10) can record the reflection signals (12), wherein other antenna elements (4-10) can each transmit the output signals (11) at successive times and at least some other, in particular all, antenna elements (4-10) can record the reflection signals (12).Radar unit according to one or more of the preceding claims, characterized in that the radar unit (2) and / or the arithmetic unit (17) is designed and / or set up in such a way that the output signals (11) have at least one output pulse, wherein the output pulse is frequency-modulated, such that a frequency of the output pulse rises, in particular from an initial frequency, preferably linearly, by a signal bandwidth (B).Radar unit according to one or more of the preceding claims, characterized in that the radar unit (2) and / or the arithmetic unit (17) is designed and / or set up in such a way that output signals (11) having a frequency between 76 and 81 GHz can be generated.Radar unit according to one or more of the preceding claims, characterized in that the radar unit (2) and / or the arithmetic unit (17) is designed and / or set up in such a way that the output signals (11) have a plurality of output pulses.Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) is designed and / or set up in such a way that it can form a plurality of product values xmkn(t) by multiplication from the respective output signals s n( t) and the respective reflection signals s mk( t).Radar unit according to one or more of the preceding claims, characterized in that the product values xmkn(t), in particular by means of a low-pass filter (21), can be filtered, so that filter values x≅mkn(t) can be formed.Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) is designed and / or set up in such a way that it can simplify the filter values x≅mkn(t), so that approximation values x̂mkn(t) can be formed.Radar unit according to one or more of the preceding claims, characterized in that the computing unit (17) is designed and / or configured such that, in the simplification, it can disregard quadratic terms in order preferably to simplify φ IF of the filter values x≅mkn(t), and / or can take account of geometric relationships between the antenna elements (4-10).Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) is designed and / or set up in such a way that it can shift the approximation values x̂mkn(t) to a common point in time.Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) is designed and / or set up in such a way that it can Fourier transform the approximation values x̂mkn(t) with respect to time, wherein a fast Fourier transform can preferably be used.Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) is designed and / or set up in such a way that it can determine a maximum of X̂mkn[f R] in order to determine the distance (15; R).Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) is designed and / or set up in such a way that it can Fourier transform the approximation values x̂mkn(t) with respect to the location, wherein a fast Fourier transform can preferably be used.Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) is designed and / or set up in such a way that it can first Fourier transform the approximation values x̂mkn(t) with respect to time and then Fourier transform them with respect to location.Radar unit according to one or more of the preceding claims, characterized in that the computing unit (17) is designed and / or set up in such a way that, after the application of the Fourier transformation with respect to time, the non-regular discrete Fourier transformation with respect to the location can be applied, with X ^ ^ k [f R, f Θ p ] = X ^ k [f R ] ∑ ( m = 1, n = 1 ) ( M, N ) exp ( j 2 π Δ m n ( f Θ p - f Θ k ) ). Radar unit according to one or more of the preceding claims, characterized in that the computing unit (17) is designed and / or set up in such a way that it can output the associated result after the determination of a position, in particular direction and / or distance, and / or a speed of an object (1) in road traffic.Radar unit according to one or more preceding claims, characterized in that the radar unit (2) comprises a microcontroller which is the arithmetic unit (17) or in which the arithmetic unit (17) is integrated.Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) and / or the microcontroller are designed and / or configured in such a way that they can monitor and / or control the radar unit (2), can carry out the determination of the position, in particular direction and / or distance, and / or of the speed of the object (1) in road traffic, can evaluate and / or process the signals occurring in the process and / or can output the associated result or results.Radar unit according to one or more of the preceding claims, characterized in that the arithmetic unit (17) and / or the microcontroller is connected to the antenna unit (3), in particular to the antenna elements (4-10).Radar unit according to one or more of the preceding claims, characterized in that the radar unit (2) comprises a data memory (18), a signal generator (19), a multiplier (20), a low-pass filter (21) and / or a switching unit (22).Radar unit according to one or more of the preceding claims, characterized in that the data memory (18), the signal generator (19), the multiplier (20), the low-pass filter (21) and / or the switching unit (22) are integrated in the arithmetic unit (17) and / or in the microcontroller and / or in that the data memory (18), the signal generator (19), the multiplier (20), the low-pass filter (21) and / or the switching unit (22) are connected to the arithmetic unit (17) and / or to the microcontroller.Radar unit according to one or more of the preceding claims, characterized in that the data memory (18), the signal generator (19), the multiplier (20), the low-pass filter (21), the switching unit (22), the arithmetic unit (17) and / or the microcontroller are arranged on a printed circuit board and / or in that the antenna unit (3) is arranged on the printed circuit board or is coupled to the printed circuit board, in particular by means of a plug arranged on the printed circuit board.Vehicle having a radar unit (2) which is designed according to one or more of the preceding claims.Computer program which, when executed by a computing unit (17), causes the latter to carry out a determination of a position, in particular direction and / or distance, and / or a speed of an object (1) in road traffic by means of a radar unit (2) in a vehicle, wherein the radar unit (2) is designed according to one or more of the preceding claims.Computer-readable storage medium comprising a computer program, wherein the computer program, when executed by means of a computing unit (17), causes the latter to carry out a determination of a position, in particular direction and / or distance, and / or a speed of an object (1) in road traffic by means of a radar unit (2) in a vehicle, wherein the radar unit (2) is designed according to one or more of the preceding claims.

Images