Method for estimating speed of high-speed object in closed cavity based on magnetic characteristic pulse width time difference

Abstract

The application belongs to the technical field of high-speed object velocity measurement in a closed cavity. The application provides a high-speed object velocity estimation method in a closed cavity based on magnetic characteristic pulse width time difference. In the method, a single fluxgate sensor is arranged on a movement path of a measured target, a magnetic field disturbance signal collected by the fluxgate sensor is combined with signal preprocessing and disturbance mutation segment pulse width detection, a start time and an end time of the magnetic field disturbance signal are extracted, a time width of the target passing through a magnetic flux gate induction area is calculated, and a movement velocity of the target is estimated. The method is completely based on data analysis of the magnetic field disturbance signal collected by the fluxgate sensor, and does not need to contact the measured target or change the structure of the target or add a sensor device during measurement. Moreover, the method does not need to establish a magnetic field mathematical model of the measured target in advance, does not rely on prior knowledge such as magnetic permeability and magnetic moment distribution of the target, and only needs to know a physical width of the target in a disturbance direction.

Description

Technical Field

[0001] This disclosure relates to the field of high-speed object velocity measurement technology in a closed cavity, and in particular to a method for estimating the velocity of a high-speed object in a closed cavity based on magnetic feature pulse width time difference. Background Technology

[0002] In fields such as industrial automation, transportation, and life monitoring, the speed of a moving target is a key parameter for describing its dynamic behavior and enabling state judgment and intelligent control. Traditional contact-based speed measurement methods, such as speed encoders and tachometers, while highly accurate, require physical connections and are difficult to apply in high-temperature, high-speed, or strong electromagnetic interference environments. Non-contact methods, such as lasers, Doppler radar, and image recognition, are flexible, but their accuracy and stability are difficult to guarantee in scenarios with obstructions, lighting conditions, or complex background noise.

[0003] Fluxgate sensors, with their high sensitivity, low noise, and all-weather anti-interference capabilities, are beginning to be widely used in passive detection. Existing fluxgate-based velocity measurement methods mostly rely on slope abrupt changes, peaks, or zero-crossing points for feature extraction, and then use multi-sensor time difference inversion to retrieve velocity. However, such methods are highly dependent on noise and signal morphology, and multi-channel time difference alignment increases system complexity, making it difficult to balance real-time performance and robustness.

[0004] Therefore, while maintaining the inherent advantages of magnetic sensors, there is an urgent need for a non-contact speed measurement solution with a simpler structure, stronger anti-interference capabilities, and higher computational efficiency. This solution should be able to achieve speed inversion based solely on the overall characteristics of a single-channel signal without requiring multi-point alignment or high-order signal processing, thereby meeting the application needs of various scenarios such as industrial automation, traffic monitoring, and underground environment safety inspection.

[0005] Therefore, it is necessary to improve one or more of the problems existing in the above-mentioned related technical solutions.

[0006] It should be noted that this section is intended to provide background or context for the technical solutions of this disclosure as set forth in the claims. The description herein does not constitute an admission that it is prior art simply because it is included in this section. Summary of the Invention

[0007] The purpose of this disclosure is to provide a method for estimating the velocity of a high-speed object in a closed cavity based on magnetic feature pulse width time difference, thereby overcoming, to at least some extent, one or more problems caused by the limitations and defects of related technologies.

[0008] According to embodiments of this disclosure, a method for estimating the velocity of a high-speed object within a closed cavity based on magnetic feature pulse width time difference is provided, including:

[0009] A single fluxgate sensor is deployed along the target's path to collect the magnetic field disturbance signal caused by the target's passage.

[0010] The magnetic field disturbance signal is preprocessed to eliminate noise and baseline drift;

[0011] The pulse width of the preprocessed magnetic field disturbance signal is detected to calculate the pulse width time.

[0012] Based on the pulse width time and the target's standard pulse width time at standard speed, the target's speed can be deduced.

[0013] Furthermore, the preprocessing step for the magnetic field disturbance signal to eliminate noise and baseline drift includes:

[0014] First, a Gaussian weighted moving average filter is used to initially smooth the magnetic field disturbance signal in order to reduce high-frequency noise;

[0015] Subsequently, a low-pass Butterworth filter was used to suppress high-frequency interference in the magnetic field disturbance signal in order to suppress residual high-frequency interference.

[0016] Finally, a sliding window detrending process is performed on the magnetic field disturbance signal to remove background geomagnetic drift and baseline offset, making the disturbance pulse easier to identify.

[0017] Furthermore, the weighting coefficients of the Gaussian-weighted moving average filter are generated based on a standard Gaussian kernel:

[0018]

[0019] in, This is the signal value after weighted averaging; The neighborhood range used in the calculation is determined by the summation of half the window width; For the weight function, For the original signal at the index The value at;

[0020] The weighting function is:

[0021]

[0022] in, To control the standard deviation parameter of the weight distribution width, This is the window length.

[0023] Furthermore, the step of performing pulse width detection on the preprocessed magnetic field disturbance signal to calculate the pulse width time includes:

[0024] Based on the preprocessed magnetic field disturbance signal, the instantaneous slope of each sampling point is calculated using the first-order forward difference method;

[0025] Calculate the absolute value of all instantaneous slopes |s[i]| and the maximum value s among all the absolute values ​​of instantaneous slopes.max And based on the maximum value s max Set the slope threshold T;

[0026] Identify all consecutive sampling points that satisfy |s[i]|≥T, and form a mutation segment;

[0027] The first time point of the mutation segment is taken as the start time, and the last time point is taken as the end time t. end The pulse width time is calculated based on the start and end times.

[0028] Furthermore, the expression for the instantaneous slope is:

[0029]

[0030] in, For the first The signal value at each sampling point For the first The signal value at each sampling point The sampling time interval;

[0031] The expression for the slope threshold T is:

[0032]

[0033] in, The set percentage coefficient;

[0034] The expression for pulse width and time is:

[0035]

[0036] in, This is the index of the starting sampling point for the mutation segment. This is the index of the termination sampling point for the mutation segment.

[0037] Furthermore, the step of inferring the target's velocity based on the pulse width time and the target's standard pulse width time at standard speed includes:

[0038] The target's velocity is calculated based on the standard pulse width time at standard speed and the measured pulse width time.

[0039] Furthermore, the expression for the velocity of motion is:

[0040]

[0041] in, For standard speed, This refers to the standard pulse width time.

[0042] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects:

[0043] In the embodiments of this disclosure, the above method, on the one hand, involves deploying a single fluxgate sensor along the motion path of the target, utilizing the magnetic field disturbance signal collected by the sensor, and combining signal preprocessing with pulse width detection of disturbance transition segments to extract the start and end times of the magnetic field disturbance signal, calculating the time width of the target passing through the fluxgate sensing area, thereby estimating its motion speed. On the other hand, this method is entirely based on data analysis of the magnetic field disturbance signal collected by the fluxgate sensor. The measurement process does not require contact with the target, nor does it require structural modifications or additional sensor devices to the target. Based on the overall pulse width detection strategy of the transition segment rather than local extremum point extraction, it has good tolerance to high-frequency random noise, system baseline drift, or irregularities in the disturbance waveform. Furthermore, it does not require prior establishment of a mathematical model of the target's magnetic field, nor does it rely on prior knowledge such as the permeability and magnetic moment distribution of the target material; only the physical width of the target in the disturbance direction needs to be known, making it applicable to moving targets of various structural types and materials. Attached Figure Description

[0044] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0045] Figure 1 A flowchart illustrating the steps of a method for estimating the velocity of a high-speed object in a closed cavity based on magnetic feature pulse width time difference in an exemplary embodiment of this disclosure is shown.

[0046] Figure 2 A flowchart illustrating the specific velocity estimation method for high-speed objects in a closed cavity based on magnetic feature pulse width time difference in an exemplary embodiment of this disclosure is shown.

[0047] Figure 3 A schematic diagram illustrating the principle of a velocity estimation method for high-speed objects in a closed cavity based on magnetic feature pulse width time difference in an exemplary embodiment of this disclosure;

[0048] Figure 4 This illustrates a pulse width-time detection graph in an exemplary embodiment of this disclosure;

[0049] Figure 5 This diagram illustrates pulse width and time extraction in an exemplary embodiment of the present disclosure.

[0050] Figure 6 This diagram illustrates the estimation of the exit velocity of a high-speed object in an exemplary embodiment of the present disclosure. Detailed Implementation

[0051] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0052] Furthermore, the accompanying drawings are merely illustrative diagrams of embodiments of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities.

[0053] This example implementation provides a method for velocity estimation of high-speed objects within a closed cavity based on magnetic feature pulse width time difference. (Reference) Figure 1 As shown, the velocity estimation method for high-speed objects within a closed cavity based on magnetic feature pulse width time difference may include:

[0054] Step S101: Deploy a single fluxgate sensor along the target's movement path to collect the magnetic field disturbance signal caused by the target passing through;

[0055] Step S102: Preprocess the magnetic field disturbance signal to eliminate noise and baseline drift;

[0056] Step S103: Perform pulse width detection on the preprocessed magnetic field disturbance signal to calculate the pulse width time;

[0057] Step S104: Based on the pulse width time and the standard pulse width time of the target at the standard speed, inversely calculate the target's speed.

[0058] The aforementioned method for estimating the velocity of high-speed objects within a closed cavity based on magnetic characteristic pulse width time difference (PWM) has two main aspects. Firstly, by deploying a single fluxgate sensor along the target's motion path, the method utilizes the acquired magnetic field disturbance signal. Combined with signal preprocessing and PWM detection of abrupt disturbance transitions, the start and end times of the magnetic field disturbance signal are extracted, and the time width of the target passing through the fluxgate sensing area is calculated, thereby estimating its velocity. Secondly, this method is entirely based on data analysis of the magnetic field disturbance signal acquired by the fluxgate sensor. The measurement process does not require contact with the target, nor does it require structural modifications or additional sensor devices. Based on an overall PWM detection strategy for abrupt transitions rather than local extremum extraction, it exhibits good tolerance to high-frequency random noise, system baseline drift, or irregularities in the disturbance waveform. Furthermore, it does not require a prior mathematical model of the target's magnetic field, nor does it rely on prior knowledge of the target material's permeability or magnetic moment distribution; only the physical width of the target in the disturbance direction needs to be known. This method is applicable to moving targets of various structural types and materials.

[0059] Below, we will refer to Figures 1 to 6 The steps of the above-described velocity estimation method for high-speed objects in a closed cavity based on magnetic feature pulse width time difference in this example embodiment will be described in more detail.

[0060] In step S101, a single fluxgate sensor is deployed on the target's movement path to collect the magnetic field disturbance signal caused by the target passing through.

[0061] Specifically, such as Figure 2 The diagram shows a flowchart of a method for estimating the velocity of a high-speed object in a closed cavity based on the magnetic characteristic pulse width time difference.

[0062] A single fluxgate sensor is set on the movement path of the target to collect the magnetic field disturbance signal caused by the target passing through.

[0063] In step S102, the magnetic field disturbance signal is preprocessed to eliminate noise and baseline drift.

[0064] Specifically, a Gaussian weighted moving average filter is used to initially smooth the signal and reduce high-frequency noise.

[0065] Further use of a low-pass Butterworth filter to suppress residual high-frequency interference.

[0066] Perform sliding window detrending processing to remove background geomagnetic drift and baseline offset, making disturbance pulses easier to identify.

[0067] In step S103, the pulse width of the preprocessed magnetic field disturbance signal is detected to calculate the pulse width time.

[0068] Specifically, pulse width detection is performed on the preprocessed magnetic field disturbance signal:

[0069] The instantaneous slope at each time point is calculated using the differential slope method, and the formula is as follows:

[0070]

[0071] Where x[i] is the signal value of the i-th sampling point, This represents the sampling time interval.

[0072] Calculate the absolute value of all slopes |s[i]|, and calculate the maximum value s. max .

[0073] Set the slope threshold as follows:

[0074]

[0075] in, The percentage coefficient set for experience is used as the boundary to identify all time points that satisfy |s[i]|≥T. Points that continuously satisfy the condition constitute a mutation segment.

[0076] Let the start and end times of the mutation segment be respectively... t start and t end The time width of the disturbance pulse is:

[0077]

[0078] In step S104, the target's speed is inferred from the pulse width time and the target's standard pulse width time at standard speed.

[0079] Specifically, based on the time taken for the target to pass through a given scenario at a known speed, obtained from standard experiments, the target's speed is inversely calculated using the standard speed × time-width method:

[0080] Assuming at standard speed Below, the time width of the disturbance pulse is Then, based on the measured time width Target speed It can be calculated using the following formula:

[0081]

[0082] In one embodiment, this application uses a single fluxgate sensor to collect the magnetic disturbance signal generated when a target passes through, employs a sudden change segment identification algorithm to extract the start and end times of the disturbance, and then estimates the target's velocity based on the pulse duration and the target's physical dimensions. This method has advantages such as simple structure, high signal processing robustness, and intuitive velocity calculation, and is suitable for non-contact dynamic velocity measurement in complex magnetic environments.

[0083] In practical applications, the target object is assumed to move at a constant speed along a fixed channel. Fluxgate sensors are deployed along its path to synchronously acquire magnetic disturbance signals. The sensor's response to the target's disturbance is represented as a pulse signal segment with abrupt changes. The sampling frequency is set to fs, and the signal sampling time interval is... =1 / fs, the discrete signal of magnetic field strength collected by the fluxgate sensor is x[i], where i∈{1,2,…,N}, and N is the signal length.

[0084] like Figure 3 The diagram shown is a schematic of a method for estimating the velocity of a high-speed object in a closed cavity based on the magnetic characteristic pulse width time difference. Figure 3 The illustration shows the spatial relationship of a single fluxgate sensor deployed on the movement path of the target being measured, including the target being measured and the first fluxgate sensor.

[0085] (1) Signal preprocessing

[0086] First, the acquired raw magnetic field signal (i.e., the magnetic field disturbance signal) undergoes double filtering. To ensure the sensitivity and accuracy of subsequent mutation detection, a Gaussian weighted moving average filter is first used to smooth the signal. The window length is set to... The weighting coefficients are generated based on the standard Gaussian kernel:

[0087]

[0088] The weighting function is:

[0089]

[0090] This allows for the construction of a symmetrical, smooth weighted kernel, thereby improving signal stability.

[0091] Subsequently, a Butterworth low-pass filter was applied to further suppress high-frequency interference, and a cutoff frequency was set. The order n, according to the normalized frequency Design filters to further eliminate high-frequency interference in the signal and make the edges of the disturbance segment clearer.

[0092] To eliminate the background geomagnetic drift trend, a sliding window detrending process is used to maintain a stable zero-mean distribution of the disturbance signal throughout the time domain, thereby improving the accuracy of abrupt change detection.

[0093] (2) Mutation segment identification and pulse width (i.e. pulse width time) extraction

[0094] This step aims to identify the start and end positions of the disturbance pulse signal and extract the pulse width for subsequent velocity inversion. For example... Figure 4The image shown is a pulse width-time detection plot; the pulse width plot is extracted from the preprocessed magnetic field disturbance signal based on differential analysis and relative threshold setting. Figure 4 It demonstrates how to identify and extract significant change regions in a perturbation signal using first-order difference and mutation rate.

[0095] The instantaneous slope of the signal is calculated using first-order forward difference, defined as follows:

[0096]

[0097] Set the mutation identification threshold as a percentage of the maximum slope value:

[0098]

[0099] Where θ is an empirical constant, usually set to 0.1≤θ≤0.2. When the instantaneous slope at a certain moment satisfies |s[i]|≥T, and this condition exists continuously for more than a preset length, the region is determined to be a mutation segment. The first and last points in this segment are extracted as the start and end times of the mutation segment, thus obtaining the pulse time width of the disturbance segment:

[0100]

[0101] in i start , i end These are the indices for the start and end sampling points of the mutation segment, respectively.

[0102] like Figure 5 The diagram shown illustrates pulse width extraction; the start time for each perturbation segment is marked. t start and termination time t end And calculate its pulse time width. = t end - t start .

[0103] (3) Speed ​​estimation

[0104] This application is based on the following core idea: utilizing the perturbation pulse width detected by a fluxgate sensor. The target velocity is then calculated by combining the standard velocity × time width method. Specifically, the instantaneous velocity of the target is calculated by measuring the time width of the magnetic field disturbance pulse caused when the target passes through the fluxgate and by using the relationship between the known velocity and the corresponding time width in the standard test.

[0105]

[0106] in, and The time width and velocity of the perturbation pulse in the standard experiment. This is the measured time width. The target speed.

[0107] Using the above method, the target speed can be accurately inverted without introducing additional target equipment or relying on external positioning or speed sensors.

[0108] This application proposes a non-contact velocity measurement method that combines fluxgate sensing technology with abrupt change pulse width extraction algorithm. This method is simple in structure, efficient in signal processing, and suitable for various application scenarios. It directly estimates velocity using pulse width, resulting in a simpler algorithm flow, lower requirements for abrupt change alignment, and greater suitability for measurement environments with small target velocity changes and stable disturbances.

[0109] In a specific embodiment, such as Figure 6 As shown, this application can be applied to estimate the exit velocity of a high-speed object within a closed cavity using a fluxgate sensor. In this system, the fluxgate sensor is positioned along the path of the high-speed object within the closed cavity, and its velocity is estimated by detecting the pulse width of the magnetic field disturbance signal caused by the passing of the high-speed object.

[0110] When a target (i.e., a high-speed object) passes through the launching device, the fluxgate sensor detects the instantaneous change in the magnetic field caused by the target's motion. By analyzing the pulse width of the signal, a value proportional to the target's velocity can be obtained. Using this pulse width information, combined with the known sensor position and time difference, the target's exit velocity can be calculated. The advantage of this method is that it does not rely on additional markers or complex hardware devices; a single sensor can achieve high-precision, real-time velocity measurement. This method is particularly suitable for accurately measuring the launch velocity of targets, offering advantages such as non-contact operation, low cost, and insensitivity to environmental influences, and is widely used in fields such as shooting tests.

[0111] In one specific embodiment, the velocity of the target at Z1 is calculated using the velocity and pulse width at Y1 as standard conditions.

[0112]

[0113] Using the velocity and pulse width at Y1 as standard conditions, substituting the pulse width (2.998s) and velocity (180m / s) at Y1, we obtain the calculation formula:

[0114]

[0115] Substituting the pulse width (3.156s) at Z1, we obtain the target velocity as 189.48m / s.

[0116] This application proposes a non-contact, highly interference-resistant method for estimating the velocity of a moving object by deploying a single fluxgate sensor along the target's motion path and utilizing the acquired magnetic field disturbance signal. Combined with signal preprocessing and pulse width detection of disturbance abrupt changes, the start and end times of the disturbance signal are extracted, and the time width of the target passing through the fluxgate sensing area is calculated. This method can be widely applied to estimating the exit velocity of high-speed objects in enclosed cavities, sealed pipelines, and industrial logistics, offering advantages such as simple structure, low computational load, and no need for additional electronic equipment on the target. Through local time-domain analysis of the disturbance signal pulse shape, the disturbance time range is automatically determined, and the target velocity is inverted using the measured pulse width, combined with the target's standard pulse width in the magnetic disturbance direction.

[0117] This application is particularly suitable for application environments where the target structure is regular, the motion path is well-defined, it is difficult to deploy contact sensors, or it is not suitable to damage the target structure, and has the following advantages:

[0118] 1. Non-contact measurement with strong adaptability: This application is based entirely on the disturbance signal collected by the fluxgate sensor for data analysis. During the measurement process, there is no need to contact the target being measured, nor is there any need to modify the target structure or add sensor devices.

[0119] 2. Strong noise resistance and high robustness: This application is based on the overall pulse width detection strategy of abrupt segment rather than local extreme point extraction, which has good tolerance to high-frequency random noise, system baseline drift or irregularity of disturbance waveform.

[0120] 3. Not dependent on magnetic field model, highly versatile: This application does not require the prior establishment of a mathematical model of the magnetic field of the target to be measured, nor does it rely on prior knowledge such as the magnetic permeability and magnetic moment distribution of the target material. It only requires that the physical width of the target in the direction of disturbance be known, and it is applicable to moving targets of various structural types and materials.

[0121] 4. Clear processing flow and low computational cost: The core process of the pulse width detection method includes filtering preprocessing, abrupt segment identification and time width calculation. Compared with traditional methods such as spectrum analysis, time delay correlation and template matching, it has less computation and lower resource consumption, making it easy to deploy on low-power embedded platforms or edge terminals to realize real-time speed measurement functions.

[0122] In summary, this application constructs a method for estimating the velocity of a high-speed object within a closed cavity based on the characteristics of magnetic signals passing through the target magnetic signal and pulse width features. Combined with adaptive signal mutation detection, filtering preprocessing, and a velocity estimation model, it provides an efficient, stable, and universal solution for non-contact dynamic parameter extraction.

[0123] In the embodiments of this disclosure, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this disclosure according to the specific circumstances.

[0124] In embodiments of this disclosure, unless otherwise expressly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature being directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0125] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0126] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

Claims

1. A method for estimating the velocity of a high-speed object within a closed cavity based on magnetic characteristic pulse width time difference, characterized in that, include: A single fluxgate sensor is deployed along the target's path to collect the magnetic field disturbance signal caused by the target's passage. The magnetic field disturbance signal is preprocessed to eliminate noise and baseline drift; The pulse width of the preprocessed magnetic field disturbance signal is detected to calculate the pulse width time of the target passing through the fluxgate sensing area. Specifically, this includes: calculating the instantaneous slope of each sampling point using the first-order forward difference method based on the preprocessed magnetic field disturbance signal; calculating the absolute value of all instantaneous slopes |s[i]| and the maximum value s among all the absolute values ​​of instantaneous slopes. max And based on the maximum value s max Set a slope threshold T; identify all consecutive sampling points that satisfy |s[i]|≥T, forming a mutation segment; take the first time point of the mutation segment as the start time and the last time point as the end time t. end And calculate the pulse width time based on the start and end times; The expression for the instantaneous slope is: in, For the first The signal value at each sampling point For the first The signal value at each sampling point The sampling time interval; The expression for the slope threshold T is: in, The set percentage coefficient; The expression for pulse width time is: in, This is the index of the starting sampling point for the mutation segment. This is the index of the termination sampling point of the mutation segment; Based on the pulse width time and the target's standard pulse width time at standard speed, the target's speed can be deduced.

2. The velocity estimation method for high-speed objects in a closed cavity based on magnetic characteristic pulse width time difference according to claim 1, characterized in that, The preprocessing steps for the magnetic field disturbance signal to eliminate noise and baseline drift include: First, a Gaussian weighted moving average filter is used to initially smooth the magnetic field disturbance signal in order to reduce high-frequency noise; Subsequently, a low-pass Butterworth filter was used to suppress high-frequency interference in the magnetic field disturbance signal in order to suppress residual high-frequency interference. Finally, a sliding window detrending process is performed on the magnetic field disturbance signal to remove background geomagnetic drift and baseline offset, making the disturbance pulse easier to identify.

3. The velocity estimation method for high-speed objects in a closed cavity based on magnetic characteristic pulse width time difference according to claim 2, characterized in that, The weighting coefficients of the Gaussian-weighted moving average filter are generated based on the standard Gaussian kernel: in, This is the signal value after weighted averaging; To achieve a sum of half the window width; For the weight function, For the original signal at the index The value at; The weighting function is: in, To control the standard deviation parameter of the weight distribution width, This is the window length.

4. The velocity estimation method for high-speed objects in a closed cavity based on magnetic feature pulse width time difference according to claim 3, characterized in that, The steps for inferring the target's velocity based on the pulse width time and the target's standard pulse width time at standard speed include: The target's velocity is calculated based on the standard pulse width time at standard speed and the measured pulse width time.

5. The velocity estimation method for high-speed objects in a closed cavity based on magnetic characteristic pulse width time difference according to claim 4, characterized in that, The expression for velocity is: in, For standard speed, This refers to the standard pulse width time.

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