Pulse-shaped signal centroid detection method and device, electronic equipment and storage medium
By dynamically determining the length of the pulse-shaped signal center of mass window, the problem of the traditional center of mass window algorithm deteriorating the accuracy of center of mass calculation under different signal intensities is solved, and a higher center of mass detection accuracy is achieved.
Patent Information
- Application Number
- CN202311775154.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-12-21
- Publication Date
- 2025-06-24
AI Technical Summary
When calculating pulse-shaped signal center of mass, the use of fixed-length windows may cause the accuracy of center of mass calculation of signals of different intensities to decrease.
By obtaining the signal parameters of the pulse-shaped signal, dynamically determine the length of the center of mass window, setting a critical threshold according to the intensity level of the signal parameters, and finding the starting point and ending point of the center of mass window, so as to flexibly configure the center of mass window.
The accuracy of calculating the pulse-shaped signal center of mass is improved, and the length of the centroid window of different signal intensities is adapted to improve the distance measurement repetition accuracy.
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Figure CN120195654A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of signal processing, and in particular, to a method, device, electronic device, and storage medium for detecting the centroid of a pulsed signal. Background Art
[0002] In the scenario of lidar ranging, it is generally necessary to analyze and process the echo signal, calculate the centroid of the echo signal, so as to improve the ranging repetition accuracy. The echo signal of lidar belongs to a kind of pulsed signal. At present, the centroid window algorithm is usually used to detect the centroid of the pulsed signal. The basic principle of the traditional centroid window algorithm is to intercept a window with a fixed length in the pulsed signal, called the centroid window, and then calculate the centroid of the pulsed signal according to all the signal points in the centroid window. However, for signals with different intensities, their durations may be different. If the centroid window with the same length is used to calculate the centroid, the problem of decreased accuracy in calculating the centroid may occur. Summary of the Invention
[0003] In view of this, the embodiments of this application provide a method, device, electronic device, and storage medium for detecting the centroid of a pulsed signal, which can improve the accuracy of calculating the centroid of the pulsed signal.
[0004] The first aspect of the embodiments of this application provides a method for detecting the centroid of a pulsed signal, including:
[0005] Obtain the signal parameters of the pulsed signal;
[0006] Determine the centroid window of the pulsed signal according to the signal parameters;
[0007] Calculate the centroid of the pulsed signal according to all the signal points in the centroid window.
[0008] The embodiments of this application propose an improved centroid window algorithm. First, obtain the signal parameters of the pulsed signal, such as parameters like signal-to-noise ratio, signal peak value, and signal energy. Then, determine the centroid window of the pulsed signal according to the signal parameters. Finally, calculate the centroid of the pulsed signal according to all the signal points in the centroid window. Compared with the traditional centroid window algorithm, the centroid window in the embodiments of this application is no longer a window with a fixed length, but a window with higher adaptability that can be flexibly configured according to the signal parameters of the pulsed signal. Therefore, it can improve the accuracy of calculating the centroid of the pulsed signal.
[0009] In an implementation manner of the embodiments of this application, determining the centroid window of the pulsed signal according to the signal parameters includes:
[0010] Determine the critical threshold according to the signal parameters;
[0011] Based on a critical threshold, search for the starting point and ending point of the centroid window on both sides of the signal peak of the pulsed signal respectively.
[0012] In one implementation manner of the embodiment of the present application, determining the critical threshold according to the signal parameters includes:
[0013] Determine the signal strength level of the pulsed signal according to the signal parameters;
[0014] Determine the critical threshold according to the signal strength level.
[0015] In one implementation manner of the embodiment of the present application, determining the signal strength level of the pulsed signal according to the signal parameters includes:
[0016] Determine each demarcation threshold according to the type of the signal parameters;
[0017] Determine the signal strength level according to the magnitude relationship between the value of the signal parameters and each demarcation threshold.
[0018] In one implementation manner of the embodiment of the present application, determining the critical threshold according to the signal strength level includes:
[0019] Determine the target coefficient according to the signal strength level; wherein, the target coefficient is inversely proportional to the signal strength level;
[0020] Calculate the critical threshold according to the target coefficient and the amplitude of the signal peak.
[0021] In one implementation manner of the embodiment of the present application, based on the critical threshold, search for the starting point and ending point of the centroid window on both sides of the signal peak of the pulsed signal respectively, including:
[0022] Taking the signal peak as the center, search for the position point on the left side of the center where the signal amplitude is greater than the critical threshold and the signal amplitude at the adjacent position on the left is less than the critical threshold as the starting point of the centroid window, and search for the position point on the right side of the center where the signal amplitude is greater than the critical threshold and the signal amplitude at the adjacent position on the right is less than the critical threshold as the ending point of the centroid window.
[0023] In one implementation manner of the embodiment of the present application, the signal parameters are signal-to-noise ratio, signal peak value or signal energy.
[0024] The second aspect of the embodiment of the present application provides a centroid detection device for a pulsed signal, including:
[0025] A signal parameter acquisition module, configured to acquire the signal parameters of the pulsed signal;
[0026] A centroid window determination module, configured to determine the centroid window of the pulsed signal according to the signal parameters;
[0027] A centroid calculation module, configured to calculate the centroid of a pulsed signal based on all signal points within a centroid window.
[0028] A third aspect of the embodiments of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the centroid detection method for pulsed signals provided in the first aspect of the embodiments of the present application is implemented.
[0029] A fourth aspect of the embodiments of the present application provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the centroid detection method for pulsed signals provided in the first aspect of the embodiments of the present application is implemented.
[0030] A fifth aspect of the embodiments of the present application provides a computer program product. When the computer program product runs on an electronic device, the electronic device is caused to execute the centroid detection method for pulsed signals provided in the first aspect of the embodiments of the present application.
[0031] It can be understood that the beneficial effects of the above second to fifth aspects can be referred to the relevant descriptions in the first aspect above, and will not be elaborated here. Description of the Drawings
[0032] Figure 1 is a flowchart of a centroid detection method for a pulsed signal provided by an embodiment of the present application;
[0033] Figure 2 is a schematic diagram of the effect of using a centroid window with a fixed length to intercept a pulsed signal provided by an embodiment of the present application;
[0034] Figure 3 is a schematic diagram of the effect of selecting a critical threshold for a pulsed signal provided by an embodiment of the present application;
[0035] Figure 4 is a schematic structural diagram of a centroid detection device for a pulsed signal provided by an embodiment of the present application;
[0036] Figure 5 is a schematic diagram of an electronic device provided by an embodiment of the present application. Detailed Embodiments
[0037] In the following description, specific details such as specific system architectures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application. Additionally, in the description of the specification and claims of the present application, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and should not be construed as indicating or implying relative importance.
[0038] Currently, when analyzing the echo signal of a lidar, the centroid window algorithm is usually used to detect the centroid of the echo signal. The basic principle of the traditional centroid window algorithm is to intercept a centroid window with a fixed length in a pulse-like signal, and calculate the centroid of the pulse-like signal based on all the signal points within the centroid window. However, for signals with different intensities, their durations may be different. If a centroid window with the same length is used to calculate the centroid, there may be a problem of decreased accuracy in calculating the centroid.
[0039] In view of the above problems existing in the prior art, the embodiments of the present application provide a method, device, electronic device, and storage medium for detecting the centroid of a pulse-like signal, which can improve the accuracy of calculating the centroid of the pulse-like signal. For more specific technical implementation details of the embodiments of the present application, please refer to the following various embodiments.
[0040] It should be understood that the execution subject of each method embodiment of the present application is various types of electronic devices, such as mobile phones, tablet computers, wearable devices, in-vehicle devices, signal analysis devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), large-screen TVs, and so on. The embodiments of the present application do not impose any restrictions on the specific types of these electronic devices.
[0041] Please refer to Figure 1 , which shows a method for detecting the centroid of a pulse-like signal provided by an embodiment of the present application, including:
[0042] 101. Obtain the signal parameters of the pulse-like signal;
[0043] First, obtain a pulsed signal, which is a signal of any type of pulse shape for which the centroid needs to be detected. For example, it can be the echo signal of a lidar. The waveform of the pulsed signal generally has a convex middle forming a signal peak and concave sides. It should be noted that the method described in the embodiments of this application for detecting the centroid of a single pulsed waveform. If the signal to be measured contains multiple pulsed waveforms, the centroid window of each pulsed waveform can be determined in the same way, and then the centroid of each can be calculated separately.
[0044] After obtaining the pulsed signal, detect its signal parameters, which are mainly used to determine the signal intensity level of the pulsed signal, so as to select a centroid window adapted to this signal intensity level. Specifically, the signal parameters can be the signal-to-noise ratio, signal peak value, signal energy, etc. The specific methods for detecting these signal parameters can refer to the prior art and will not be elaborated here.
[0045] 102. Determine the centroid window of the pulsed signal according to the signal parameters;
[0046] The following explains the disadvantages of the traditional centroid window algorithm using a centroid window of fixed length. As Figure 2 shown, it is a schematic diagram of the effect of using a centroid window of fixed length to intercept a pulsed signal. In Figure 2 , two pulsed signals of different signal intensity levels are shown. The signal intensity level of signal 1 is higher than that of signal 2. It can be seen that the amplitude of the signal peak of signal 1 is much larger than that of signal 2. Through Figure 2 it can be seen that when using a centroid window of fixed length, the weak signal (signal 2) has almost intercepted the complete pulse, while the strong signal (signal 1) obviously has not intercepted the complete pulse. In addition, the system noise does not change due to the signal strength. Therefore, it is unreasonable to use the same centroid window to intercept pulsed signals of different signal intensity levels. That is, the ratio of strong and weak signals contained in this centroid window is different. Through Figure 2 it can be seen that it is necessary to dynamically control the window length according to the duration of the strong and weak signals, that is, use a smaller centroid window for the weak signal with a short duration, and use a larger centroid window for the strong signal with a long duration.
[0047] To solve the above disadvantages of the traditional centroid window algorithm, the embodiments of this application propose an improved dynamic centroid window algorithm. After obtaining the signal parameters of the pulsed signal, determine the centroid window of the pulsed signal according to the signal parameters. That is, the centroid windows determined for pulsed signals with different signal parameters are different. For example, different centroid window lengths can be set for strong and weak signals respectively, so as to obtain a centroid window with a higher degree of suitability, thereby improving the accuracy of calculating the signal centroid.
[0048] In the dynamic centroid window algorithm proposed in the embodiments of the present application, the key part is the selection of the centroid window length, and whether the selection is reasonable directly affects the accuracy of the centroid calculation result. For the centroid solution of pulsed signals, the optimal centroid window generally needs to meet the following two conditions: (1) The centroid window length should contain all the information of the signal; (2) The ratio of the signal energy to the noise energy within the centroid window length is the largest. The following explains why the centroid window that meets these two conditions is the optimal centroid window.
[0049] Generally speaking, for the strong / weak echo signals in the time domain or frequency domain of lidar in the form of pulses, there is a strong linear correlation between their waveform shapes, that is, the conversion between strong and weak signals can be achieved by controlling the coefficient before the signal. For example, it can be set that the signal waveform a = coefficient p * signal waveform b, and different intensity signals can be obtained by controlling the coefficient p.
[0050] Suppose a set of waveforms is y i (i = 1...K, where K is the total length of the waveform), x i is the index sequence corresponding to y i , and the specific value of x i is related to the attributes of the signal being analyzed. For example, if the echo signal is a time-domain signal, then x i can be time or a digital index sequence, etc. If it is a frequency-domain signal, it can be frequency or a digital index sequence, etc. Suppose y i is composed of random noise N i and signal S i , that is, y i = N i + S i , then when the length of the centroid window centered on the digital index A corresponding to the signal peak is 2*m, the centroid calculation result result is:
[0051]
[0052] Among them, the first term simplifies to which represents the mean of the index sequence within the centroid window. When the length of the centroid window is fixed, is also a fixed value. The second term is considered to be the contribution term of the signal, and the third term is considered to be the contribution term of the noise. If the noise is zero, that is, N i = 0, then the third term is equal to 0, that is, only the first term and the second term remain. The first term is the mean of the index sequence and does not introduce the calculation of the waveform amplitude. Then, if you want to accurately reflect the centroid of the signal, only the summation interval of the second term needs to contain all the information of the signal. For the signals in practical applications, their duration can be considered finite. Therefore, when the noise is 0, the optimal window length is the duration length of the signal. When noise is included, the noise will interfere with the centroid result; from the above formula, Ni It exists in the denominator and cannot be infinitely large. The last two terms are both summations. When S i > N i At this time, the contribution of the signal is large. When S i < N i At this time, the contribution of the noise is large. Therefore, S i and N i within the window satisfy S i > N i , which is equivalent to when the signal energy / noise energy is the largest, the obtained centroid window is the optimal one.
[0053] However, the measured signals are often noisy, and it is difficult to obtain pure noise-free signals. Therefore, it is difficult to measure the ratio of signal energy to noise energy. Therefore, based on the above theoretical derivation and combined with the actual application situation, an algorithm is designed to make the algorithm include the complete information of the signal to the greatest extent while introducing as little noise as possible. Therefore, in the following text, the method of jointly determining the critical threshold by the target coefficient and the signal peak value is used to determine the optimal centroid window of the signal at each intensity level.
[0054] In an implementation manner of the embodiment of the present application, according to the signal parameters, determining the centroid window of the pulsed signal includes:
[0055] (1) According to the signal parameters, determining the critical threshold;
[0056] (2) Based on the critical threshold, searching for the starting point and the ending point of the centroid window on both sides of the signal peak of the pulsed signal respectively.
[0057] According to different signal parameters, different critical thresholds can be determined respectively. For example, according to the signal parameters, it can be judged whether the pulsed signal is a strong signal or a weak signal. If it is a strong signal, a smaller critical threshold is selected. If it is a weak signal, a larger critical threshold is selected. As Figure 3 shown, it is a schematic diagram of the effect of selecting the critical threshold for the pulsed signal. Figure 3A pulsed signal and two different set critical thresholds are shown. It can be seen that the centroid window 1 corresponding to the larger critical threshold (0.5 times the peak value) is smaller, while the centroid window 2 corresponding to the smaller critical threshold (0.3 times the peak value) is larger. Since a strong signal requires a larger centroid window and a weak signal requires a smaller centroid window, a smaller critical threshold is selected for a strong signal and a larger critical threshold is selected for a weak signal. After determining the appropriate critical threshold, the start point and end point of the centroid window are respectively searched on both sides of the signal peak of the pulsed signal based on this critical threshold, and the appropriate centroid window length can be obtained. For example, the position of the signal peak (i.e., the waveform index) of the pulsed signal can be detected first, and then a certain position where the signal amplitude is close to the critical threshold is found on the left side of the signal peak as the start point, and a certain position where the signal amplitude is close to the critical threshold is found on the right side of the signal peak as the end point. The length between the start point and the end point is the length of the centroid window.
[0058] In an implementation manner of the embodiment of the present application, determining the critical threshold according to the signal parameters includes:
[0059] (1) Determining the signal strength level of the pulsed signal according to the signal parameters;
[0060] (2) Determining the critical threshold according to the signal strength level.
[0061] When determining the critical threshold, the signal strength level of the pulsed signal can be determined first according to the signal parameters, and then the critical threshold adapted to this signal strength level can be selected. For example, according to signal parameters such as the signal-to-noise ratio, signal peak value or signal energy of the pulsed signal, it can be determined whether the pulsed signal is a strong signal or a weak signal, that is, which specific signal strength level it belongs to. The signal strength level includes at least two levels of strong and weak, and can also sequentially include multiple levels such as strong, relatively strong, medium, relatively weak and weak... The embodiment of the present application does not impose any restrictions on the specific form of the signal strength level division. If the signal strength level is high, a lower critical threshold can be selected, and if the signal strength level is low, a higher critical threshold can be selected.
[0062] In an implementation manner of the embodiment of the present application, determining the signal strength level of the pulsed signal according to the signal parameters includes:
[0063] (1) Determining each boundary threshold according to the type of the signal parameters;
[0064] (2) Determining the signal strength level according to the magnitude relationship between the value of the signal parameter and each boundary threshold.
[0065] When determining the signal strength level according to signal parameters, the respective demarcation thresholds can be first determined according to the type of signal parameters, and then the corresponding signal strength level can be determined according to the magnitude relationship between the value of the signal parameter and each demarcation threshold. For example, assuming that the type of signal parameter is signal-to-noise ratio and the signal strength levels to be divided include two levels: strong and weak, then a preset signal-to-noise ratio demarcation threshold snr_thre is obtained. By comparing the value of the signal parameter of the pulsed signal, that is, its signal-to-noise ratio value SNR, with the threshold snr_thre, if SNR is greater than snr_thre, the signal strength level is determined to be strong, that is, the pulsed signal is considered a strong signal; conversely, if SNR is less than or equal to snr_thre, the signal strength level is determined to be weak, that is, the pulsed signal is considered a weak signal. Another example, assuming that the type of signal parameter is signal energy and the signal strength levels to be divided include three levels: strong, medium, and weak, then two preset energy demarcation thresholds p_thre1 and p_thre2 are obtained, where p_thre1 < p_thre2. The signal energy value Power of the pulsed signal is detected. If Power is greater than p_thre2, the signal strength level is determined to be strong, that is, the pulsed signal is considered a strong signal; if Power is less than p_thre1, the signal strength level is determined to be weak, that is, the pulsed signal is considered a weak signal; if Power is between p_thre1 and p_thre2, the signal strength level is determined to be medium, that is, the pulsed signal is considered a medium-strength signal. And so on, the respective demarcation thresholds can be flexibly set according to the number of signal strength levels to be divided and the actual type of signal parameters to be detected.
[0066] In an implementation manner of the embodiment of the present application, determining the critical threshold according to the signal strength level includes:
[0067] (1) Determining a target coefficient according to the signal strength level; wherein, the target coefficient is inversely proportional to the signal strength level;
[0068] (2) Calculating the critical threshold according to the target coefficient and the amplitude of the signal peak.
[0069] When determining the critical threshold according to the signal strength level, the target coefficient corresponding to the signal strength level can be determined first, and the target coefficient is inversely proportional to the signal strength level, that is, the higher the signal strength level, the smaller the target coefficient, and the lower the signal strength level, the larger the target coefficient. Then, according to the target coefficient and the amplitude of the signal peak, the critical threshold is calculated. Specifically, multiple target coefficients of different sizes can be preset: prop1, prop2, prop3..., where 0 < prop1 < prop2 < prop3... < 1, and the corresponding target coefficients are selected according to the high or low signal strength level. For example, if the signal strength level is relatively high, smaller target coefficients such as prop1 and prop2 can be selected; if the signal strength level is relatively low, larger target coefficients such as prop3 and subsequent target coefficients can be selected. After selecting the appropriate target coefficient, combined with the amplitude of the signal peak of the pulsed signal, the critical threshold is calculated. For example, assuming the amplitude of the signal peak is a and the selected target coefficient is prop, then the critical threshold thre = prop * a, that is, if prop is 0.5, it means the critical threshold is 0.5 times the peak value; if prop is 0.3, it means the critical threshold is 0.3 times the peak value, and so on. In addition, appropriate critical thresholds thre1, thre2, thre3... corresponding to each signal strength level can also be preset in advance, so that only the corresponding critical threshold needs to be selected according to the signal strength level of the pulsed signal.
[0070] In an implementation manner of the embodiment of the present application, based on the critical threshold, the starting point and the ending point of the centroid window are searched for on both sides of the signal peak of the pulsed signal, including:
[0071] Taking the signal peak as the center, search for the position point on the left side of the center where the signal amplitude is greater than the critical threshold and the signal amplitude at the adjacent position on the left is less than the critical threshold as the starting point of the centroid window, and search for the position point on the right side of the center where the signal amplitude is greater than the critical threshold and the signal amplitude at the adjacent position on the right is less than the critical threshold as the ending point of the centroid window.
[0072] After determining the appropriate critical threshold, with the signal peak as the center, search to the left of the center for a position point where the signal amplitude is close to the critical threshold as the starting point of the centroid window, and search to the right of the center for a position point where the signal amplitude is close to the critical threshold as the ending point of the centroid window. Specifically, assume the critical threshold is thre. Then start searching from the signal peak to the left. When a signal amplitude m greater than thre is found, and the signal amplitude k adjacent to the left of m is less than thre, the position where the amplitude m is located is used as the critical point, and the waveform index i corresponding to this position can be used as the starting point of the centroid window. Similarly, start searching from the signal peak to the right. When a signal amplitude m' greater than thre is found, and the signal amplitude k' adjacent to the right of m' is less than thre, the position where the amplitude m' is located is also the critical point, and the waveform index j corresponding to this position can be used as the ending point of the centroid window. In this way, the constructed centroid window contains all signal points of the pulse-like signal from waveform index i to waveform index j.
[0073] 103. Calculate the centroid of the pulse-like signal according to all signal points within the centroid window.
[0074] After determining the centroid window of the pulse-like signal in the manner described in step 102, the centroid of the pulse-like signal can be calculated according to all signal points within the centroid window. For example, assume that the determined centroid window contains all signal points from waveform index i to waveform index j. Then, according to all signal points of the pulse-like signal from waveform index i to waveform index j, the centroid of the pulse-like signal is calculated. The specific calculation method here can refer to the prior art.
[0075] The embodiment of the present application proposes an improved centroid window algorithm. First, obtain the signal parameters of the pulse-like signal, such as parameters like signal-to-noise ratio, signal peak value, and signal energy. Then, according to these signal parameters, determine the centroid window of the pulse-like signal. Finally, calculate the centroid of the pulse-like signal according to all signal points within this centroid window. Compared with the traditional centroid window algorithm, the centroid window in the embodiment of the present application is no longer a window with a fixed length, but a more adaptable window that can be flexibly configured according to the signal parameters of the pulse-like signal. Therefore, it can improve the accuracy of calculating the centroid of the pulse-like signal.
[0076] It should be understood that the magnitudes of the sequence numbers of the steps in the above various embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
[0077] The above mainly describes a method for detecting the centroid of a pulse-like signal. Next, a device for detecting the centroid of a pulse-like signal will be described.
[0078] Please refer to Figure 4, an embodiment of a centroid detection device for a pulsed signal in an embodiment of the present application includes:
[0079] A signal parameter acquisition module 401, configured to acquire signal parameters of the pulsed signal;
[0080] A centroid window determination module 402, configured to determine a centroid window of the pulsed signal according to the signal parameters;
[0081] A centroid calculation module 403, configured to calculate the centroid of the pulsed signal according to all signal points within the centroid window.
[0082] In an implementation manner of the embodiment of the present application, the centroid window determination module includes:
[0083] A critical threshold determination unit, configured to determine a critical threshold according to the signal parameters;
[0084] A centroid window search unit, configured to search for the start point and end point of the centroid window on both sides of the signal peak of the pulsed signal based on the critical threshold.
[0085] In an implementation manner of the embodiment of the present application, the critical threshold determination unit includes:
[0086] A signal intensity determination subunit, configured to determine the signal intensity level of the pulsed signal according to the signal parameters;
[0087] A critical threshold determination subunit, configured to determine the critical threshold according to the signal intensity level.
[0088] In an implementation manner of the embodiment of the present application, the signal intensity determination subunit includes:
[0089] A demarcation threshold determination subunit, configured to determine each demarcation threshold according to the type of the signal parameters;
[0090] An intensity level determination subunit, configured to determine the signal intensity level according to the magnitude relationship between the value of the signal parameters and each demarcation threshold.
[0091] In an implementation manner of the embodiment of the present application, the critical threshold determination subunit includes:
[0092] A coefficient determination subunit, configured to determine a target coefficient according to the signal intensity level; wherein, the target coefficient is inversely proportional to the signal intensity level;
[0093] A critical threshold calculation subunit, configured to calculate the critical threshold according to the target coefficient and the amplitude of the signal peak.
[0094] In an implementation manner of the embodiment of the present application, the centroid window search unit includes:
[0095] The centroid window search subunit is configured to search, centered on the signal peak, for a position point where the signal amplitude is greater than the critical threshold and the signal amplitude at the adjacent position on the left is less than the critical threshold to the left of the center as the starting point of the centroid window, and search for a position point where the signal amplitude is greater than the critical threshold and the signal amplitude at the adjacent position on the right is less than the critical threshold to the right of the center as the ending point of the centroid window.
[0096] In an implementation manner of the embodiment of the present application, the signal parameter is signal-to-noise ratio, signal peak value or signal energy.
[0097] The embodiment of the present application further provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, it implements the centroid detection method of the pulsed signal as shown in any of the above embodiments.
[0098] The embodiment of the present application further provides a computer program product, and when the computer program product runs on an electronic device, it causes the electronic device to execute the centroid detection method of the pulsed signal as shown in any of the above embodiments.
[0099] Figure 5 is a schematic diagram of an electronic device provided by an embodiment of the present application. As Figure 5 shown, the electronic device 5 in this embodiment includes: a processor 50, a memory 51, and a computer program 52 stored in the memory 51 and executable on the processor 50. When the processor 50 executes the computer program 52, it implements the steps in the embodiments of the above-mentioned centroid detection methods of various pulsed signals, such as Figure 1 the steps 101 to 103 shown. Alternatively, when the processor 50 executes the computer program 52, it implements the functions of each module / unit in the above-mentioned device embodiments, such as Figure 4 the functions of the modules 401 to 403 shown.
[0100] The computer program 52 can be divided into one or more modules / units, and the one or more modules / units are stored in the memory 51 and executed by the processor 50 to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 52 in the electronic device 5.
[0101] The so-called processor 50 may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.
[0102] The memory 51 may be an internal storage unit of the electronic device 5, such as the hard disk or memory of the electronic device 5. The memory 51 may also be an external storage device of the electronic device 5, such as a plug-in hard disk equipped on the electronic device 5, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory 51 may also include both the internal storage unit of the electronic device 5 and the external storage device. The memory 51 is used to store the computer program and other programs and data required by the electronic device. The memory 51 may also be used to temporarily store data that has been output or is to be output.
[0103] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be assigned to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working processes of the units and modules in the above system may refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.
[0104] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working processes of the above-described system, device, and unit may refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.
[0105] In the above embodiments, the descriptions of the various embodiments each have their own emphasis. For parts not described or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.
[0106] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.
[0107] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical or other forms.
[0108] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments of this application.
[0109] In addition, the functional units in the various embodiments of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.
[0110] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of this application, it can also be completed by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.
[0111] The above-described embodiments are only used to illustrate the technical solutions of this application, rather than to limit them; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A method for detecting the centroid of a pulsed signal, characterized in that, Including: Obtaining signal parameters of a pulsed signal; Determining a centroid window of the pulsed signal according to the signal parameters; Calculating the centroid of the pulsed signal according to all signal points within the centroid window.
2. The method according to claim 1, wherein The determining the centroid window of the pulsed signal according to the signal parameters includes: Determining a critical threshold according to the signal parameters; Based on the critical threshold, searching for a starting point and an ending point of the centroid window on both sides of the signal peak of the pulsed signal respectively.
3. The method according to claim 2, wherein The determining the critical threshold according to the signal parameters includes: Determining a signal intensity level of the pulsed signal according to the signal parameters; Determining the critical threshold according to the signal intensity level.
4. The method according to claim 3, wherein The determining the signal intensity level of the pulsed signal according to the signal parameters includes: Determining respective demarcation thresholds according to the type of the signal parameters; Determining the signal intensity level according to the magnitude relationship between the value of the signal parameters and the respective demarcation thresholds.
5. The method according to claim 3, wherein The determining the critical threshold according to the signal intensity level includes: Determining a target coefficient according to the signal intensity level; wherein, the target coefficient is inversely proportional to the signal intensity level; Calculating the critical threshold according to the target coefficient and the amplitude of the signal peak.
6. The method according to claim 2, wherein The searching for the starting point and the ending point of the centroid window on both sides of the signal peak of the pulsed signal based on the critical threshold includes: Taking the signal peak as the center, searching for a position point on the left side of the center where the signal amplitude is greater than the critical threshold and the signal amplitude at the adjacent position on the left is less than the critical threshold as the starting point of the centroid window, and searching for a position point on the right side of the center where the signal amplitude is greater than the critical threshold and the signal amplitude at the adjacent position on the right is less than the critical threshold as the ending point of the centroid window.
7. The method according to any one of claims 1 to 6, characterized in that, The signal parameters are signal-to-noise ratio, signal peak value or signal energy.
8. A centroid detection device for a pulsed signal, characterized in that, Including: A signal parameter acquisition module, configured to obtain signal parameters of a pulsed signal; A centroid window determination module, configured to determine a centroid window of the pulsed signal according to the signal parameters; A centroid calculation module, configured to calculate the centroid of the pulsed signal according to all signal points within the centroid window.
9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the centroid detection method of the pulsed signal according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the centroid detection method of the pulsed signal according to any one of claims 1 to 7.