Method and system for identifying false detections

Abstract

The invention relates to a model-based method for determining false detections during radar detections in radar data, in conjunction with cross paths which arise on account of different transmit and receive angles of paths for a radar target, in which method a radar cube having range-Doppler cells is generated by Fourier transform on the basis of the radar data, wherein first a range and then a Doppler Fourier transform is carried out, such that channel data are thereby available for each range-Doppler cell, wherein false detections are determined via the channel data of a plurality of neighbouring range-Doppler cells, in that multi-dimensional models for multipath propagation spanning said range-Doppler cells are used to determine the detection parameters range, Doppler and angle of the detections, wherein the following models are used as models for multipath propagation: - a multipath model, which comprises a direct path, an indirect path and an associated cross path for a radar target; and / or - a cross path model, which comprises only one cross path for a radar target (and no direct or indirect path); and / or - a plurality of individual target models, which comprise a plurality of direct independent paths or a plurality of independent radar targets.

Description

[0001]202400193 1 Description / Description Method and system for detecting false detections The present invention relates to a method and a system for detecting false detections. Technological background Wireless transmissions via radio waves, such as radar transmissions, are susceptible to propagation effects such as sensor blockage, scattering or multipath. In monostatic radar applications, multipath propagation leads to so-called false positives (false detections), i.e. incorrectly identified targets or detections. In application scenarios of radar in the automotive sector, multipath propagation often occurs on smooth surfaces, such as guardrails. The general propagation paths are shown in Fig. 1, with a total of four different propagation paths being shown and labeled accordingly in the table in Fig. 1.Depending on the detection algorithm of the radar sensor and its resolution, the four different propagation paths within such a multipath scenario can lead to target detection. In particular, propagation via the indirect path and the two cross paths can lead to incorrectly classified targets (i.e., false detections or false positives). Cross paths can also exist in multipath propagation. A cross path has a different propagation path on the outward and return paths. It is therefore essentially a mixture of direct and indirect propagation paths. Typically, there is a first cross path that uses the direct propagation path on the outward path but the indirect propagation path on the return path, and a second cross path that, in the opposite direction, uses the indirect propagation path on the outward path and the direct propagation path on the return path.A cross path is characterized by the fact that the angle of reflection and the angle of incidence of the radar signal are different. State of the Art: DE 102012105582 A1 discloses a method for a radar system that evaluates multiple beams to determine the angular position of objects in at least one coordinate. A high-resolution method for separating multiple reflection points based on a cost function is repeatedly executed. The calculation of the cost function is then split into a part that is independent of the input data and a part that is dependent on the input data. The part that is independent of the input data is determined and stored in advance at predetermined support points for parameters of the reflection points.Furthermore, DE 102016215509 A1 describes a method for operating a radar system in a vehicle, in which a mirror surface is first detected and the minimum distance from an object to the mirror surface is determined, whereby the object is classified as a mirror object if the object and the vehicle are located on different sides of the mirror surface. Furthermore, Engels et al. in Automotive MIMO Radar Angle Estimation in the Presence of Multipath (October 2017; DOI: 10.23919 / EURAD.2017.8249152) describe MIMO schemes used in automotive radar to improve resolution and the signal-to-noise ratio. Practical scenarios that typically require high-resolution angle estimation include horizontal or vertical multipath propagation. In these situations, the standard two-target model can no longer be applied when using MIMO schemes, and model-based angle estimation must be extended.For this purpose, signal models with two targets and with a single target in the presence of multipath propagation are disclosed, wherein a multipath scenario or multipath propagation within a Range / Doppler Internal 202400193 3 cell is defined. In addition, corresponding maximum likelihood estimators (ML - "maximum likelihood") are described. DE 102021211989 B3 discloses a method for associating a detection of a real target detected by a radar sensor with its mirror target based on a detected cross path, in which the angle of incidence and reflection of the cross path, which arises due to a reflection at a mirror surface, as well as its length are determined, wherein based on the angle of incidence and reflection and the length of the cross path, radar detections are grouped by respectively assigning a radar detection to a group of a set of several groups.Furthermore, at least one radar detection of a first group is associated with a radar detection of a second group, wherein the radar detection of the first group is arranged in an angular range around the angle of incidence and the radar detection of the second group is arranged in an angular range around the angle of reflection, and the first group of radar detections has a radial distance from the radar sensor less than the length of the cross path and the second group of radar detections has a radial distance from the radar sensor greater than the length of the cross path, or vice versa, and wherein the sum of the radial distances of the associated radar detections from the radar sensor is substantially equal to twice the length of the cross path. As a result, information can then be provided that the associated radar detections are a real target and an associated mirror target.The values ​​used in DE 102021211989 B3 are based on estimates of detections. Especially in MIMO (Multiple Input Multiple Output) setups, the azimuth estimates are distorted. Furthermore, not all components of the multipath scenario are recognizable, which prevents part of the algorithm from functioning. In automotive scenarios where the target is located at a greater distance, for example, the mirror target may no longer be detected because it is too close to one of the crossing paths and has less power. Internal 202400193 4 Object of the present invention Based on this, the object of the invention is to specify a method for detecting false detections, in which the detection accuracy can be improved and the number of false detections can be reduced. Inventive Solution The above object is achieved by the combination of features of claim 1 and the independent claim.Advantageous embodiments of the invention are claimed in the subclaims. The present invention relates to a (model-based) method for determining false detections in radar detections in radar data, in conjunction with cross paths that arise due to different transmission and reception angles of paths for a radar target. In this method, a radar cube with range Doppler cells is generated from the radar data using Fourier transformation. First, a range and then a Doppler Fourier transformation are performed, so that channel data are available for each range Doppler cell. False detections are determined using the channel data of several neighboring range Doppler cells (neighboring cells). Multidimensional models for multipath propagation that span these range Doppler cells are used to determine the detection parameters range, Doppler, and angle of the detections.Furthermore, the following models are used as models for multipath propagation: - multipath model, which comprises a direct path, an indirect path and an associated cross-path for a radar target; and / or - cross-path model, which only comprises a cross-path for a radar target (and no direct and indirect path); and / or - multiple single-target models, which comprise multiple direct independent paths or multiple independent radar targets. Internal 202400193 5 The present invention enables the reliable detection of a multipath scenario on the basis of raw radar data, wherein increased accuracy of the detected values ​​can be achieved on the basis of physically related models and the number of erroneously detected targets or false detections is reduced.Preferably, the number of detection parameters for the multipath model is reduced so that both the rank and Doppler values ​​of the cross paths correspond to the mean of the corresponding values ​​of the indirect and direct paths. For example, the geometric relationship can be used. The geometric relationship is based on the cross paths in range and Doppler lying between the corresponding values ​​of the direct and mirror target. Pre-filtering can be advantageously performed by using a beamformer to determine at least two detections with a maximum power difference, whereby the range / Doppler values ​​of the two detections must not exceed a threshold in the difference of the respective value, or the difference between range and Doppler of the found detections should be below a certain threshold. Furthermore, the determination of the detection parameters range, Doppler, and angle can be divided into two parts, whereby the angle values ​​of the models are estimated first, and then the range-Doppler values ​​are estimated. The range-Doppler estimation can also be divided into two separate parts.Conveniently, both cross paths can also be represented with a common amplitude. Furthermore, the present invention comprises a system for determining false detections in radar detections in radar data, in conjunction with internal 202400193 6 cross paths that arise due to different transmission and reception angles of paths for a radar target, wherein the system comprises at least one radar sensor for detecting the surroundings of a vehicle and a control unit for processing the information provided by the radar sensor, wherein the control unit is designed to carry out a method according to one of the preceding claims. Description of the invention based on an exemplary embodiment. In Fig.2 shows a simplified schematic representation (of a section) of a radar cube comprising a type of multidimensional data structure in which, for example, the raw radar data can be stored in a spatially discrete and preferably structured manner. This shows the current range-Doppler cell (or the processing cell of interest) as well as the surrounding (eight) neighboring cells, including all channels or channel data for a range-Doppler cell. A key aspect of the present invention is that the crossing paths with other models are differentiated using the channel data (so-called "channel data," which are the received samples for a specific receive / transmit antenna combination after range and Doppler Fast Fourier Transformation (FFT processing)).Assuming that the channel data consists of an area of ​​Nr by Nd processing cells around a particular processing cell, the sampled data for L individual targets can be described as zrd|st:. Equation (1) where ⊗ denotes the Kronecker product and ⋄ the Kathri-Rao product, i.e., a column-wise Kronecker product. The matrices Br and Bd provide the Fourier transform and windowing around the processing cell of interest, while Ar(br), Ad(bd), Aϕ(bϕ) denote the steering matrices in range, Doppler, and azimuth angles, respectively. Each column of the matrices denotes a steering vector per target in its corresponding range. The vectors br, bd, and bϕ have length L and denote the positions of the L targets with respect to range, Doppler, and azimuth values, respectively, and α denotes the corresponding amplitude vector. Furthermore, in equation (1), a virtual array within Aϕ(bϕ) is used according to the monostatic MIMO (multiple-input multiple-output) concept. The noise vector n is circularly symmetric, complex normal, and distributed as zero mean with covariance matrix: G leichung (2) assuming white, circularly symmetric complex normally distributed noise samples with variance σ 2 at the input before FFT processing where INϕ stands for the identity matrix of size Nϕ × Nϕ. A total of 3·L nonlinear parameters must be estimated. Assuming that only the two cross paths within the Nr · Nd processing cells, the channel data zrd|cp can be described by G leichung (3) with the range value br,c, the Doppler value bd,c and the azimuth angles bϕ = [bϕ1, bϕ2]. The control matrix AT,R,ϕ (bϕ) takes into account the different angle of arrival (AoA – “angle of arrival”) and angle of departure (AoD – “angle-of-departure”) by Equation (4) where aT(b) and aR(b) are the steering vectors of the transmit and receive antenna arrays, respectively. Note that if aT(b) and aR(b) are well characterized for the sensor, i.e., can be corrected, a simpler model for AT,R,ϕ (bϕ) can be used as: Equation (5)Internal 202400193 8 where only a single amplitude needs to be used in equation (3). However, a total of four nonlinear parameters (br,c, bd,c, bϕ1, bϕ2) need to be estimated. Assuming that all paths of the multipath scenario are within the Nr · Nd processing cells, e.g., if the target and the mirror target have a similar range and Doppler, then the channel data zrd|mp can be described by equation (6) where the position of the target is (br,d, bd,d, bϕ1), for the crossing trajectories (br,c, bd,c) with the angle values ​​b ϕ1 and b ϕ2 , while the mirror is located at (br,m, bd,m, bϕ2). Using the geometric relations G leichung (7) the number of independent parameters can be reduced, i.e., only 6 nonlinear parameters (br,c, bd,c, r, d, bϕ1, bϕ2) need to be estimated, since all paths are interdependent. In automotive scenarios, the "cross-path" scenario represents the most critical scenario, as two additional false targets can be generated. If all four paths are significant, i.e., the full multi-path model, comprising direct, mirror, and cross paths, then most likely only two targets will be generated, one at the mirror path and one at the target location, since the discriminatory power of the mirror path is most likely higher than the cross path, and the direct path most likely has better performance than the corresponding cross path.Internal 202400193 9 In order to differentiate between the different situations, the detection parameters can then be estimated from the corresponding models in order to calculate the mean squared error (MSE). The use of standard model discrimination techniques, such as the so-called generalized likelihood ratio test (GLRT) or information criteria (IC), makes it possible to identify the correct model and mark the detections as false positive targets or false detections or real targets using the known method from DE 10 2021211 989 B3. Simplified determination of parameters The following describes a design of a simplified estimator for the described models. The estimation is divided into two parts or ranges, whereby the angle values ​​of the models are estimated first and the range Doppler values ​​in a second step. In the first step orIn the first part, the angle values ​​bφ are estimated either within the range or Doppler cell with the highest power or incoherently across all Nr· Nd cells. The estimation can be performed using the maximum likelihood (ML) approach, e.g., maximizing the lumped probability distribution by. Equation (8)where A is the angle control matrix as a function of bϕ for the corresponding model and z is the channel data used within the estimation. With the angle estimates The complex amplitudes can be estimated using least squares (LS) for each processing cell as follows: Equation (9)Internal 202400193 10 where i = 1, ..., NrNd and zi are the channel data of the i-th cell. The covariance matrix Rϕ of the estimated amplitudes can be simplified to Equation (10)where σ 2is the variance of the white circularly symmetric complex normal distribution of the noise in zi. Stacking the estimated complex amplitudes per cell in a matrix Γ with equation (11) describes a circularly symmetric complex normally distributed random matrix whose logarithmic probability distribution is proportional to G leichung (12) log where a simplified notation is used with Ard as the control matrix depending on the objectives within the model, br and bd, respectively. The matrix W is a diagonal matrix with complex weights for each objective in the model, while the covariance matrix is ​​described across the processing cells, by S = ^^ ^^ ^^^ ^+ ^^ ^ ^ ^^^^ . Equation (13)The optimization in equation (12) refers to W, ie the linear parameter results Equation (14)The use of Wopt in equation (12) allows the cost function that needs to be minimized to be determined in a simple way as equation (15) Internal 202400193 11 Requirements for the Evaluation Since the described tests are comparatively complex in terms of the calculations described, they should not, for example, be calculated for each range or each Doppler cell or detection. To reduce the computational effort, the data from a processing cell should therefore be examined before the model estimation described above. The present invention can be used in particular to distinguish between "cross-only situations" or cross-path propagations, which are particularly critical with regard to false detections. At least two peaks with a maximum power difference of Δ should be found in the beamformer, the difference between the peaks found should be below a certain threshold in range and Doppler, and any peaks found should not be classified as stationary. Internal

Claims

202400193 12 Patent claims / Patent claims 1. Method for determining false detections in radar detections in radar data, in connection with cross paths which arise due to different transmission and reception angles of paths for a radar target, in which a radar cube with range Doppler cells is generated on the basis of the radar data by means of Fourier transformation, wherein first a range and then a Doppler Fourier transformation is carried out so that channel data is available for each range Doppler cell, wherein the determination of false detections is carried out via the channel data of several adjacent range Doppler cells by using multidimensional models for multipath propagation which span these range Doppler cells to determine detection parameters range, Doppler and angle of the detections, wherein the following models are used as models for multipath propagation: - multipath model which has a direct path,an indirect path and an associated cross path for a radar target; and / or - cross path model which only comprises a cross path for a radar target (and no direct and indirect path); and / or - multiple single target models which comprise multiple direct independent paths or multiple independent radar targets.

2. Method according to claim 1, characterized in that the number of detection parameters for the multi-path model is reduced by the geometric relationship that both the value of the rank and that of the Doppler of the cross paths correspond to the mean of the corresponding values ​​of the indirect and direct paths.

3. Method according to claim 1 or 2, characterized in that pre-filtering is carried out by determining at least two detections with a maximum power difference of Δ by means of a beamformer, wherein the internal, 202400193 13 the difference between the range and Doppler of the detections found should be below a certain threshold value.

4. Method according to one of the preceding claims, characterized in that the determination of the detection parameters range, Doppler, and angle is divided into two parts, whereby first the angle values ​​of the models are estimated and then the range-Doppler values ​​are estimated.

5. Method according to claim 4, characterized in that the estimation of the range-Doppler values ​​is not performed jointly, but is again divided into two separate parts.

6. Method according to one of the preceding claims, characterized in that both cross paths are represented with a common amplitude.7.A system for determining false detections in radar data in conjunction with cross paths that arise due to different transmission and reception angles of paths for a radar target, comprising at least one radar sensor for detecting the surroundings of a vehicle and a control unit for processing the information provided by the radar sensor, wherein the control unit is configured to carry out a method according to one of the preceding claims. Internal.

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