Method, device and equipment for suppressing ultrasonic co-frequency interference and storage medium

Abstract

The invention discloses a method, device and equipment for suppressing ultrasonic co-frequency interference and a storage medium, and relates to the technical field of intelligent driving, and the method comprises the steps: obtaining single echo data and parking distance control data of an ultrasonic radar; filtering the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data; parking control is carried out according to the updated echo data, the problem of how to restrain co-frequency interference on the premise that the position of a vehicle ultrasonic probe and a wave receiving and sending time sequence mechanism are not changed is solved, and the stability and reliability of parking are improved.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent driving, and in particular to a method, device, equipment and storage medium for suppressing ultrasonic co-frequency interference. Background Art

[0002] In parking scenarios, ultrasonic radar, as an important component of the vehicle's automatic parking system, undertakes key functions such as detecting the surrounding environment and providing collision warnings. However, in actual applications, when multiple vehicles turn on ultrasonic radars at the same time, due to the similarity of the radar's operating frequencies, the ultrasonic signals between different vehicles are very likely to interfere with each other at the same frequency, resulting in mixed received signals, which in turn affects the parking system's accurate judgment of the surrounding environment and increases safety hazards during parking. In existing methods, in order to address this problem, measures such as adjusting the radar's transmit and receive timing, changing the radar's operating frequency, or increasing physical isolation are usually adopted. However, these methods often involve hardware modifications or modifications to the manufacturer's source code, which not only have high implementation costs, but are also difficult to be used in ultrasonic radar products of different brands.

[0003] Therefore, how to suppress co-channel interference without changing the position of the vehicle's ultrasonic probe and the timing mechanism of transmitting and receiving waves is a problem that needs to be solved urgently. Summary of the invention

[0004] The main purpose of this application is to provide a method, device, equipment and storage medium for suppressing ultrasonic co-frequency interference, aiming to solve the technical problem of how to suppress co-frequency interference without changing the position of the vehicle ultrasonic probe and the timing mechanism of transmitting and receiving waves.

[0005] To achieve the above object, the present application proposes a method for suppressing ultrasonic co-frequency interference, the method comprising:

[0006] Obtain single echo data and parking distance control data of ultrasonic radar;

[0007] filtering the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data;

[0008] Parking control is performed according to the updated echo data to suppress ultrasonic co-frequency interference.

[0009] In one embodiment, the step of filtering the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data includes:

[0010] Initialize the state transfer matrix, predict the system covariance, process covariance noise, measurement matrix and observation noise covariance based on the preset filtering strategy;

[0011] Obtaining predicted echo data and predicted error covariance according to at least two of the state transfer matrix, the predicted system covariance, the process covariance noise, and the single echo data;

[0012] Filtering and updating are performed according to the measurement matrix, the observation noise covariance, the predicted echo data, the prediction error covariance and the parking distance control data to obtain updated echo data.

[0013] In one embodiment, after the step of initializing the state transfer matrix, predicting the system covariance, the process covariance noise, the measurement matrix and the observation noise covariance based on the preset filtering strategy, the method further includes:

[0014] Get the adjustment ratio;

[0015] The magnitudes of the observation noise covariance and the process covariance noise are adjusted according to the adjustment ratio.

[0016] In one embodiment, the step of obtaining predicted echo data and prediction error covariance according to at least two of the state transfer matrix, the predicted system covariance, the process covariance noise, and the single echo data comprises:

[0017] Obtaining predicted echo data according to the state transfer matrix and the single echo data;

[0018] The prediction error covariance is obtained according to the state transfer matrix, the prediction system covariance and the process covariance noise.

[0019] In one embodiment, the step of filtering and updating according to the measurement matrix, the observation noise covariance, the predicted echo data, the prediction error covariance and the parking distance control data to obtain updated echo data comprises:

[0020] Get historical parking distance control data;

[0021] Obtaining a filter gain according to the measurement matrix, the observation noise covariance, and the prediction error covariance;

[0022] Updated echo data is obtained according to the predicted echo data, the filter gain, the parking distance control data, the historical parking distance control data and the measurement matrix.

[0023] In one embodiment, the step of obtaining updated echo data according to the predicted echo data, the filter gain, the parking distance control data, the historical parking distance control data and the measurement matrix comprises:

[0024] When the parking distance control data is updated, updating the echo data according to the parking distance control data, the predicted echo data, the filter gain and the measurement matrix calculation;

[0025] When the parking distance control data is not updated, the parking distance control data in the updating process is replaced according to the historical parking distance control data, and the updated echo data is calculated according to the parking distance control data, the predicted echo data, the filter gain and the measurement matrix.

[0026] In one embodiment, after the step of obtaining the filter gain according to the measurement matrix, the observation noise covariance and the prediction error covariance, the method further includes:

[0027] Update the prediction system covariance according to the filter gain, the measurement matrix and the prediction error covariance to obtain an updated prediction system covariance;

[0028] The filter gain is updated according to the updated predicted system covariance and the observed noise covariance.

[0029] In addition, to achieve the above purpose, the present application also proposes a device for suppressing ultrasonic co-frequency interference, the device comprising:

[0030] A data acquisition module, used to acquire single echo data of ultrasonic radar and parking distance control data;

[0031] A filtering update module, configured to filter the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data;

[0032] The parking control module is used to perform parking control according to the updated echo data to suppress ultrasonic co-frequency interference.

[0033] In addition, to achieve the above-mentioned purpose, the present application also proposes a device for suppressing ultrasonic co-channel interference, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the method for suppressing ultrasonic co-channel interference as described above.

[0034] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the method for suppressing ultrasonic co-frequency interference as described above are implemented.

[0035] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the method for suppressing ultrasonic co-frequency interference as described above are implemented.

[0036] The present application provides a method for suppressing ultrasonic co-frequency interference. The present application obtains single echo data and parking distance control data of an ultrasonic radar; filters the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data; and performs parking control according to the updated echo data to suppress ultrasonic co-frequency interference. In summary, the present application processes the single echo data of an ultrasonic radar in real time, and combines the data of a parking distance control system as a true value for filtering and updating, thereby accurately extracting effective signals, solving the problem of how to suppress co-frequency interference without changing the position of the vehicle ultrasonic probe and the timing mechanism of the transceiver wave, thereby improving the stability and reliability of the parking system. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0039] Figure 1 A flowchart diagram of the first embodiment of the method for suppressing ultrasonic co-frequency interference provided by the present application;

[0040] Figure 2 A flow chart of a second embodiment of the method for suppressing ultrasonic co-frequency interference provided by the present application;

[0041] Figure 3 A flowchart diagram of a third embodiment of the method for suppressing ultrasonic co-frequency interference provided by the present application;

[0042] Figure 4 This is a schematic diagram of the module structure of the device for suppressing ultrasonic co-frequency interference according to an embodiment of the present application;

[0043] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the method for suppressing ultrasonic co-frequency interference in the embodiment of the present application.

[0044] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0045] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0046] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0047] The main solution of the embodiment of the present application is: by acquiring single echo data and parking distance control data of the ultrasonic radar; filtering the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data; and performing parking control according to the updated echo data to suppress ultrasonic co-frequency interference.

[0048] In parking scenarios, ultrasonic radar, as an important component of the vehicle's automatic parking system, undertakes key functions such as detecting the surrounding environment and providing collision warnings. However, in actual applications, when multiple vehicles turn on ultrasonic radars at the same time, due to the similarity of the radar's operating frequencies, the ultrasonic signals between different vehicles are very likely to interfere with each other at the same frequency, resulting in mixed received signals, which in turn affects the parking system's accurate judgment of the surrounding environment and increases safety hazards during parking. In existing methods, in order to address this problem, measures such as adjusting the radar's transceiver timing, changing the radar's operating frequency, or increasing physical isolation are usually adopted. However, these methods often involve hardware modification or modification of the manufacturer's source code, which not only has high implementation costs, but is also difficult to be used in ultrasonic radar products of different brands. Therefore, how to suppress co-frequency interference without changing the position of the vehicle's ultrasonic probe and the timing mechanism of transceiver waves is a problem that needs to be solved urgently.

[0049] The present application processes the single echo data of the ultrasonic radar in real time, and combines it with the data of the parking distance control system as the true value for filtering and updating, so as to accurately extract the effective signal. This solves the problem of how to suppress co-frequency interference without changing the position of the vehicle ultrasonic probe and the timing mechanism of the receiving and transmitting waves, thereby improving the stability and reliability of the parking system.

[0050] It should be noted that the execution subject of this embodiment can be a system for suppressing ultrasonic co-frequency interference, or a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above-mentioned function of suppressing ultrasonic co-frequency interference, etc., and this embodiment does not specifically limit this. The following takes the system for suppressing ultrasonic co-frequency interference as an example to illustrate this embodiment and the following embodiments.

[0051] Based on this, the present application embodiment provides a method for suppressing ultrasonic co-frequency interference, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the method for suppressing ultrasonic co-frequency interference of the present application.

[0052] In this embodiment, the method for suppressing ultrasonic co-frequency interference includes steps S10 to S30:

[0053] Step S10: Acquire single echo data of the ultrasonic radar and parking distance control data.

[0054] It should be noted that single echo data refers to the first reflected signal directly received by the ultrasonic radar. Although it can reflect the existence of obstacles, it will produce large errors when there is co-frequency interference. Parking distance control data is more accurate, but due to its low update frequency, it cannot be directly used for real-time obstacle detection.

[0055] In addition, it should be noted that in this step, the system will first obtain single echo data in real time through the vehicle-mounted ultrasonic radar. Single echo data is the first reflected signal received after the ultrasonic radar transmits the signal. Its period is generally 40ms and contains the distance information between the obstacle and the vehicle. At the same time, the PDC (Parking Distance Control) system also provides data in real time. This data is a more accurate parking distance calculated by other sensors of the vehicle, and its update period is generally 100-200ms.

[0056] Step S20: filtering the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data.

[0057] It should be noted that the updated echo data refers to the obstacle distance information after Kalman filtering, which combines the advantages of single echo data and parking distance control data, and can more accurately reflect the actual situation of the vehicle and the surrounding environment. In this step, the system will use Kalman filter as the preset filtering strategy. Kalman filter is an efficient recursive filter (autoregressive filter), which can estimate the state of the dynamic system from a series of measurements containing statistical noise. Specifically, the system will initialize the parameters required by Kalman filter (such as state transfer matrix, covariance of prediction system, covariance noise, observation noise covariance, etc.), and predict the obstacle distance at the current moment based on these parameters. Then, the parking distance control data is used as the true value to update the obstacle distance (i.e., observation value) at the current moment using Kalman gain and measurement matrix to obtain updated echo data.

[0058] It can be understood that this process is repeated, and each frame of data is filtered to obtain more accurate obstacle distance information. This method effectively integrates single echo data and parking distance control data, and updates the echo data in real time through the prediction and update mechanism of Kalman filtering to suppress the error caused by co-frequency interference.

[0059] Step S30: performing parking control according to the updated echo data to suppress ultrasonic co-frequency interference.

[0060] It should be noted that in this step, the updated echo data processed in step S20 will be used for parking control. These data have been optimized by Kalman filtering and can more accurately reflect the distance between the vehicle and surrounding obstacles. Therefore, during the parking process, the system can control the vehicle's speed and direction according to these data to ensure safe parking.

[0061] This embodiment provides a method for suppressing ultrasonic co-frequency interference. This embodiment obtains single echo data and parking distance control data of ultrasonic radar; filters the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data; and performs parking control according to the updated echo data to suppress ultrasonic co-frequency interference. In summary, this embodiment processes the single echo data of ultrasonic radar in real time, and combines the data of parking distance control system as the true value for filtering and updating, thereby accurately extracting effective signals, solving the problem of how to suppress co-frequency interference without changing the position of the vehicle ultrasonic probe and the timing mechanism of transmitting and receiving waves, thereby improving the stability and reliability of the parking system.

[0062] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can refer to the above introduction, and will not be repeated later. Figure 2 , Figure 2 This is a flow chart of a second embodiment of the method for suppressing ultrasonic co-frequency interference of the present application, wherein step S20 further includes:

[0063] Step S201: Initialize the state transfer matrix, prediction system covariance, process covariance noise, measurement matrix and observation noise covariance based on a preset filtering strategy.

[0064] It should be noted that the system will initialize the parameters required for the Kalman filter. Specifically, the state transfer matrix (F) is initialized, that is, the state transfer matrix is ​​set to 1, indicating that in the current filtering cycle, the distance prediction value is directly equal to the observed value after the last filtering (that is, the single echo distance observed by the sensor). The prediction system covariance (P) is initialized, that is, the prediction system covariance is set to a small positive number (such as 1), representing the uncertainty or error at the initial moment of the system. This value will be gradually adjusted as the filtering process progresses to more accurately reflect the current confidence of the system. The process covariance noise (Q) is initialized. The process covariance noise Q reflects the random noise in the state transfer process. In this step, it can be assumed that the single echo data is relatively stable. The initial value of Q needs to be set according to the system characteristics and experience. It is usually a small positive number, but in actual applications, it may need to be adjusted according to the specific situation to reduce the uncertainty impact on the system state prediction. The measurement matrix (H) is initialized. The measurement matrix H is also initialized to 1 in this step, indicating that the observation value (parking distance control data) is directly used to update the system state. This is because the parking distance control data, as the true value of the parking distance control, has high accuracy and reliability. Initialize the observation noise covariance (R), which reflects the difference between the observed value (parking distance control data PDC) and the true value. Similarly, its initial value also needs to be set according to system characteristics and experience to balance the trust in the observed value and the prediction of the system state.

[0065] In a feasible implementation manner, after step S201, the method further includes:

[0066] Step A10: Obtain the adjustment ratio.

[0067] It should be noted that the adjustment ratio is a dynamically adjusted parameter, which can be adjusted in real time according to the actual application scenario and the specific situation during the parking process. In this step, the system will determine a suitable adjustment ratio by analyzing historical data or experimental tests. This ratio is used to adjust the order of magnitude relationship between the observation noise covariance R and the process covariance noise Q. The choice of the adjustment ratio depends on the system's requirements for real-time and accuracy, as well as the understanding of noise characteristics. It can be understood that the setting of the adjustment ratio is crucial to the performance of the Kalman filter algorithm. An appropriate adjustment ratio can enable the algorithm to reduce the error caused by noise interference while maintaining a high real-time performance, thereby improving the accuracy of parking distance control.

[0068] Step A20: adjusting the magnitudes of the observation noise covariance and the process covariance noise according to the adjustment ratio.

[0069] It should be noted that after determining the adjustment ratio, the system will adjust the order of magnitude of R and Q according to the adjustment ratio. Specifically, according to the preset adjustment ratio, the initial values ​​of R and Q are scaled to ensure that the accuracy and smoothness of the output results can be balanced during the filtering process. For example: During automatic parking, when the system detects that the co-channel interference is more serious, the order of magnitude of R can be appropriately reduced (i.e., its value can be increased), while maintaining or appropriately reducing the order of magnitude of Q (i.e., not increasing its value or slightly increasing it) to increase the algorithm's trust in the true value of PDC, thereby effectively restraining co-channel interference.

[0070] It is understandable that by adjusting the magnitude of R and Q, the degree of trust that the Kalman filter algorithm has in the true value of PDC and the observed value of DE can be affected. When R is small, the algorithm is more inclined to trust the true value of PDC; and when Q is small, the algorithm is more inclined to rely on the observed value of DE. Through reasonable adjustment, the algorithm can still maintain high accuracy and real-time performance when facing co-channel interference.

[0071] Step S202: obtaining predicted echo data and a prediction error covariance according to at least two of the state transfer matrix, the predicted system covariance, the process covariance noise and the single echo data.

[0072] It should be noted that the predicted echo data is based on the current state of the system and the prediction of the future, and the prediction error covariance is a quantitative evaluation of the accuracy of this prediction. Specifically, in each filtering cycle, the system will first predict the DE distance of the current cycle (i.e., predicted echo data) based on the single echo data DE and the state transition matrix F, and calculate the uncertainty of the prediction (i.e., the prediction error covariance P_predict).

[0073] In a feasible implementation manner, the step S202 specifically includes:

[0074] Step B10: Obtain predicted echo data according to the state transfer matrix and the single echo data.

[0075] It should be noted that in this step, the single echo data DE refers to the obstacle distance directly measured by the ultrasonic radar, which is the raw data without filtering. The predicted echo data DE_predict refers to the predicted value of the obstacle distance at the current moment calculated by the state transfer matrix F and the last optimal estimate.

[0076] In addition, it should be noted that in this step, the system uses the preset state transfer matrix F (in this case, 1, indicating that the distance prediction value is equal to the last sensor observation value) and the single echo data (ie, DE data, representing a direct reflection result of the obstacle distance measured by the ultrasonic radar) to calculate the predicted echo data (denoted as DE_predict), as shown in Formula 1:

[0077] DE predict =F*DE(Formula 1)

[0078] It can be understood that the purpose of this step is to use the last optimal estimation result and the state transfer matrix to predict the obstacle distance at the current moment.

[0079] Step B20: Obtaining the prediction error covariance according to the state transfer matrix, the prediction system covariance and the process covariance noise.

[0080] It should be noted that in this step, the system uses the state transfer matrix F, the prediction system covariance P (representing the uncertainty of the system state prediction), and the process covariance noise Q (representing the error of the process model itself) to calculate the prediction error covariance P_predict, as shown in Formula 2:

[0081] P predict =F*P*F T +Q(Formula 2)

[0082] It can be understood that the purpose of this step is to evaluate the uncertainty of the current prediction and provide a basis for subsequent filtering updates using new observation data (PDC value).

[0083] Step S203: performing filtering and updating according to the measurement matrix, the observation noise covariance, the predicted echo data, the prediction error covariance and the parking distance control data to obtain updated echo data.

[0084] It should be noted that, specifically, the system will use the measurement matrix H, the observation noise covariance R and the prediction error covariance P_predict to calculate the Kalman gain K at the current moment. The value of K reflects the influence of the observation value (parking distance control data, i.e., PDC data) on the system state update. At the same time, the system will take the PDC data as the true value, and use the Kalman gain K and the measurement matrix H to update the predicted echo data to obtain the optimal estimate value (i.e., updated echo data DE) at the current moment.

[0085] In this embodiment, the Kalman filter method is used to effectively suppress the same-frequency interference of the ultrasonic radar in the parking scene, reduce the possibility of misjudgment and false alarm, and improve the accuracy and reliability of the parking system. At the same time, since this method only requires algorithm deployment at the software level and does not require modification of the hardware and manufacturer source code, it has low implementation cost and high versatility.

[0086] Based on the first and second embodiments of the present application, in the third embodiment of the present application, the same or similar contents as those in the first and second embodiments can be referred to the above description, and will not be described in detail later. Figure 3 , Figure 3 This is a flow chart of the third embodiment of the method for suppressing ultrasonic co-frequency interference of the present application, wherein step S203 specifically includes:

[0087] Step C10: Acquire historical parking distance control data.

[0088] It should be noted that historical parking distance control data refers to the actual distance information between the vehicle and the obstacle recorded by the PDC system in a certain period of time in the past. These data are dynamically changing and are constantly updated as the vehicle position moves and the obstacles change. It is understandable that obtaining historical parking distance control data (PDC value) is an important step in the filter update process. These data are usually provided in real time by the vehicle's parking assistance system and are used as a reference for the actual distance to calibrate and correct the primary echo (DE) data of the ultrasonic radar. Specifically, the system reads the most recent one or more PDC values ​​from the database of the parking assistance system. These values ​​represent the obstacle distance perceived by the vehicle at a specific point in time, with high accuracy and credibility.

[0089] Step C20: Obtaining a filter gain according to the measurement matrix, the observation noise covariance, and the prediction error covariance.

[0090] It should be noted that the filter gain, namely the Kalman filter gain, can be adaptively adjusted according to the dynamic changes of the observation noise and the prediction error to achieve the optimal filtering effect.

[0091] In addition, it should be noted that in this step, the system will calculate the filter gain at the current moment, that is, the Kalman filter gain K, through the Kalman filter formula according to the set measurement matrix H (usually set to 1 here, indicating that the DE value is directly related to the PDC value) and the current observation noise covariance R (indicating the noise level in the PDC value measurement), combined with the prediction error covariance P_predict (indicating the uncertainty of the DE value prediction), as shown in Formula 3:

[0092] K=P predict *HT *(H*P predict *H T +R) -1 (Formula 3)

[0093] It can be understood that the Kalman filter gain K is used to determine the relative weight between the observed value (PDC value) and the predicted value (DE value) during the updating process, so as to optimize the updated DE value.

[0094] In a feasible implementation manner, after step C20, the method further includes:

[0095] Step D10: updating the prediction system covariance according to the filter gain, the measurement matrix and the prediction error covariance to obtain an updated prediction system covariance.

[0096] It should be noted that in this step, the system will update the covariance of the prediction system by comprehensively considering the previous prediction error covariance (P_predict), the current observation noise covariance (R) and the filter gain (K) to reflect the uncertainty of the current system state. Specifically, the system will use the filter gain K, the measurement matrix H and the observation noise covariance R to calculate the updated prediction system covariance P according to the Kalman filter update equation, as shown in Formula 4:

[0097] P=(1-K*H)*P predict (Formula 4)

[0098] Step D20: updating the filter gain according to the updated prediction system covariance and the observed noise covariance.

[0099] It should be noted that in this step, the system will update the filter gain according to the updated prediction system covariance P and the observation noise covariance R, and its update process is consistent with Formula 3 in step C20, which will not be repeated here. It can be understood that updating the prediction system covariance can affect the calculation of the filter gain and the update of the state estimation in the subsequent steps.

[0100] Step C30: obtaining updated echo data according to the predicted echo data, the filter gain, the parking distance control data, the historical parking distance control data and the measurement matrix.

[0101] It should be noted that in this step, the updated echo data (i.e., the updated DE value, DE_updata) is obtained by applying the Kalman filter gain K to the predicted echo data and the parking distance control data. Specifically, the system uses the Kalman filter gain K to weight the predicted echo data (i.e., the predicted value of the DE value at the previous moment, DE_predict), and then updates it in combination with the current parking distance control data (PDC value). During the update process, the historical parking distance control data is also referenced to ensure the continuity and stability of the data, as shown in Formula 5:

[0102] DE updata =DE predict +K*(PDC-H*DE predict )(Formula 5)

[0103] In a feasible implementation manner, the step C30 specifically includes:

[0104] Step C301: When the parking distance control data is updated, update the echo data according to the parking distance control data, the predicted echo data, the filter gain and the measurement matrix.

[0105] It should be noted that in this step, when the parking distance control (PDC) data is updated, it indicates that the system has obtained new and more accurate obstacle distance information. At this time, the system will use the Kalman filter algorithm to update the single echo (DE) data of the ultrasonic radar to ensure that the actual distance of the obstacle can still be accurately reflected in the presence of co-channel interference. For example, during automatic parking, the vehicle is gradually approaching an obstacle. At a certain moment, the PDC system detected that the obstacle was 1.5 meters away from the vehicle and updated the PDC data. At this time, the system obtained the DE data of the previous frame after filtering as 1.6 meters (there is a slight co-channel interference effect). By calculating the Kalman gain K and combining the PDC true value, the system obtains an updated DE distance of 1.51 meters, which is closer to the actual distance and effectively suppresses co-channel interference.

[0106] It can be understood that this step fuses the PDC true value and the DE prediction value through the Kalman filter algorithm, effectively reducing the impact of co-channel interference on DE data and improving the accuracy and real-time performance of obstacle distance measurement.

[0107] Step C302: when the parking distance control data is not updated, replacing the parking distance control data in the updating process according to the historical parking distance control data, and updating the echo data according to the parking distance control data, the predicted echo data, the filter gain and the measurement matrix calculation.

[0108] It should be noted that when the PDC data is not updated, it means that there is no new obstacle distance information available. In order to ensure the continuity and stability of the system, the system will use the PDC data of the previous frame (ie, historical parking distance control data) as a substitute to continue the update process of DE data (echo data).

[0109] In this embodiment, by collecting past parking distance control data (i.e., PDC data) as a reference and processing and updating DE data in real time according to the Kalman filter algorithm, the interference of other same-frequency ultrasonic radar signals is effectively suppressed, and the environmental perception capability of the parking system is improved. At the same time, filtering and updating are performed using PDC data as the true value, ensuring the accuracy and real-time performance of DE data, thereby improving the overall accuracy of the parking system.

[0110] This application also provides a device for suppressing ultrasonic co-frequency interference, please refer to Figure 4 , the device for suppressing ultrasonic co-frequency interference comprises:

[0111] A data acquisition module 10 is used to acquire single echo data of the ultrasonic radar and parking distance control data;

[0112] A filtering and updating module 20, configured to filter the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data;

[0113] The parking control module 30 is used to perform parking control according to the updated echo data to suppress ultrasonic co-frequency interference.

[0114] The device for suppressing ultrasonic co-frequency interference provided by the present application adopts the method for suppressing ultrasonic co-frequency interference in the above-mentioned embodiment, and can solve the technical problem of how to suppress co-frequency interference without changing the position of the vehicle ultrasonic probe and the timing mechanism of the receiving and transmitting waves. Compared with the prior art, the beneficial effects of the device for suppressing ultrasonic co-frequency interference provided by the present application are the same as the beneficial effects of the method for suppressing ultrasonic co-frequency interference provided by the above-mentioned embodiment, and the other technical features of the device for suppressing ultrasonic co-frequency interference are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0115] In one embodiment, the filtering update module 20 is further used to initialize the state transfer matrix, the predicted system covariance, the process covariance noise, the measurement matrix and the observation noise covariance based on a preset filtering strategy; obtain the predicted echo data and the predicted error covariance according to the state transfer matrix, the predicted system covariance, the process covariance noise and at least two of the single echo data; and perform filtering and updating according to the measurement matrix, the observation noise covariance, the predicted echo data, the predicted error covariance and the parking distance control data to obtain the updated echo data.

[0116] In one embodiment, the data acquisition module 10 is further used to acquire an adjustment ratio.

[0117] In one embodiment, the filter update module 20 is further used to adjust the magnitudes of the observation noise covariance and the process covariance noise according to the adjustment ratio.

[0118] In one embodiment, the filter update module 20 is further used to obtain predicted echo data according to the state transfer matrix and the single echo data; and to obtain predicted error covariance according to the state transfer matrix, the predicted system covariance and the process covariance noise.

[0119] In one embodiment, the data acquisition module 10 is further used to acquire historical parking distance control data.

[0120] In one embodiment, the filter update module 20 is further used to obtain a filter gain based on the measurement matrix, the observation noise covariance and the prediction error covariance; and to obtain updated echo data based on the predicted echo data, the filter gain, the parking distance control data, the historical parking distance control data and the measurement matrix.

[0121] In one embodiment, the filter update module 20 is further configured to update the echo data according to the parking distance control data, the predicted echo data, the filter gain, and the measurement matrix calculation when the parking distance control data is updated; and to replace the parking distance control data in the updating process according to the historical parking distance control data when the parking distance control data is not updated, and to update the echo data according to the parking distance control data, the predicted echo data, the filter gain, and the measurement matrix calculation.

[0122] In one embodiment, the filter update module 20 is further used to update the prediction system covariance according to the filter gain, the measurement matrix and the prediction error covariance to obtain an updated prediction system covariance; and update the filter gain according to the updated prediction system covariance and the observation noise covariance.

[0123] The present application provides a device for suppressing ultrasonic co-channel interference, and the device for suppressing ultrasonic co-channel interference includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for suppressing ultrasonic co-channel interference in the above-mentioned embodiment one.

[0124] Reference below Figure 5, which shows a schematic diagram of the structure of a device for suppressing ultrasonic co-channel interference suitable for implementing the embodiment of the present application. The device for suppressing ultrasonic co-channel interference in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The device for suppressing ultrasonic co-channel interference shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0125] like Figure 5 As shown, the ultrasonic co-channel interference suppression device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the ultrasonic co-channel interference suppression device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the ultrasonic co-channel interference suppression device to communicate wirelessly or wired with other devices to exchange data. Although the ultrasonic co-channel interference suppression device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0126] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0127] The ultrasonic co-frequency interference suppression device provided by the present application adopts the ultrasonic co-frequency interference suppression method in the above embodiment, which can solve the technical problem of how to suppress co-frequency interference without changing the position of the vehicle ultrasonic probe and the timing mechanism of the receiving and transmitting waves. Compared with the prior art, the beneficial effects of the ultrasonic co-frequency interference suppression device provided by the present application are the same as the beneficial effects of the ultrasonic co-frequency interference suppression method provided by the above embodiment, and the other technical features of the ultrasonic co-frequency interference suppression device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0128] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0129] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0130] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the method for suppressing ultrasonic co-frequency interference in the above-mentioned embodiment.

[0131] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0132] The computer-readable storage medium may be included in the device for suppressing ultrasonic co-frequency interference; or may exist independently without being assembled into the device for suppressing ultrasonic co-frequency interference.

[0133] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the ultrasonic co-frequency interference suppression device, the ultrasonic co-frequency interference suppression device: obtains single echo data and parking distance control data of the ultrasonic radar; filters the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data; and performs parking control according to the updated echo data to suppress ultrasonic co-frequency interference.

[0134] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0135] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0136] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0137] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned method for suppressing ultrasonic co-frequency interference, and can solve the technical problem of how to suppress co-frequency interference without changing the position of the vehicle ultrasonic probe and the timing mechanism of the transceiver wave. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the method for suppressing ultrasonic co-frequency interference provided by the above-mentioned embodiment, and will not be repeated here.

[0138] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned method for suppressing ultrasonic co-frequency interference when executed by a processor.

[0139] The computer program product provided by the present application can solve the technical problem of how to suppress co-frequency interference without changing the position of the vehicle ultrasonic probe and the timing mechanism of the transceiver wave. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the method for suppressing ultrasonic co-frequency interference provided by the above embodiment, and will not be repeated here.

[0140] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for suppressing ultrasonic co-frequency interference, characterized in that: The method comprises: Obtain single echo data and parking distance control data of ultrasonic radar; filtering the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data; Parking control is performed according to the updated echo data to suppress ultrasonic co-frequency interference.

2. The method according to claim 1, characterized in that The step of filtering the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data comprises: Initialize the state transfer matrix, predict the system covariance, process covariance noise, measurement matrix and observation noise covariance based on the preset filtering strategy; Obtaining predicted echo data and predicted error covariance according to at least two of the state transfer matrix, the predicted system covariance, the process covariance noise, and the single echo data; Filtering and updating are performed according to the measurement matrix, the observation noise covariance, the predicted echo data, the prediction error covariance and the parking distance control data to obtain updated echo data.

3. The method according to claim 2, characterized in that After the step of initializing the state transfer matrix, predicting the system covariance, the process covariance noise, the measurement matrix and the observation noise covariance based on the preset filtering strategy, the method further includes: Get the adjustment ratio; The magnitudes of the observation noise covariance and the process covariance noise are adjusted according to the adjustment ratio.

4. The method according to claim 2, characterized in that The step of obtaining predicted echo data and predicted error covariance according to at least two of the state transfer matrix, the predicted system covariance, the process covariance noise and the single echo data comprises: Obtaining predicted echo data according to the state transfer matrix and the single echo data; The prediction error covariance is obtained according to the state transfer matrix, the prediction system covariance and the process covariance noise.

5. The method according to claim 2, characterized in that The step of filtering and updating according to the measurement matrix, the observation noise covariance, the predicted echo data, the prediction error covariance and the parking distance control data to obtain updated echo data comprises: Get historical parking distance control data; Obtaining a filter gain according to the measurement matrix, the observation noise covariance, and the prediction error covariance; Updated echo data is obtained according to the predicted echo data, the filter gain, the parking distance control data, the historical parking distance control data and the measurement matrix.

6. The method according to claim 5, characterized in that The step of obtaining updated echo data according to the predicted echo data, the filter gain, the parking distance control data, the historical parking distance control data and the measurement matrix comprises: When the parking distance control data is updated, updating the echo data according to the parking distance control data, the predicted echo data, the filter gain and the measurement matrix calculation; When the parking distance control data is not updated, the parking distance control data in the updating process is replaced according to the historical parking distance control data, and the updated echo data is calculated according to the parking distance control data, the predicted echo data, the filter gain and the measurement matrix.

7. The method according to claim 5, characterized in that After the step of obtaining the filter gain according to the measurement matrix, the observation noise covariance and the prediction error covariance, the method further includes: Update the prediction system covariance according to the filter gain, the measurement matrix and the prediction error covariance to obtain an updated prediction system covariance; The filter gain is updated according to the updated predicted system covariance and the observed noise covariance.

8. A device for suppressing ultrasonic co-frequency interference, characterized in that: The device comprises: A data acquisition module, used to acquire single echo data of ultrasonic radar and parking distance control data; A filtering update module, configured to filter the parking distance control data and the single echo data according to a preset filtering strategy to obtain updated echo data; The parking control module is used to perform parking control according to the updated echo data to suppress ultrasonic co-frequency interference.

9. A device for suppressing ultrasonic co-frequency interference, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the method for suppressing ultrasonic co-frequency interference according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the method for suppressing ultrasonic co-frequency interference as described in any one of claims 1 to 7 are implemented.

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