Evaluation methods for RADAR measurement data from a mobile RADAR measurement system

Abstract

Evaluation method for RADAR measurement data of a mobile RADAR measurement system (10), wherein - multidimensional range Doppler maps (22,a,b,c) are created from the RADAR measurement data, - where each created multidimensional range-Doppler map (22,a,b,c) is stored together with a time information, - wherein at least one multidimensional range-Doppler map (22,a,b,c) with time information is propagated to the current time based on known motion data of the RADAR measurement system (10) corresponding to the motion of the RADAR measurement system (10), - where several multidimensional range Doppler maps (22,a,b,c) are combined to form a combined range Doppler map (24).

Description

[0001] The invention relates to an evaluation method for a RADAR measuring system.

[0002] There are many different types of radar measurement systems. Such a radar measurement system comprises a transmitting antenna and a receiving antenna. The transmitting antenna emits a radar wave that can be reflected by an object. The reflected radar wave is received by the receiving antenna. Using multiple transmitting and receiving antenna pairs, measurement data is generated for each combination. Range Doppler maps are generated from the measurement data. Such range Doppler maps show the distance and speed of objects in the form of high-intensity measured values. To determine the direction, the range Doppler maps are subjected to a directional process, such as beamforming. This produces angle-dependent range Doppler maps or multidimensional range Doppler maps.These angle-dependent range Doppler maps, or multidimensional range Doppler maps, are sampled by an algorithm to determine local maxima of the measured values ​​that represent the objects. For this purpose, the CFAR algorithm is used, for example.

[0003] In these known systems, objects that have an intensity below the threshold of the CFAR algorithm in the angle-dependent or multidimensional range Doppler maps are not detected.

[0004] DE 10 2015 119 650 A1 shows a method for validating at least one target detection of a target object, a computing device, a driver assistance system and a motor vehicle.

[0005] DE 10 2009 016 479 A1 shows a radar system with a method for avoiding incorrect reactions caused by interference or coupling.

[0006] US 6,538,599 B1 shows a non-coherent gain enhancement technique for non-stationary targets.

[0007] US 2017 / 0059695 A1 shows an apparatus and a method for detecting and correcting a blockage of an automotive radar sensor.

[0008] The task is therefore to improve the detection of weak objects.

[0009] This object is achieved by the method according to patent claim 1. Advantageous method variants are explained in the dependent claims.

[0010] The radar measurement system suitable for the method explained below corresponds, among other things, to the prior art. Such a radar measurement system is designed, in particular, as a mobile radar measurement system. Such a system can be mounted, for example, on a vehicle, in particular a motor vehicle, to detect objects such as other vehicles.

[0011] In particular, the radar measurement system features a multitude of transmit and receive antennas. Ideally, it is a frequency-modulated continuous wave radar, also known as FMCW radar. A sawtooth modulation pattern is advantageously used.

[0012] Each transmitting antenna transmits radar waves. The sequence of radar wave transmissions is distributed across the entire number of transmitting antennas. For example, the transmitting antennas transmit alternately one after the other or simultaneously in a coded pattern, particularly using the BPSK method. Each receiving antenna can receive every transmitted radar wave, with measurement data being provided for each pairing of transmitting and receiving antennas.

[0013] These measurement data are evaluated using multiple Fourier transformations and converted into range-Doppler maps. A range-Doppler map (RDM) is associated with each pair of transmitting and receiving antennas and includes the distance to objects and their speed, but not yet any directional information.

[0014] From the majority of RDMs and knowledge of the arrangement of sensor antennas and receiving antennas, a multitude of direction-oriented range Doppler maps are determined. For this purpose, a beamforming technique is used, for example, which provides range Doppler maps that cover a specific solid angle. The solid angle is determined by a azimuth angle and / or an elevation angle. Such an angle-dependent range Doppler map, wRDM, uses its measured values ​​to describe any objects located in front of the radar measurement system at a specific solid angle.

[0015] A high reading corresponding to a local maximum represents an object, whose position within the wRDM provides the distance and velocity. Such readings may, under certain circumstances, be unwanted reflections.

[0016] These unwanted reflections can be caused, for example, by side lobes of the RADAR measuring field.

[0017] The multitude of wRDMs divides the observed spatial region into a multitude of solid angles, thus providing a multidimensional range Doppler map (mRDM). This mRDM can, for example, be 3-dimensional if only one angle is considered, or 4-dimensional if two angles are considered. Actual objects and unwanted objects move within this mRDM if the radar measurement system and the object are moving relative to each other.

[0018] Such an mRDM is created for each time a measurement is taken. Each mRDM is saved with its time information or retained for future use. Furthermore, any movement of the mobile RADAR measurement system is detected and also kept available for future use.

[0019] Due to the known movement of the mobile RADAR measurement system, this movement can be used to propagate the mRDM. For this purpose, an mRDM is used, and a shift in measured values ​​within the mRDM is determined from the known movement. The movement data corresponds to the movement of the RADAR measurement system from the time of the mRDM to the time of the current mRDM. The measured values ​​are then shifted accordingly within the mRDM. If an object is static, i.e., cannot move relative to the ground, its measured value, i.e., its local maximum, is shifted to the position in the mRDM where it would have to be during a current measurement.

[0020] Now, multiple mRDMs propagated to the same time point are combined, for example, by summing the measured values. This combined range Doppler map is also referred to as a zRDM. Static objects are all propagated to the same position in the mRDM and add up to a large measured value for the zRDM, which can be detected as a local maxima. Unwanted reflections from side lobes do not move within the mRDM like a static object.

[0021] This allows weak static objects, in particular, to be identified through subsequent analysis. If the current mRDM were evaluated exclusively, these weak static objects would have been lost below the threshold for the analysis algorithm. These static objects, which are weakly detected by the radar measurement system, can thus be identified early. Unwanted reflections, on the other hand, are averaged out.

[0022] For the zRDM, a plurality of mRDMs from different time points is preferably used. For example, a current mRDM and several mRDMs from previous time points can be used. If necessary, only mRDMs from previous time points can be used.

[0023] Advantageous variants of the evaluation procedure are explained below.

[0024] It is proposed that the merged range Doppler map be evaluated with respect to objects.

[0025] The zRDM can be evaluated, for example, using the Constant False Alarm Rate (CFAR) algorithm. This allows for better detection and tracking of static objects. Furthermore, it also detects static objects measured with low intensity. The number of static objects detected in the zRDM is therefore significantly larger than the number of static objects detected in an mRDM.

[0026] Particularly advantageous is the CFAR algorithm's ability to detect patterns within the measured values ​​and track them over multiple zRDM cycles. Patterns that change little or not at all over multiple cycles can be verified as actual objects.

[0027] It is advisable to average the merged range Doppler map before evaluation.

[0028] This makes it easier to evaluate individual objects by allowing the measured values ​​to be compared more easily.

[0029] In a further variant, we propose that only the areas relevant for static objects are evaluated at the zRDM.

[0030] These regions of the zRDM can be determined based on the known motion, saving computing power. These regions are characterized by measured values ​​that are shifted during propagation.

[0031] Furthermore, a RADAR measuring system is proposed which carries out the evaluation method according to one of claims 1 to 5 or at least one of the previous embodiments.

[0032] This RADAR measuring system can be designed according to the above or further embodiments.

[0033] The evaluation procedure and a suitable RADAR measurement system are explained in detail using several figures. Fig. 1 a schematic representation of a mobile RADAR measuring system and an environment in plan view; Fig. 2 an angle-dependent range Doppler map of the RADAR measurement system; Fig. 3 a multidimensional range Doppler map of the RADAR measurement system; Fig. 4 Addition of several multidimensional range Doppler maps;

[0034] In the Fig. Figure 1 schematically shows a top view of a radar measuring system 10 and its surroundings. The radar measuring system 10 emits radar waves 12, which can be reflected by objects and detected again by the radar measuring system 10. The radar waves 12 are shown in simplified form as lines. For this purpose, at least one transmitting antenna and at least one receiving antenna are formed on the radar measuring system 10. Furthermore, the radar measuring system 10 comprises a plurality of electronic components to enable the transmission and reception of the radar waves and to process the acquired measurement data.

[0035] In the vicinity of the radar measuring system 10, there are, for example, two static objects 14, 16 that are firmly connected to a substrate or at least cannot move relative to it. The radar measuring system 10, however, moves itself at a speed v rAccordingly, the radar measuring system 10 is also referred to as a mobile radar measuring system 10. This can be mounted, for example, on a motor vehicle. For the purposes of this explanation, the movement is assumed to be uniform and straight. However, the radar measuring system 10 can actually perform any desired movement pattern.

[0036] This movement of the radar measurement system 10 is known and available for subsequent steps. For example, the motor vehicle can provide this movement information.

[0037] The Fig. Figure 1 shows objects 14, 16 at different times t0, t1, t2, and t3. These times correspond to the times at which the radar measurement system 10 performs measurements and transmits and receives radar waves 12 accordingly. Time t0 corresponds to the time of the current measurement, with the previous measurement being performed at time t1, and so on.

[0038] Object 14 is located directly in front of the radar measurement system 10, with object 16 laterally offset from object 14. For the following explanations, both objects 14 and 16 are at the same altitude, which corresponds to a constant elevation angle for the radar measurement system 10. The radar waves 12 emitted to objects 14 and 16 form an angle θ. This angle θ increases with respect to object 16 as time increases.

[0039] After a pulse sequence is transmitted by the transmitting antennas, reflected by the objects 14, 16, and subsequently detected by the receiving antennas, range Doppler maps (RDMs) are created from the measurement data of the RADAR measurement system 10. Each RDM corresponds to a transmitting antenna / receiving antenna pair and includes the distance and radial velocity of an object relative to the RADAR measurement system.

[0040] From the determined RDM, an angle-dependent range Doppler map, wRDM, is created for each angle θ, for example using the beamforming method. Such a wRDM 18 is described in the Fig. 2 shown for an angle θ = 0. On the X-axis is the speed of -v max to +v max In addition, the radial distance from 0 to s max shown on the Y-axis. This distance and speed range results from the design of the RADAR measurement system 10 and represents the system boundaries.

[0041] Within this wRDM, a measured value is displayed that corresponds to object 14. Since object 14 is static, it moves in the wRDM with the speed v r towards the RADAR measuring system 10. The object 14 is represented by the reference symbols 14a, 14b, 14c and 14d at the times t0, t1, t2 and t3.

[0042] Each object 14a, 14b, 14c and 14d is part of its own wRDM 18 at the times t0, t1, t2 and t3. However, to represent the movement of object 14, these are shown together, i.e. superimposed, in the Fig. 2. Since the object 14 is located directly in front of the RADAR measuring system 10, the angle θ does not change, so that it always remains in the same wRDM 18.

[0043] In addition to objects 14, 16, the measurement data also generates ghost objects 20 in the wRDM 18. These ghost objects 20a, b, c, d are displayed at different times. These can result, for example, from unwanted reflections from the side lobes of the radar measurement system 10. Furthermore, these unwanted reflections can also be caused by multipath propagation, when a radar wave travels different paths. Interference with other mobile or stationary radar measurement systems can also be averaged out.

[0044] The majority of such wRDMs can be combined into a multidimensional range Doppler map, mRDM. Such an mRDM 22 is in the Fig. 3. This extends the wRDM by the angle θ of -θ max to +θ max . The wRDM 18 of the Fig. 2 is part of the mRDM and is located in the middle at θ = 0.

[0045] In addition to object 14, object 16 is also shown in the mRDM at times t0, t1, t2, and t3. Object 16 moves towards the RADAR measuring system 10, whereby the radial velocity decreases and the angle θ increases to -θ max there.

[0046] Now, for further evaluation according to Fig. 4, a propagation is carried out for all points in time except the current time t0. The propagation uses the known movement of the RADAR measuring system to propagate the mRDM or the respective wRDM to time t0. Propagation means determining where an object 14 would be in the form of a measured value from time t1 to the current time t0. In doing so, each position within the mRDM is propagated, whereby only a subset of all possible positions can have static objects. In addition, it is calculated where a measured value should be from time t2 to the current time t0, and so on. This is only a straight-line movement, which is why shifting the measured values ​​is relatively easy. In principle, this method can be used for any movement pattern. The position of the measured value of object 14d in the mRDM is thus propagated or shifted to the position of the measured value of object 14a.The measured values ​​of object 14c and 14b are also propagated to the position of the measured value of object 14a.

[0047] According to the Fig.14, a plurality of mRDMs at different points in time are then propagated to the current point in time with the corresponding propagation and then combined. These mRDMs are designated with the reference symbols 22a, 22b, 22c, etc. This results in a combined multidimensional range Doppler map 24, zRDM. If necessary, an average value can also be determined. The number of points above time t indicates how far the mRDM is propagated. Static objects are always propagated to the same location. However, such unwanted reflections behave differently, so that starting from times t0, t1, t2, and t3, they are positioned at different locations in the combined range Doppler map 24 after propagation and are thus averaged out. This allows static objects that are lost in the noise floor during the evaluation of an mRDM to still be detected.

[0048] In addition to the azimuth angle θ, the application can also be extended to include an elevation angle. The functionality is the same. Due to the difficulty of representing a 4-dimensional mRDM in a single figure, a 3-dimensional mRDM was used for the explanation. Reference symbol 10 RADAR measuring system 12 radar waves 14,a,b,c,d object 16 objects 18 wRDM 20,a,b,c,d ghost object 22,a,b,c mRDM 24 zRDM v r speed θ angle t0 time t1 time point t2 time point t3 time point

Claims

[1] Evaluation method for RADAR measurement data of a mobile RADAR measurement system (10), where - multidimensional range Doppler maps (22,a,b,c) are created from the RADAR measurement data, - wherein each created multidimensional range Doppler map (22,a,b,c) is stored together with time information, - wherein at least one multidimensional range Doppler map (22,a,b,c) with time information is propagated to the current time based on known movement data of the RADAR measuring system (10) which correspond to the movement of the RADAR measuring system (10), - wherein several multidimensional range Doppler maps (22,a,b,c) are merged into a merged range Doppler map (24). [2] Evaluation method according to claim 1, characterized by that the merged range Doppler map (24) is evaluated with respect to objects (14, 16). [3] Evaluation method according to claim 1 or 2, characterized bythat the merged range Doppler map (24) is evaluated using the CFAR algorithm. [4] Evaluation method according to one of claims 1 to 3, characterized by that only the areas relevant for static objects are evaluated in the merged range Doppler map (24). [5] RADAR measuring system using a method according to any one of claims 1 to 4.

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