Signal processing method and device of vehicle and vehicle

Abstract

The invention provides a vehicle signal processing method and device and a vehicle. The vehicle signal processing method comprises the following steps: acquiring a first request signal sequence of a vehicle and a first response signal sequence corresponding to the first request signal sequence; the first request signal sequence and the first response signal sequence are time sequences; for each sequence numerical value in the first response signal sequence, adjusting the sequence numerical value according to the size relationship between other sequence numerical values in the first response signal sequence and the sequence numerical value to obtain a filtered second response signal sequence; and determining characteristic parameters of the first response signal sequence and the first request signal sequence according to the first request signal sequence and the second response signal sequence. The accuracy of analysis between the response signal and the request signal of the vehicle can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle signal processing, and particularly to a vehicle signal processing method, apparatus, and vehicle. Background Art

[0002] For autonomous vehicles, a large amount of data is generated during their R & D process and user usage. Many of these data are time series data. The analysis of vehicle functions can be completed by analyzing this data. For example, for the steering function of a vehicle, it can be determined whether the steering function of the vehicle is in a normal state by analyzing the delay, followability, etc. between the vehicle's steering request signal and steering response signal.

[0003] When analyzing these signals, it is usually necessary to filter the data to eliminate the noise of the original data. Common algorithms include: AR (Autoregressive), MA (Moving Average), ARMA (Autoregressive Moving Average), and ARIMA (Autoregressive Integrated Moving Average). However, applying these algorithms often not only eliminates noise but also has a certain impact on the original characteristics of the signal. In addition, for low-frequency signals, the positions of their extreme points also shift to a certain extent during the filtering process, interfering with signal analysis and affecting the accuracy of signal analysis. Summary of the Invention

[0004] The present application provides a vehicle signal processing method, apparatus, and vehicle with high accuracy.

[0005] The present application provides a vehicle signal processing method, including:

[0006] Obtain a first request signal sequence of the vehicle and a first response signal sequence corresponding to the first request signal sequence; both the first request signal sequence and the first response signal sequence are time series;

[0007] For each sequence value in the first response signal sequence, adjust the sequence value according to the magnitude relationship between other sequence values in the first response signal sequence and this sequence value to obtain a filtered second response signal sequence;

[0008] Determine characteristic parameters of the first response signal sequence and the first request signal sequence according to the first request signal sequence and the second response signal sequence.

[0009] Optionally, the step of, for each sequence value in the first response signal sequence, adjusting the sequence value according to the magnitude relationship between other sequence values in the first response signal sequence and this sequence value to obtain a filtered second response signal sequence includes:

[0010] For each target sequence value in the first response signal sequence, extract a preset number of sequence values before and after the target sequence value to obtain a sequence value segment;

[0011] According to the magnitude relationship between each sequence value and the previous sequence value in the sequence value segment, determine a trend sequence;

[0012] According to the pre-established correspondence between the trend sequence and the trend adjustment sequence, search for the trend adjustment sequence corresponding to the trend sequence, and obtain the filtered second response signal sequence according to the trend adjustment sequence.

[0013] Optionally, the determining of the trend sequence according to the magnitude relationship between each sequence value and the previous sequence value in the sequence value segment includes:

[0014] For each sequence value in the sequence value segment, determine the trend sequence according to the following rules:

[0015] If the sequence value is equal to the previous sequence value, in the trend sequence, the sequence value corresponding to this sequence value is the reference value;

[0016] If the sequence value is greater than the previous sequence value, in the trend sequence, the sequence value corresponding to this sequence value is the sum of the reference value and the adjustment value;

[0017] If the sequence value is less than the previous sequence value, in the trend sequence, the sequence value corresponding to this sequence value is the difference between the reference value and the adjustment value; the reference value and the adjustment value are numerical values.

[0018] Optionally, the correspondence between the trend sequence and the trend adjustment sequence is established according to the following rules:

[0019] If the trend sequence indicates that the sequence values after the target sequence value show an upward trend, establish the trend adjustment sequence according to the principle of adjusting the target sequence value to be greater than the previous sequence value and less than the next sequence value;

[0020] If the trend sequence indicates that the sequence values after the target sequence value show a downward trend, establish the trend adjustment sequence according to the principle of adjusting the target sequence value to be less than the previous sequence value and greater than the next sequence value;

[0021] If the trend sequence indicates that the sequence values after the target sequence value show a horizontal trend, establish the trend adjustment sequence according to the principle of adjusting the target sequence value to be a value between the previous sequence value and the next sequence value.

[0022] Optionally, for each sequence value in the first response signal sequence, according to the magnitude relationship between other sequence values in the first response signal sequence and this sequence value, adjusting this sequence value to obtain a filtered second response signal sequence includes:

[0023] For each target sequence value in the first response signal sequence, extracting a preset number of sequence values before and after the target sequence value to obtain a sequence value segment;

[0024] According to the magnitude relationship between each sequence value and the previous sequence value in the sequence value segment, determining a trend sequence;

[0025] According to the trend sequence and the adjustment principle, adjusting this sequence value to obtain a filtered second response signal sequence; wherein, the adjustment principle is related to the previous sequence value and / or the subsequent sequence value respectively.

[0026] Optionally, the adjustment principle includes:

[0027] If the trend sequence indicates that the previous sequence value and the subsequent sequence value of the target sequence value are equal, adjusting the target sequence value to the previous sequence value or the subsequent sequence value;

[0028] If the trend sequence indicates that the previous sequence value and the subsequent sequence value of the target sequence value are not equal, and the sequence values before and after the target sequence value both show a horizontal trend, adjusting the target sequence value to the previous sequence value or the subsequent sequence value;

[0029] If the trend sequence indicates that the previous sequence value and the subsequent sequence value of the target sequence value are not equal, and the sequence values before or after the target sequence value do not show a horizontal trend, adjusting the target sequence value to the average value of the previous sequence value and the subsequent sequence value.

[0030] Optionally, the determining the characteristic parameters of the first response signal sequence and the first request signal sequence according to the first request signal sequence and the second response signal sequence includes:

[0031] Extracting a second request signal sequence according to a preset signal sequence and the first request signal sequence;

[0032] Determining the characteristic parameters of the first response signal sequence and the first request signal sequence according to the second request signal sequence and the second response signal sequence.

[0033] Optionally, the sampling time sequence corresponding to the second request signal sequence is a first sampling time sequence;

[0034] Determining characteristic parameters of the first response signal sequence and the first request signal sequence according to the first request signal sequence and the second response signal sequence includes:

[0035] Extracting a second sampling time series according to the first sampling time series;

[0036] Intercepting a third response signal sequence from the second response signal sequence and intercepting a third request signal sequence from the second request signal sequence according to the second sampling time series;

[0037] Determining characteristic parameters of the first response signal sequence and the first request signal sequence according to the third request signal sequence and the third response signal sequence.

[0038] Optionally, determining characteristic parameters of the first response signal sequence and the first request signal sequence according to the third request signal sequence and the third response signal sequence includes:

[0039] Determining inflection points of the third request signal sequence and the third response signal sequence;

[0040] Determining a signal delay time between the first response signal and the first request signal according to a time series difference between the inflection point of the third request signal sequence and the inflection point of the third response signal sequence.

[0041] Optionally, determining inflection points of the third request signal sequence and the third response signal sequence includes:

[0042] For each target sequence value in the third request signal and the third response signal respectively, determining a trend sequence according to a magnitude relationship between the target sequence value and the previous sequence value;

[0043] Determining inflection points of the third request signal and the third response signal respectively according to the trend sequences of the third request signal and the third response signal.

[0044] This application provides a computer-readable storage medium, on which a program is stored. When the program is executed by a processor, the signal processing method of the vehicle described in any one of the above is implemented.

[0045] This application provides a signal processing device for a vehicle, including one or more processors for implementing the signal processing method of the vehicle described in any one of the above.

[0046] This application further provides a vehicle, including:

[0047] A request signal sending device;

[0048] Response signal sending device; and

[0049] The signal processing device as described above is electrically connected to the request signal sending device and the response signal sending device.

[0050] In some embodiments, for each sequence value in the first response signal sequence of the vehicle, according to the magnitude relationship between other sequence values in the first response signal sequence and this sequence value, this sequence value is adjusted to obtain a filtered second response signal sequence, so as to filter the data according to the change trend of the data; according to the first request signal sequence and the second response signal sequence, characteristic parameters of the first response signal sequence and the first request signal sequence are determined, and the characteristic parameters can reflect the characteristics of the first response signal sequence and the first request signal sequence; thus, not only can noise be eliminated during the filtering process, but also the original characteristics of the data can be maintained as much as possible, which can improve the accuracy of the analysis between the response signal and the request signal of the vehicle.

[0051] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this application. Brief Description of the Drawings

[0052] The drawings here are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application.

[0053] Figure 1 Shown is a flowchart of an embodiment of the signal processing method for a vehicle of this application.

[0054] Figure 2 Shown is a schematic diagram of an embodiment of the trend sequence of this application.

[0055] Figure 3 Shown as being related to Figure 2 Shown is a schematic diagram of an embodiment of the trend adjustment sequence corresponding to the trend sequence shown.

[0056] Figure 4 Shown is a structural block diagram of an embodiment of the signal processing device for a vehicle of this application. Detailed Embodiments

[0057] This application provides a signal processing method, device and vehicle for a vehicle. The signal processing method, device and vehicle for a vehicle of this application will be described in detail below with reference to the drawings. Without conflict, the features in the following embodiments and implementation manners can be combined with each other.

[0058] Figure 1 Shown is a flowchart of an embodiment of the signal processing method 10 for a vehicle of this application. As Figure 1As shown, the signal processing method 10 of the vehicle includes: step 11 to step 13.

[0059] Step 11, obtain a first request signal sequence of the vehicle and a first response signal sequence corresponding to the first request signal sequence. Both the first request signal sequence and the first response signal sequence are time series.

[0060] The first request signal sequence and the first response signal sequence are signal sequences related to the functions of the vehicle. For example, when it is necessary to analyze the steering function of the vehicle, the first request signal sequence is a steering request signal, and correspondingly, the first response signal is a steering response signal, that is, the actual corner signal of the vehicle; when it is necessary to analyze the door unlocking function of the vehicle, the first request signal sequence is an unlocking request signal, and the first response signal is the status signal of the door. The first request signal sequence is usually sent by the control system of the vehicle, such as the central console. The first response signal sequence is usually sent by a component of the vehicle that executes this function as a response to the first request signal sequence. By collecting the signals sent by specific components of the vehicle, the first request signal sequence and the first response signal sequence can be obtained. The first request signal sequence and the first response signal sequence are a series of signal values arranged in chronological order.

[0061] Step 12, for each sequence value in the first response signal sequence, adjust the sequence value according to the magnitude relationship between other sequence values in the first response signal sequence and this sequence value to obtain a filtered second response signal sequence.

[0062] In order to reduce the interference of noise in the first response signal sequence, it is necessary to perform filtering processing on the first response signal sequence. Filter the first response signal sequence according to the magnitude relationship of the sequence values in the first response signal sequence. For example, if a certain sequence value is significantly higher or lower than its surrounding sequence values, this sequence value may be noise or an outlier, and adjust this sequence value, such as smoothing processing, removing or replacing this sequence value. The resulting second response signal sequence more accurately reflects the true trend or pattern of the response signal. Filtering based on the magnitude relationship between each data and its surrounding data without directly applying a filter can improve the filtering accuracy, prevent the introduction of new noise, and retain the characteristics of the original data as much as possible.

[0063] Step 13, determine the characteristic parameters of the first response signal sequence and the first request signal sequence according to the first request signal sequence and the second response signal sequence.

[0064] The characteristic parameters may include the amplitude, frequency, phase, duration, etc. of the signal, and can describe the basic characteristics of the signal. According to the first request signal sequence and the second response signal sequence, the characteristics of the first request signal sequence and the second response signal sequence are analyzed, and then the characteristic parameters of the first response signal sequence and the first request signal sequence can be determined, such as the delay, followability, etc. between the first response signal sequence and the first request signal sequence, to complete the analysis of the corresponding functions of the vehicle. Since the second response signal sequence weakens the noise and tries to retain the characteristics of the first response signal sequence, determining the characteristic parameters according to the first request signal sequence and the second response signal sequence can improve the accuracy of signal analysis.

[0065] In some embodiments, for each sequence value in the first response signal sequence of the vehicle, according to the magnitude relationship between other sequence values in the first response signal sequence and this sequence value, this sequence value is adjusted to obtain the filtered second response signal sequence, so as to filter the data according to the change trend of the data; according to the first request signal sequence and the second response signal sequence, the characteristic parameters of the first response signal sequence and the first request signal sequence are determined, and the characteristic parameters can reflect the characteristics of the first response signal sequence and the first request signal sequence; thus, not only can noise be eliminated during the filtering process, but also the original characteristics of the data can be maintained as much as possible, which can improve the accuracy of the analysis between the response signal and the request signal of the vehicle.

[0066] In some embodiments, step 12 includes:

[0067] For each target sequence value in the first response signal sequence, a preset number of sequence values before and after the target sequence value are extracted to obtain a sequence value segment;

[0068] According to the magnitude relationship between each sequence value and the previous sequence value in the sequence value segment, a trend sequence is determined;

[0069] According to the pre-established correspondence between the trend sequence and the trend adjustment sequence, the trend adjustment sequence corresponding to the trend sequence is searched, and according to the trend adjustment sequence, the filtered second response signal sequence is obtained.

[0070] For each sequence value in the first response signal sequence, filtering is required. When filtering a certain sequence value, that sequence value is the target sequence value. The sequence value segment includes the target sequence value and a preset number of sequence values before and after the target sequence value in chronological order. The number of sequence values before and after the target sequence value can be equal or unequal. For example, the preset number is 2, and the target sequence value is 1.5. Two sequence values before and after this value are extracted respectively to form the sequence value segment [2, 1.8, 1.5, 1, 1]. The sequence value segment is to extract the change trend of the sequence segment where the target sequence value is located.

[0071] In the obtained sequence value segment, analyze the magnitude relationship between each sequence value and its previous sequence value. If the current value is greater than the previous value, it is recorded as an upward trend; if it is less, it is recorded as a downward trend; if they are equal, it can be recorded as a stable trend. In this way, the original numerical sequence can be converted into a sequence describing the trend, that is, the trend sequence.

[0072] In some embodiments, determining the trend sequence according to the magnitude relationship between each sequence value and the previous sequence value in the sequence value segment includes:

[0073] For each sequence value in the sequence value segment, determine the trend sequence according to the following rules:

[0074] If the sequence value is equal to the previous sequence value, in the trend sequence, the sequence value corresponding to this sequence value is the reference value;

[0075] If the sequence value is greater than the previous sequence value, in the trend sequence, the sequence value corresponding to this sequence value is the sum of the reference value and the adjustment value;

[0076] If the sequence value is less than the previous sequence value, in the trend sequence, the sequence value corresponding to this sequence value is the difference between the reference value and the adjustment value; where the reference value is a numerical value.

[0077] In the sequence value segment, for the first data, since there is no data before it, the data corresponding to the first data in the trend sequence can be set as the reference value.

[0078] The reference value is a fixed value, which is used to represent the situation where there is no change in the current sequence value compared with the previous sequence value. The adjustment value is used to represent the situation where the current sequence value changes compared with the previous sequence value. The reference value and the adjustment value can be set as needed. For example, let the reference value be 0 and the adjustment value be 1. For each sequence value in the sequence value segment, if the sequence value is equal to the previous sequence value, in the trend sequence, the sequence value at the corresponding position of this sequence value is 0; if the sequence value is greater than the previous sequence value, in the trend sequence, the sequence value at the corresponding position of this sequence value is 1; if the sequence value is less than the previous sequence value, in the trend sequence, the sequence value at the corresponding position of this sequence value is -1. For example, for the sequence value segment [2, 1.8, 1.5, 1, 1], the trend sequence is [0, -1, -1, -1, 0].

[0079] The corresponding relationship between the trend sequence and the trend adjustment sequence is established in advance, which can be obtained based on experience, statistical models or machine learning algorithms, and is used to define a more ideal and smoother trend adjustment sequence according to the characteristics of the trend sequence. For each possible trend sequence, there is a corresponding trend adjustment sequence. When establishing the corresponding relationship, the trend sequences are enumerated to ensure that all sequence value segments can be adjusted using the trend adjustment sequence. According to the pre-established corresponding relationship between the trend sequence and the trend adjustment sequence, the adjustment strategy for the target sequence value can be quickly obtained, improving the signal processing speed.

[0080] According to the found trend adjustment sequence, the original first response signal sequence can be adjusted to obtain the filtered second response signal sequence. The second response signal sequence retains the characteristics of the first response signal sequence while reducing noise, making the signal clearer and easier to analyze and utilize.

[0081] In some embodiments, the corresponding relationship between the trend sequence and the trend adjustment sequence is established according to the following rules:

[0082] If the trend sequence indicates that the sequence values after the target sequence value show an upward trend, the trend adjustment sequence is established according to the principle of adjusting the target sequence value to be greater than the previous sequence value and less than the next sequence value;

[0083] If the trend sequence indicates that the sequence values after the target sequence value show a downward trend, the trend adjustment sequence is established according to the principle of adjusting the target sequence value to be less than the previous sequence value and greater than the next sequence value;

[0084] If the trend sequence indicates that the sequence values after the target sequence value show a horizontal trend, the trend adjustment sequence is established according to the principle of adjusting the target sequence value to be a value between the previous sequence value and the next sequence value.

[0085] If the trend sequence indicates that the values after the target sequence value show an upward trend, then adjust the target sequence value to a value that is greater than the sequence value before it and less than the sequence value after it. This can maintain the continuity of the upward trend in the original data sequence segment and make the target sequence value more conform to this trend.

[0086] If the trend sequence indicates that the values after the target sequence value show a downward trend, then adjust the target sequence value to a value that is less than the sequence value before it and greater than the sequence value after it. This can maintain the continuity of the downward trend in the original data sequence segment and make the target sequence value more conform to this trend.

[0087] If the trend sequence indicates that the values after the target sequence value show a horizontal trend, then adjust the target sequence value to a value between the sequence value before it and the sequence value after it. For example, the average value of the sequence value before it and the sequence value after it. This can maintain the stability of the horizontal trend in the original data sequence segment and make the target sequence value more conform to this trend.

[0088] Adjust the specific target sequence value according to the trend in the original data sequence segment, thereby constructing a new trend-adjusted sequence. According to the trend-adjusted sequence, adjust the first response signal sequence, and the obtained second response signal sequence not only retains the trend information of the data in the first response signal sequence but also weakens the noise.

[0089] Figure 2 The figure shows a schematic diagram of an embodiment of the trend sequence of the present application.

[0090] Figure 3 The figure shows the one corresponding to Figure 2 The figure shows a schematic diagram of an embodiment of the trend-adjusted sequence corresponding to the shown trend sequence.

[0091] In Figure 2 and Figure 3 , the sequence value segment includes 5 data, and the 3rd data is the target sequence value. The direction of the line segment represents the change trend of the data. For example, for Figure 2 in the first row and the first column, the line segment is horizontal, indicating that the data has not changed. Correspondingly, Figure 3 the first row and the first column in is the corresponding trend-adjusted sequence, also horizontal, indicating that no adjustment is required for the data. For Figure 2 in the first row and the second column, the line segment first descends and then ascends, indicating that the 3rd data, that is, the target sequence value, is less than the sequence values before and after it, Figure 3The second column in the first row is the corresponding trend adjustment sequence, which is horizontal, indicating that the target sequence value is adjusted to a value equal to the sequence values before and after it, thereby smoothing the signal.

[0092] In some other embodiments, step 12 includes:

[0093] For each target sequence value in the first response signal sequence, a preset number of sequence values before and after the target sequence value are extracted to obtain a sequence value segment;

[0094] According to the size relationship between each sequence value and the previous sequence value in the sequence value segment, a trend sequence is determined;

[0095] According to the trend sequence and the adjustment principle, the sequence value is adjusted to obtain the filtered second response signal sequence; wherein, the adjustment principle is related to the previous sequence value and / or the subsequent sequence value respectively.

[0096] The adjustment principle is a rule formulated based on the trend sequence, which is used to adjust the sequence value to reduce the influence of noise or outliers. The adjustment principle can be related to the previous sequence value and / or the subsequent sequence value, and the adjustment principle is set according to the size relationship between the target sequence value and the previous sequence value and / or the subsequent sequence value.

[0097] In some embodiments, the adjustment principle includes:

[0098] If the trend sequence indicates that the previous sequence value and the subsequent sequence value of the target sequence value are equal, the target sequence value is adjusted to the previous sequence value or the subsequent sequence value;

[0099] If the trend sequence indicates that the previous sequence value and the subsequent sequence value of the target sequence value are not equal, and the sequence values before and after the target sequence value both show a horizontal trend, the target sequence value is adjusted to the previous sequence value or the subsequent sequence value;

[0100] If the trend sequence indicates that the previous sequence value and the subsequent sequence value of the target sequence value are not equal, and the sequence values before or after the target sequence value do not show a horizontal trend, the target sequence value is adjusted to the average of the previous sequence value and the subsequent sequence value.

[0101] When the trend sequence shows that the previous sequence value and the subsequent sequence value of the target sequence value are equal, it indicates that the target sequence value is at a local point of a stable or horizontal trend. To maintain this stability, the target sequence value is adjusted to the previous sequence value or the subsequent sequence value equal to it. This can help eliminate possible small fluctuations or noise.

[0102] When the value of the target sequence itself is not equal to the values of its preceding and succeeding sequences, but the values of its preceding and succeeding sequences both exhibit a horizontal trend (i.e., there is no significant upward or downward trend), it indicates that the value of the target sequence may be an outlier or a noise point. To maintain overall smoothness, the value of the target sequence is adjusted to the value of the preceding or succeeding sequence that is adjacent to it and exhibits a horizontal trend. This can help reduce the impact of outliers on the overall trend.

[0103] When the value of the target sequence is not equal to the values of its preceding and succeeding sequences, and the values of its preceding and succeeding sequences do not exhibit a horizontal trend, it indicates that the value of the target sequence is at a turning point or a midpoint of an upward or downward trend. To maintain the continuity of this trend, the value of the target sequence is adjusted to the average of the value of the preceding sequence and the value of the succeeding sequence. This can help with smooth transition and reduce the interference caused to the overall trend by the mutation of a single value.

[0104] Based on the analysis results of the trend sequence, smooth processing is performed on the values of the target sequence to reduce the impact of noise, outliers, or mutation points on the overall trend. By selecting an appropriate adjustment method, the continuity and reliability of the signal can be maintained, and the accuracy and credibility of data analysis can be improved.

[0105] In some embodiments, step 13 includes:

[0106] Extract a second request signal sequence according to a preset signal sequence and a first request signal sequence;

[0107] Determine the characteristic parameters of the first response signal sequence and the first request signal sequence according to the second request signal sequence and the second response signal sequence.

[0108] The preset signal sequence is a pre-defined signal sequence. Since the first request signal sequence may contain excessive information, according to the preset signal sequence and the first request signal sequence, the second request signal sequence that needs to be analyzed can be extracted. The second request signal sequence is more concise and contains the signal segments that need to be analyzed. Specifically, the preset signal sequence can be used as a convolution kernel to perform convolution on the first request signal sequence to obtain the second request signal sequence. According to the second request signal sequence and the second response signal sequence, the characteristic parameters of the first response signal sequence and the first request signal sequence can be analyzed more quickly.

[0109] In some embodiments, the sampling time sequence corresponding to the second request signal sequence is the first sampling time sequence;

[0110] The determining the characteristic parameters of the first response signal sequence and the first request signal sequence according to the first request signal sequence and the second response signal sequence includes:

[0111] Extract a second sampling time sequence according to the first sampling time sequence;

[0112] Based on the second sampling time series, a third response signal sequence is intercepted from the second response signal sequence, and a third request signal sequence is intercepted from the second request signal sequence;

[0113] Based on the third request signal sequence and the third response signal sequence, determine the characteristic parameters of the first response signal sequence and the first request signal sequence.

[0114] Based on the first sampling time series, combined with the characteristics of the vehicle functions corresponding to the first request signal sequence and the second response signal sequence, appropriately window the first sampling time series to obtain the second sampling time series. Using the second sampling time series as a window, a third response signal sequence is intercepted from the second response signal sequence, and a third request signal sequence is intercepted from the second request signal sequence. In this way, a specific signal sequence that requires more attention can be obtained to analyze the signal more accurately.

[0115] In some embodiments, the determining the characteristic parameters of the first response signal sequence and the first request signal sequence based on the third request signal sequence and the third response signal sequence includes:

[0116] Determine the inflection points of the third request signal sequence and the third response signal sequence;

[0117] Based on the time series difference between the inflection point of the third request signal sequence and the inflection point of the third response signal sequence, determine the signal delay time between the first response signal and the first request signal.

[0118] An inflection point is a point where the signal changes significantly (such as a change in direction, a change in rate, etc.). The method for determining the inflection point includes finding the extreme points of the signal, the points with a significant change in slope, or using specific signal processing algorithms to identify.

[0119] The characteristic parameters include the signal delay time, which refers to the time interval from when the request signal is sent to when the response signal starts to be received. The signal delay time is estimated by calculating the time series difference between the inflection point of the third request signal sequence and the inflection point of the third response signal sequence.

[0120] The signal delay time can be used to evaluate the response speed of the communication system, optimize the system performance, and diagnose potential problems.

[0121] In some embodiments, the determining the inflection points of the third request signal sequence and the third response signal sequence includes:

[0122] For each target sequence value in the third request signal and the third response signal respectively, determine the trend sequence according to the magnitude relationship between the target sequence value and the previous sequence value;

[0123] Determine the inflection points of the third request signal and the third response signal respectively according to the trend sequences of the third request signal and the third response signal.

[0124] The method for determining the trend sequence is as described above and will not be elaborated here. The inflection points of the signal can be determined according to the extreme points and the points with significant slope changes in the trend sequence. For example, if the trend sequence is [1, 1, 1, 0, 0, 0], the point where it changes from 1 to 0 is the inflection point. Through the trend sequence, the inflection points of the signal can be determined simply and quickly.

[0125] Figure 4 The following shows a structural block diagram of an embodiment of the signal processing device of the vehicle of the present application.

[0126] As Figure 4 shown, the signal processing device of the vehicle includes one or more processors 21 for implementing the vehicle signal processing method 10 as described above.

[0127] In some embodiments, the signal processing device may include a computer-readable storage medium 22. The computer-readable storage medium 22 may store a program that can be called by the processor 21 and may include a non-volatile storage medium. In some embodiments, the signal processing device may include a memory 23 and an interface 24. In some embodiments, the signal processing device may also include other hardware according to actual applications.

[0128] The computer-readable storage medium 22 of the embodiment of the present application stores a program thereon. When the program is executed by the processor 21, it is used to implement the vehicle signal processing method 10 described above.

[0129] The present application may be in the form of a computer program product implemented on one or more computer-readable storage media 22 (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing program codes. The computer-readable storage medium 22 includes permanent and non-permanent, removable and non-removable media and can implement information storage by any method or technology. The information may be computer-readable instructions, data structures, program modules or other data. Examples of the computer-readable storage medium 22 include but are not limited to: phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information accessible by a computing device.

[0130] The present application also provides a vehicle, comprising: a request signal sending device, a response signal sending device, and the signal processing device as described above. The signal processing device is electrically connected to the request signal sending device and the response signal sending device, and is configured to collect the electrical signals of the request signal sending device and the response signal sending device, and execute the signal processing method 10 of the vehicle as described above.

Claims

1. A vehicle signal processing method, characterized in that: include: Acquire a first request signal sequence of the vehicle and a first response signal sequence corresponding to the first request signal sequence; The first request signal sequence and the first response signal sequence are both time series; For each sequence value in the first response signal sequence, adjusting the sequence value according to a magnitude relationship between other sequence values ​​in the first response signal sequence and the sequence value, to obtain a filtered second response signal sequence; Characteristic parameters of the first response signal sequence and the first request signal sequence are determined according to the first request signal sequence and the second response signal sequence.

2. The vehicle signal processing method according to claim 1, characterized in that: The step of adjusting each sequence value in the first response signal sequence according to a magnitude relationship between other sequence values ​​in the first response signal sequence and the sequence value to obtain a filtered second response signal sequence includes: For each target sequence value in the first response signal sequence, extract a preset number of sequence values ​​located before and after the target sequence value to obtain a sequence value segment; Determine a trend sequence according to the magnitude relationship between each sequence value and the previous sequence value in the sequence value segment; According to the pre-established correspondence between the trend sequence and the trend adjustment sequence, the trend adjustment sequence corresponding to the trend sequence is searched, and the filtered second response signal sequence is obtained according to the trend adjustment sequence.

3. The vehicle signal processing method according to claim 2, characterized in that: Determining the trend sequence according to the magnitude relationship between each sequence value and the previous sequence value in the sequence value segment includes: For each sequence value in the sequence value segment, a trend sequence is determined according to the following rules: If the sequence value is equal to the previous sequence value, the sequence value at the corresponding position in the trend sequence is the base value; If the sequence value is greater than the previous sequence value, in the trend sequence, the sequence value at the position corresponding to the sequence value is the sum of the base value and the adjustment value; If the sequence value is less than the previous sequence value, in the trend sequence, the sequence value at the position corresponding to the sequence value is the difference between the reference value and the adjustment value; the reference value and the adjustment value are numerical values.

4. The vehicle signal processing method according to claim 2, characterized in that: The corresponding relationship between the trend sequence and the trend adjustment sequence is established according to the following rules: If the trend sequence indicates that the sequence value after the target sequence value is on an upward trend, the trend adjustment sequence is established according to the principle of adjusting the target sequence value to be greater than the previous sequence value and less than the next sequence value; If the trend sequence indicates that the sequence value after the target sequence value is in a downward trend, the trend adjustment sequence is established according to the principle of adjusting the target sequence value to be smaller than the previous sequence value and larger than the next sequence value; If the trend sequence indicates that the sequence value after the target sequence value is in a horizontal trend, the trend adjustment sequence is established according to the principle of adjusting the target sequence value to a value between the previous sequence value and the next sequence value.

5. The vehicle signal processing method according to claim 1, characterized in that: The step of adjusting each sequence value in the first response signal sequence according to a magnitude relationship between other sequence values ​​in the first response signal sequence and the sequence value to obtain a filtered second response signal sequence includes: For each target sequence value in the first response signal sequence, extract a preset number of sequence values ​​located before and after the target sequence value to obtain a sequence value segment; Determine a trend sequence according to the magnitude relationship between each sequence value and the previous sequence value in the sequence value segment; According to the trend sequence and the adjustment principle, the sequence value is adjusted to obtain a filtered second response signal sequence; wherein the adjustment principle is respectively related to the previous sequence value and / or the next sequence value.

6. The vehicle signal processing method according to claim 5, characterized in that: The adjustment principles include: If the trend sequence indicates that the previous sequence value and the next sequence value of the target sequence value are equal, the target sequence value is adjusted to the previous sequence value or the next sequence value; If the trend sequence indicates that the previous sequence value and the next sequence value of the target sequence value are not equal, and the sequence values ​​before and after the target sequence value both show a horizontal trend, the target sequence value is adjusted to the previous sequence value or the next sequence value; If the trend sequence indicates that the previous sequence value and the subsequent sequence value of the target sequence value are not equal, and the sequence values ​​before or after the target sequence value do not show a horizontal trend, the target sequence value is adjusted to the average of the previous sequence value and the subsequent sequence value.

7. The vehicle signal processing method according to claim 1, characterized in that: The determining, according to the first request signal sequence and the second response signal sequence, characteristic parameters of the first response signal sequence and the first request signal sequence comprises: Extracting a second request signal sequence according to a preset signal sequence and the first request signal sequence; Characteristic parameters of the first response signal sequence and the first request signal sequence are determined according to the second request signal sequence and the second response signal sequence.

8. The vehicle signal processing method according to claim 7, characterized in that: The sampling time sequence corresponding to the second request signal sequence is the first sampling time sequence; The determining, according to the first request signal sequence and the second response signal sequence, characteristic parameters of the first response signal sequence and the first request signal sequence comprises: Extracting a second sampling time series according to the first sampling time series; According to the second sampling time sequence, a third response signal sequence is intercepted from the second response signal sequence, and a third request signal sequence is intercepted from the second request signal sequence; Characteristic parameters of the first response signal sequence and the first request signal sequence are determined according to the third request signal sequence and the third response signal sequence.

9. The vehicle signal processing method according to claim 8, characterized in that: The determining, according to the third request signal sequence and the third response signal sequence, characteristic parameters of the first response signal sequence and the first request signal sequence comprises: determining inflection points of the third request signal sequence and the third response signal sequence; The signal delay time between the first response signal and the first request signal is determined according to a time series difference between an inflection point of the third request signal sequence and an inflection point of the third response signal sequence.

10. The vehicle signal processing method according to claim 9, characterized in that: The determining of the inflection points of the third request signal sequence and the third response signal sequence comprises: For each target sequence value in the third request signal and the third response signal, determine a trend sequence according to a magnitude relationship between the target sequence value and a previous sequence value; According to the trend sequences of the third request signal and the third response signal, inflection points of the third request signal and the third response signal are determined respectively.

11. A computer-readable storage medium, characterized in that: A program is stored thereon, and when the program is executed by a processor, the signal processing method for a vehicle described in any one of claims 1 to 10 is implemented.

12. A signal processing device for a vehicle, characterized in that: The method comprises one or more processors for implementing the vehicle signal processing method according to any one of claims 1 to 10.

13. A vehicle, characterized in that: include: request signal sending device; a response signal sending device; and The signal processing device according to claim 12 is electrically connected to the request signal sending device and the response signal sending device.

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