Ultrasonic sensor unit

Abstract

The present invention relates to an ultrasonic sensor unit comprising a first ultrasonic element and a logic unit, wherein the first ultrasonic element is configured to emit and / or receive at least one ultrasonic wave, wherein the logic unit is configured to generate an echo signal and a trace signal based on the at least one emitted and / or received ultrasonic wave, wherein the logic unit is configured to predict at least one further ultrasonic wave and one further echo signal based on the echo signal and the trace signal using a Kalman filter, and wherein the logic unit is configured to assign the further ultrasonic wave, the further echo signal and / or the further trace signal to the emitted ultrasonic wave, the echo signal and / or the trace signal using a Kuhn-Munkres algorithm.

Description

State of the art

[0001] The present invention relates to an ultrasonic sensor unit and a vehicle.

[0002] Currently, numerous solutions exist for utilizing ultrasonic signals in the automotive sector. Due to the increasing number of ultrasonic sensors and the rising quality and reliability requirements for ultrasonic sensors in vehicles, the demand for innovative and robust ultrasonic sensor units is constantly growing.

[0003] The continuous reduction of weight in the vehicle sector to reduce fuel consumption, as well as increasing competition, is causing cost pressure, leading to a greater demand for cheaper and more efficient vehicle components. Disclosure of the invention

[0004] The ultrasonic sensor unit according to the invention, with the features of claim 1, has the advantage over known systems that the robustness of the ultrasonic measurements is significantly improved and they can be more easily adapted to changes in the environment of the ultrasonic sensor unit. It is an efficient tracking system that enables streamlined and systematic processing of the sensor data, leading to more precise and reliable predictions and classifications. This approach improves the robustness of the system and makes it more adaptable to changes in the environment or the number of tracked objects.

[0005] This is achieved according to the invention by the fact that the ultrasonic sensor unit comprises a first ultrasonic element and a logic unit, wherein the first ultrasonic element is configured to emit and / or receive at least one ultrasonic wave, wherein the logic unit is configured to generate an echo signal and a trace signal based on the at least one emitted and / or received ultrasonic wave, wherein the logic unit is configured to predict at least one further ultrasonic wave, one further echo signal for one further trace signal based on the echo signal and / or the trace signal by means of a Kalman filter, wherein the logic unit is configured to assign the further ultrasonic wave, the further echo signal and / or the further trace signal to the emitted ultrasonic wave, the echo signal and / or the trace signal by means of a Kuhn-Munkres algorithm.

[0006] In other words, the ultrasonic sensor unit can be used for data documentation that combines the Kalman filter and the Hungarian algorithm (or Kuhn-Munkres algorithm) to acquire echo data and link it within the ultrasonic system. This can be achieved using five main steps: prediction, linking, updating, initialization, and evaluation. Preferably, the prediction step uses the Kalman filter to forecast the measurements for the next time interval, such as a frame. In the association step, the Hungarian algorithm (or Kuhn-Munkres algorithm) can be used to link the forecasted data with the current measurement data within the current time interval, for example, within a suitable matching window.In an update step, the Kalman filter parameters can then be updated, particularly concurrently with an observer using covariance to provide a matching window and other necessary parameters for the next measurement cycle. Due to an imbalance in the number of entries in both tracks and incoming echoes, the tracks can be validated without being linked to a new echo, especially to free up storage space for new data. If the echoes cannot be linked to an existing track, a new track can be initialized, which can then develop a new history.Preferably, the echo signal can be a data entry or a plurality of data entries based on an ultrasonic wave that was both emitted and received by the same ultrasonic element, or an ultrasonic wave that was emitted by a first ultrasonic element and received by a second ultrasonic element. More preferably, the trace signal can be a trace or similar, which can particularly include a plurality of data entries.

[0007] The dependent claims describe preferred embodiments of the invention.

[0008] Preferably, the logic unit is configured to update the Kalman filter based on the associated additional ultrasound wave, the associated additional echo signal and / or the associated additional trace signal in order to form a suitable window and at least one adapted parameter for a further measurement.

[0009] An advantage of this embodiment is that measurement errors or similar issues can be detected and excluded from further processing. Preferably, the appropriate window encompasses a range within which the measured values ​​for the next subsequent measurement can lie. The Kalman filter can be used to estimate the state of a system by combining measurements of the system with state predictions. The Kalman filter is particularly useful in systems with noisy or incomplete measurements and when there is uncertainty about how the system will evolve over time. The main application of the Kalman filter in this context is to predict the next echo distance based on a series of stored echoes in a track.

[0010] A further preferred option is a number of entries in the associated further echo signal that is not equal to the number of entries in the associated further track signal, wherein the logic unit is configured to assign an entry of the associated further echo signal to a new track signal if the entry of the echo signal cannot be assigned to the associated further track signal.

[0011] One advantage of this embodiment is that the ultrasonic sensor unit makes an independent decision as to whether the received or measured ultrasonic value belongs to a track or whether a new track should be formed.

[0012] The "assignment" step can be used to assign exactly one echo to each track and vice versa. After the prediction step, each track is assigned a predicted value for the next echo distance. The predictions can then be compared to the incoming echoes, and the difference calculated. Based on this difference, the cost for each pair can be calculated. Assuming there are M tracks on the x-axis and N echoes on the y-axis that need to be assigned to each track, the cost w(x,y) for each pair (track, echo) can be determined. Preferably, all assignments can be completed to minimize the total cost in the cost table W(x,y).

[0013] For example, a track might not be assigned to any echo, or vice versa. This could mean that the track was not updated with new information during this measurement cycle. This presents two challenges: first, the local minimum may not be the global minimum cost, and second, an asymmetric matrix may be present.

[0014] To solve this assignment problem with minimal cost, a Kuhn-Munkres algorithm (also known as the Hungarian algorithm) with polynomial time complexity can be used. This algorithm can work by iteratively finding a set of complementary paths in a weighted bipartite graph.

[0015] Preferably, the cost matrix for the Hungarian algorithm is prepared with the complexity . Preferably, the minimum problem is transformed into a maximum problem: W(x, y) = -W(x, y). The cost matrix W is balanced by padding the rows or columns with a standard cost limit value, e.g., the maximum invalid cost, defined as a positive number. The result of this step is a balanced NxN matrix with covered costs. The algorithm works by finding a maximum match in a bipartite graph, where one set x of nodes represents the actual echoes and the other set y represents the traces.

[0016] The process of assigning assignments described above continues until all nodes are assigned, meaning the number of assignments can equal the size of the cost matrix. When this occurs, a path with the minimum total cost is preferentially found, where each element in the row is assigned to exactly one element in the corresponding column. This ensures that each echo and each trace is assigned to exactly one counterpart. Since the cost matrix is ​​balanced at the start of the algorithm, there may be echoes that cannot be connected to a trace because the number of traces is less than the number of echoes, and vice versa.

[0017] Preferably, the logic unit has at least one observer of the Kalman filter, wherein the observer of the Kalman filter is configured to adjust at least one output value of the Kalman filter when the output value of the Kalman filter deviates from the ultrasonic wave, the echo signal and / or the trace signal by a predetermined amount.

[0018] One advantage of this embodiment is that the results of the Kalman filter can be further improved with the help of the observer, thus further improving the accuracy of the overall system.

[0019] In practical applications of the Kalman filter, it can be challenging to determine and adjust the accuracy of the mappings in real time, as well as to analyze the system's performance based on the mappings of recorded measurements. To address this issue, an observer can be employed to monitor the system's state. The observer can analyze the filter's output and compare it to the actual measurements. If deviations in the filter's estimates are detected, the observer can make necessary adjustments to the filter's parameters to improve its accuracy and reliability.

[0020] If the filter is working correctly, the measurement noise is preferably white noise with a mean of zero. Therefore, the consistency of the filter can be checked by preferably applying the credibility check to the a posteriori error covariance as well as the credibility check to the innovation covariance.

[0021] The elements of the innovation covariance matrix can be used to check the consistency of the Kalman filter's output. If the size of the innovation is too large relative to the innovation covariance matrix, this may indicate that the filter is not working correctly and may need to be adjusted. Furthermore, the innovation covariance matrix is ​​a good indicator for adjusting the allocation window for the association step. Ideally, the first element of the innovation covariance matrix can be used to filter out uncorrelated data, thus preferentially considering only relevant data for the association step. This can improve the algorithm's accuracy and efficiency.

[0022] Preferably, the logic unit is configured to update at least one operating parameter of the observer based on the associated additional ultrasound signal, the associated additional echo signal and / or the associated additional trace signal.

[0023] When an echo is assigned to a track, it is preferably added to the track's stored echo list. This can trigger an update of the Kalman filter for that track. The Kalman filter update process can include integrating the predicted states with the newly measured states, namely the updated echo distance and the slope or first time derivative of the distance resulting from the addition of the new echo to the track. Additionally, the state control is preferably updated by calculating the second derivatives of the recent echo distances. The updated state estimate and covariance matrix are then preferably used as the basis for the next prediction step in the Kalman filter algorithm.

[0024] One advantage of this embodiment is that the accuracy of the observer can be further improved, and in particular a synergistic effect is created between the observer and the Kalman filter, which can further improve the assignment accuracy and, consequently, the measurement accuracy of the sensor unit.

[0025] Preferably, updating at least one operating parameter of the observer includes updating a covariance matrix.

[0026] One advantage of this embodiment is that a large number of components can be taken into account in order to improve the operating parameters of the observer.

[0027] Preferably, the logic unit is configured to determine a difference between the echo signal or the trace signal and the further echo signal or the further trace signal, wherein the logic unit is configured to determine a value for each pair of values ​​of the further echo signal and the further trace signal based on the difference.

[0028] One advantage of this embodiment is that the comparability of the ultrasonic sensor values ​​can be increased with the help of the resulting difference.

[0029] Preferably, the logic unit is configured to minimize a total value using the Kuhn-Munkres algorithm, wherein the total value is a sum of a plurality of values ​​for each pair of values, and wherein the logic unit is configured to assign the further ultrasound wave, the further echo signal and / or the further trace signal to the ultrasound wave, the echo signal or the trace signal based on the total value and the Kuhn-Munkres algorithm.

[0030] One advantage of this embodiment is that a journey can be determined with minimal total cost, ensuring that each echo and each trace is associated with exactly one counterpart.

[0031] Preferably, the ultrasonic sensor unit has a second ultrasonic sensor element, wherein the logic unit is configured to assign a second echo signal, which was detected by means of the second ultrasonic sensor element, to the further trace signal using the Kuhn-Munkres algorithm.

[0032] One advantage of this embodiment is that a large number of ultrasonic sensors, which can be arranged around a car, for example, can be used to further improve the accuracy of the ultrasonic sensor unit.

[0033] Another aspect of the invention relates to a vehicle which has an ultrasonic sensor unit as described above and below. Brief description of the drawings

[0034] Exemplary embodiments of the invention are described in detail below with reference to the accompanying drawings. The drawing shows: Fig. 1 an ultrasonic sensor unit according to an embodiment, Fig. 2, Fig. 3 to Fig. 4 a diagram illustrating the operation of the ultrasonic sensor unit according to one embodiment, Fig. 5 and Fig. 6 a block diagram to illustrate the operation of the ultrasonic sensor unit according to one embodiment, Fig. 7 a simulation view of a vehicle with the ultrasonic sensor unit according to one embodiment, Fig. 8 and Fig. 9 a diagram illustrating the operation of an ultrasonic sensor unit according to one embodiment, and Fig. 10 a vehicle according to an embodiment. Embodiments of the invention

[0035] Preferably, all identical elements, units and / or steps in all figures are labelled with the same reference symbols.

[0036] Fig. Figure 1 shows an ultrasonic sensor unit 10 according to one embodiment. The ultrasonic sensor unit 10 comprises a first ultrasonic element 12 and a logic unit 14, wherein the first ultrasonic element 12 is configured to emit and / or receive at least one ultrasonic wave 16, wherein the logic unit 14 is configured to generate an echo signal and a trace signal based on the at least one emitted and / or received ultrasonic wave 16, wherein the logic unit 14 is configured to predict at least one further ultrasonic wave, a further echo signal, and / or a further trace signal based on the echo signal and the trace signal using a Kalman filter, and wherein the logic unit 14 is configured to assign the further ultrasonic wave, the further echo signal, and / or the further trace signal to the emitted ultrasonic wave, the echo signal, and / or the trace signal using a Kuhn-Munkres algorithm.

[0037] As in the Fig. As shown in Figure 1, the ultrasonic sensor unit is preferably arranged in a vehicle 100. Preferably, the ultrasonic sensor unit can comprise a logic unit 14, which can be formed separately or integrally with an ultrasonic element 12. More preferably, the ultrasonic sensor unit 10 can have a second ultrasonic element 18, which can, in particular, receive an ultrasonic wave 16 emitted by the first ultrasonic element 12. As shown in the Fig. As illustrated in Figure 1, the ultrasonic elements each form a field of view 200, in particular in a section 204, which is monitored, for example, by the first ultrasonic element 12, an obstacle 206 can be detected. More preferably, the obstacle 206 can also be detected in a second section 204, which is monitored, for example, by the second ultrasonic sensor element 18. For example, the obstacle 206 can also be a tree 208.

[0038] Fig. Figure 2 shows a diagram 300 illustrating the operation of the ultrasonic sensor unit 10 according to one embodiment. The diagram 300 preferably has a first axis 302 and a second axis 304. As shown in the Fig. As can be seen in Figure 2, a large number of tracks 306 are plotted in diagram 300. For example, each ultrasound measurement can be assigned to a first track 308, a second track 310, or a third track 312.

[0039] Fig. Figure 3 shows a diagram 320 illustrating the operation of the ultrasonic sensor unit 10 according to one embodiment. Preferably, the diagram 320 has a first axis 322 and a second axis 324. As can be seen in the diagram 320, the ultrasonic measurement values ​​can be summarized, in particular, into a curve 326, a second curve 328, and a third curve 330.

[0040] Figure 350 shows a diagram illustrating the operation of the ultrasonic sensor unit 10 according to one embodiment. The diagram 350 preferably has a first axis 352 and a second axis 354. Preferably, a plurality of measured values ​​362 can be plotted on the diagram. Preferably, the ultrasonic sensor unit 10 is configured to form a first track 356 based on the plurality of measured values ​​362. More preferably, the ultrasonic sensor unit 10 can also detect a second track 358 as well as a third track 360.

[0041] Fig. Figure 5 shows a block diagram 400 illustrating the operation of the ultrasonic sensor unit 10 according to one embodiment. Preferably, the diagram 400 has two inputs, in particular an input of the echo signal 401 and an input of the track signal 402. Preferably, an algorithm 404 can handle the further processing of the input signals in the converter 406. Preferably, a Kalman prediction step 408 can be applied to the input signals 406. Based on the prediction step 408, a mapping step can be performed, in particular using the Hungarian algorithm 410, which can utilize the input signals 406. More preferably, an update step 412 of the Kalman filter can be performed, which can take into account both the results of the Hungarian algorithm 410 and the input signals 406.

[0042] Fig. Figure 6 shows a block diagram 450 illustrating the operation of the ultrasonic sensor unit 10 according to one embodiment. Preferably, new measured values ​​452 for the ultrasonic sensor unit 10 are available. In step 454, the new values ​​452 can be extended by existing values ​​453. The combination of the data in step 456, especially with the echoes 460, can be used in the prediction step 458. Based on the updated values ​​of the echo and the track 464, these values ​​can be fed into an assignment process 464 in step 462. Based on this, a substep of conflict resolution 482 can be performed in the association 464. Preferably, step 482 can comprise a plurality of substeps 484, 486, 488, 490 in order to be able to assign a plurality of echo values ​​for each track. A validation 468 can be performed using the tracks 466.Preferably, an update 470 can be performed using the traces and echoes 478. Based on the association 464, an initialization 472 can be performed using the echoes 480. Preferably, an observer of the Kalman filter 474 can be applied based on the update 470. The results of the validation 468, the update 470, and the initialization 472 can be combined in step 476 to form and store the existing trace data 453, thus closing the loop.

[0043] Fig. Figure 7 shows a simulation view 500 illustrating the operation of the ultrasonic sensor unit 10 according to one embodiment. As shown in the simulation view 500, a vehicle 502 can emit an ultrasonic wave 506, in particular simulating obstacles 504.

[0044] Fig. Figure 8 shows a diagram illustrating the operation of the ultrasonic sensor unit 10 according to one embodiment. The diagram 510 has a first axis 512, which in particular includes a distance of the echo, and a second axis 514, which includes a time signature. As shown in the diagram 510, a first curve 516 as well as a second curve 518 can be displayed, wherein the ultrasonic sensor unit 10 is configured to add new measured values ​​to the respective curve based on the Kalman filter and the Hungarian algorithm.

[0045] Fig. Figure 9 shows a diagram 520 illustrating the operation of the ultrasonic sensor unit 10 according to one embodiment. The diagram 520 has a first axis 522 and a second axis 524. A plurality of measured values ​​530 are plotted in the diagram 520, the ultrasonic sensor unit 10 being configured to identify a first trend 526 and a second trend 528.

[0046] Fig. Figure 10 shows a vehicle 100 according to one embodiment. The vehicle 100 preferably has an ultrasonic sensor unit 10, as described above and below.

Claims

[1] comprising an ultrasonic sensor unit (10): - a first ultrasound element (12), - a logic unit (14), - wherein the first ultrasound element (12) is configured to emit and / or receive at least one ultrasound wave (16), - wherein the logic unit (14) is configured to generate an echo signal and a trace signal based on at least one emitted and / or received ultrasonic wave (16), - wherein the logic unit (14) is configured to predict, based on the echo signal and / or the trace signal, at least one further ultrasonic wave, one further echo signal for one further trace signal by means of a Kalman filter, - wherein the logic unit (14) is configured to assign the further ultrasound wave, the further echo signal and / or the further trace signal to the emitted ultrasound wave, the echo signal and / or the trace signal using a Kuhn-Munkres algorithm. [2] Ultrasonic sensor unit (10) according to claim 1, - wherein the logic unit (14) is configured to update the Kalman filter based on the associated additional ultrasound wave, the associated additional echo signal and / or the associated additional trace signal in order to form a suitable window and at least one adapted parameter for further measurement. [3] Ultrasonic sensor unit (10) according to claim 2, - where the number of entries in the associated further echo signal is not equal to the number of entries in the associated further trace signal, - wherein the logic unit (14) is configured to assign an entry of the associated further echo signal to a new track signal if the entry of the echo signal cannot be assigned to the associated further track signal. [4] Ultrasonic sensor unit (10) according to one of claims 2 to 3, - wherein the logic unit (14) includes at least one observer of the Kalman filter, - wherein the observer of the Kalman filter is configured to adjust at least one output value of the Kalman filter when the output value of the Kalman filter deviates from the ultrasonic wave (16), the echo signal and / or the trace signal by a predetermined amount. [5] Ultrasonic sensor unit (10) according to claim 4, - wherein the logic unit (14) is configured to update at least one operating parameter of the observer based on the associated additional ultrasonic wave, the associated additional echo signal and / or the associated additional trace signal. [6] Ultrasonic sensor unit (10) according to claim 5, - where updating at least one operating parameter of the observer involves updating a covariance matrix. [7] Ultrasonic sensor unit (10) according to any one of the preceding claims, - wherein the logic unit (14) is configured to determine a difference between the echo signal or the trace signal and the further echo signal or the further trace signal, - wherein the logic unit (14) is configured to determine a value for each pair of values ​​of the further echo signal and the further trace signal based on the difference. [8] Ultrasonic sensor unit (10) according to claim 7, - wherein the logic unit (14) is configured to minimize a total value using the Kuhn-Munkres algorithm, - where the total value is a sum of a multitude of values ​​for each pair of values, - wherein the logic unit (14) is configured to assign the further ultrasound wave, the further echo signal and / or the further trace signal to the ultrasound wave, the echo signal or the trace signal based on the total value and the Kuhn-Munkres algorithm. [9] Ultrasonic sensor unit (10) according to any one of the preceding claims, - wherein the ultrasonic sensor unit (10) has a second ultrasonic sensor element (18), wherein the logic unit (14) is configured to assign a second echo signal, which was detected by means of the second ultrasonic sensor element (18), to the further trace signal by means of the Kuhn-Munkres algorithm. [10] Vehicle (100) comprising an ultrasonic sensor unit (10) according to one of the preceding claims.

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