A vehicle-borne ground penetrating radar mileage trigger method and device based on multi-parameter fusion

Abstract

The present invention discloses a vehicle-borne ground penetrating radar mileage triggering method and device based on multi-parameter fusion, which belongs to the technical field of ground penetrating radar. The present invention includes a mileage triggering mechanical system and a multi-sensor mileage triggering system. The present invention converts the voltage signal collected by the acceleration sensor and the square wave pulse signal collected by the wheel speed encoder into real-time mileage data through a mileage calculation module. The data fusion module performs an initial weight distribution through adaptive weighting, and performs a secondary weight distribution on the mileage data by real-time updating the pressure correction factor with the pressure sensor data at different times. Then, the fused data is output through a pulse generation module as a square wave pulse signal with a specific frequency change for triggering the ground penetrating radar. The present invention can effectively improve the adaptability of the system to complex road conditions, and bring great convenience to the subsequent radar data processing and disease point positioning.

Description

Technical Field

[0001] The present invention belongs to the technical field of ground penetrating radar, and more specifically, relates to a vehicle-mounted ground penetrating radar mileage triggering method and device based on multi-parameter fusion. Background Art

[0002] Vehicle-mounted ground penetrating radar is used to survey the structures and diseases below the road surface. In the specific measurement process, there are two common ways to trigger the ground penetrating radar. The first is time triggering, and the second is mileage triggering. Although the former method is not affected by the complex road conditions, it has a high requirement for the uniform speed of the test vehicle. Otherwise, it will cause the overlap and stretching of the radar wave signals, resulting in difficulties in later data analysis. Therefore, at present, the mileage triggering method is often used in specific experiments, that is, a mileage triggering device is equipped on the vehicle-mounted ground penetrating radar system, and the pulse signal generated by the rotation of the vehicle driving mileage wheel is input into the ground penetrating radar for triggering. However, when facing complex road conditions such as uneven and slippery ground surfaces, the mileage wheel may experience situations such as lifting off the ground and idling, and cannot fit well with the ground, resulting in distortion of the mileage trigger signal and affecting the accuracy of the ground penetrating radar data.

[0003] At present, in order to improve the accuracy of the mileage trigger signal, the prior art discloses a real-time mileage optimization system and method, including a mileage wheel set, a conversion circuit, a comparison circuit and a selection circuit, which performs real-time optimization on three-way mileage signals to improve the trigger accuracy; at the same time, the prior art also discloses a vehicle-mounted ground penetrating radar mileage triggering device, including a mileage wheel, a filtering processing module, a mileage optimization module, an orthogonal decoding module, and a mileage calculation module, which optimizes multiple mileage signals and decodes them to calculate the mileage value, improving the anti-interference ability of the vehicle-mounted ground penetrating radar. However, the current measures have limited applicable scenarios and require at least one mileage wheel to be in effective contact with the detection surface, and cannot meet the requirements of high-precision and low-error road disease detection under complex road conditions. Summary of the Invention

[0004] The present invention aims at the technical problems existing in the prior art and provides a vehicle-mounted ground penetrating radar mileage triggering method and device based on multi-parameter fusion.

[0005] To solve the above technical problems, the present invention provides the following technical solutions:

[0006] A vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion, comprising the following steps:

[0007] S1. During the vehicle driving process, the acceleration sensor and the wheel speed encoder respectively output voltage signals and square wave pulse signals, and the pressure sensor monitors the pressure value between the mileage wheel and the ground in real time;

[0008] S2. Convert the collected voltage signal and square wave pulse signal into real-time mileage data through the mileage calculation module, and normalize the two sets of data;

[0009] S3. Perform secondary real-time weight fusion on the preprocessed data through the data fusion module. First, initially assign data weights to the wheel speed encoder mileage data and the acceleration sensor mileage data, and then perform secondary data weight assignment on the two sets of mileage data according to the pressure correction factor;

[0010] S4. Output the obtained fusion data as a square wave pulse signal with a specific frequency change through the pulse generation module, and transmit it to the ground penetrating radar device for mileage triggering.

[0011] Preferably, the calculation process of the real-time mileage data is as follows:

[0012] Acceleration sensor p The obtained k Mileage data at a certain moment D p ( k ) is obtained from the following formula:

[0013]

[0014]

[0015] In the formula, a ( t ) is the acceleration in the driving direction measured by the acceleration sensor, v 0 is the initial speed, x 0 is the initial position;

[0016] Wheel speed encoder q The obtained k Mileage data at a certain moment D q ( k ) is obtained from the following formula:

[0017]

[0018] In the formula, N is the total number of pulses of the encoder per second, PPR is the number of pulses for one revolution of the mileage wheel, L is the circumference of the mileage wheel;

[0019] Pressure sensor r Record k The measured value of the pressure sensor at a certain moment is S ( k ).

[0020] Preferably, the pressure correction factor α obeys hypergeometric decay, and the formula is as follows:

[0021]

[0022] In the formula, S ( k ) is k the measured value of the pressure sensor at time S th the pressure threshold for the mileage wheel to be normally grounded, S min is the minimum effective pressure value, S th and S min are obtained by pre-experiment measurement and analysis. The specific measurement steps are as follows:

[0023] Select three experimental scenarios including flat road surface, slippery road surface, and bumpy road surface;

[0024] Let the vehicle pass through the three different road surfaces at speeds of 20 km / h, 40 km / h, and 60 km / h respectively;

[0025] Record the acquisition data of the pressure sensor, acceleration sensor, and wheel speed sensor in each experimental scenario;

[0026] Take the maximum value of the pressure sensor recorded data in each scenario as the pressure threshold S th ;

[0027] Take the average value of the pressure sensor when the errors of the acceleration sensor and the wheel speed sensor are 50% in each scenario as the minimum effective pressure value S min .

[0028] Preferably, in step S3, the initial data weight value is obtained by using the adaptive weighted fusion algorithm. For the acceleration sensor p and the wheel speed encoder q , there are measurement result signals D p ( k ) and D q ( k ). The measurement signal consists of the true signal D ( k ) and the observation error V p ( k ), V q ( k ), and is expressed as:

[0029]

[0030]

[0031] The observation error can be regarded as Gaussian white noise, and the sensors p and q are independent of each other. The observation errors between the sensors p and q are uncorrelated. The mean value of the observation error is zero and is uncorrelated with the true signal.

[0032] Preferably, the cross-correlation function p between the sensors q and R pq , R pp , R qq is calculated as follows, where E(·) is to find the mean value, and its expression is :

[0033]

[0034]

[0035] ;

[0036] The variances of the sensors p and q are and , respectively, and are expressed as:

[0037]

[0038] ;

[0039] To obtain the variance estimates of the sensors k at the p and q moments, it is necessary to take k near the n sampling points, and take the average of the measurement data at each sampling point to obtain the autocorrelation function and cross-correlation function at the k moment. The calculation formulas are as follows:

[0040]

[0041]

[0042] ;

[0043] The average value of the cross-correlation functions of two sensors is further used to obtain the estimated value of the cross-correlation function:

[0044]

[0045] where m is the number of sensors, taking the value of 2; the autocorrelation function and the estimated value of the cross-correlation function are subtracted to obtain k the estimated variance p of sensor q and sensor at time k The unbiased estimate of the observed variance at time

[0046]

[0047]

[0048] where is the observed variance obtained from sensor i at the p th sampling point and sensor q Then, the weight estimate p of sensor q and sensor is obtained using the following formula:

[0049]

[0050]

[0051] Thus, the process estimate k at time is as follows:

[0052] .

[0053] Preferably, based on the initial data weight allocation, secondary weight allocation is performed according to the pressure correction factor α to determine whether the pressure value is between the threshold and the minimum effective value. If S min ≤ S ( k ) ≤ S th , then α dynamic weights are used; if S ( k ) ≥ S th , then α fixed weight 1 is used; if S (k ) ≤ S min , then α adopt a fixed weight of 0;

[0054] The secondary allocation weight is obtained after being corrected by a correction factor It can be expressed as:

[0055]

[0056]

[0057] Then, after pressure correction k the mileage estimation at a certain moment is:

[0058] .

[0059] Preferably, in step S4, the fused data is output by the pulse generation module as a pulse signal with a specific frequency change. The pulse generation module adopts the STM32 series of microcontrollers. When working, the timer is placed in the PWM mode. The specific steps are as follows:

[0060] In the high-frequency sampling mode, the mileage estimation obtained in step S3 is regarded as a continuously varying function , and the square-wave pulse frequency f ( t ) is obtained from the following formula:

[0061]

[0062] In the formula, PPR is the number of pulses for the mileage wheel to rotate one week, L is the circumference of the mileage wheel;

[0063] The output frequency of the STM32 timer satisfies the following formula:

[0064]

[0065] In the formula, is the timer clock frequency, PSC is the prescaler value, ARR is the automatic reload value.

[0066] Furthermore, the present invention also provides a vehicle-mounted ground-penetrating radar mileage trigger device based on multi-parameter fusion, including a mileage trigger mechanical system and a multi-sensor mileage trigger system. The mileage trigger mechanical system includes a radar bracket and a mileage wheel. The radar bracket is connected to the mileage wheel through a connecting mechanism. The multi-sensor mileage trigger system includes multiple sensor modules for collecting mileage signals, processing data, and outputting signals.

[0067] Preferably, a bearing and a rotating shaft are connected to the radar bracket. The connecting mechanism is provided with a connecting bracket and a telescopic spring. The odometer wheel is connected to the rotating shaft through the connecting bracket, and the telescopic spring is arranged between the odometer wheel and the radar bracket.

[0068] Preferably, the multi-sensor odometer triggering system includes an acceleration sensor that outputs a voltage signal, a wheel speed encoder that outputs a square wave pulse signal, and a pressure sensor for pressure monitoring. The voltage signal and the square wave pulse signal are subjected to output signal conversion through an odometer calculation module. The output ends of the odometer calculation module and the pressure sensor are connected to a data fusion module. The data fusion module performs data fusion and then outputs a pulse signal to the ground penetrating radar through a pulse generation module.

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] The odometer triggering device in the embodiment of the present invention includes an odometer triggering mechanical system and a multi-sensor odometer triggering system. In the present invention, the voltage signal collected by the acceleration sensor and the square wave pulse signal collected by the wheel speed encoder are converted into real-time odometer data through an odometer calculation module. The data fusion module performs an initial weight distribution through adaptive weighting, and performs a secondary weight distribution on the odometer data by updating the pressure correction factor in real time according to the data of the pressure sensor at different times. Then, the fused data is output through a pulse generation module as a square wave pulse signal with a specific frequency change for triggering the ground penetrating radar. The present invention can effectively improve the adaptability of the system to complex road conditions and bring great convenience to the subsequent radar data processing and disease point positioning. Description of the Drawings

[0071] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0072] Figure 1 It is a schematic flowchart of an embodiment of the vehicle-mounted ground penetrating radar odometer triggering method based on multi-parameter fusion of the present invention;

[0073] Figure 2 It is a three-dimensional structure schematic diagram of an embodiment of the odometer triggering mechanical system of the present invention;

[0074] Figure 3 It is a top view structure schematic diagram of an embodiment of the odometer triggering mechanical system of the present invention;

[0075] Figure 4 It is a schematic diagram of the attitude adjustment structure of an embodiment of the odometer triggering mechanical system of the present invention;

[0076] Figure 5 This is a schematic diagram of the system layout of the multi-sensor mileage trigger system according to an embodiment of the present invention.

[0077] Explanation of the symbol markings in the figure:

[0078] 1. Mileage trigger mechanical system; 11. Radar bracket; 12. Odometer wheel; 13. Bearing; 14. Rotating shaft; 15. Telescopic spring; 16. Arc rod; 17. Straight rod;

[0079] 21. Acceleration sensor; 22. Wheel speed encoder; 23. Pressure sensor; 24. Mileage calculation module; 25. Data fusion module; 26. Pulse generation module. Specific implementation manner

[0080] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present application more clear and understandable, the following further details a vehicle-borne ground penetrating radar mileage trigger method and device based on multi-parameter fusion provided by the present application in combination with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0081] Embodiment 1

[0082] Please refer to Figure 1 , an embodiment of the present invention provides a vehicle-borne ground penetrating radar mileage trigger method based on multi-parameter fusion, including the following steps:

[0083] S1. During the vehicle driving process, the acceleration sensor and the wheel speed encoder respectively output a voltage signal and a square wave pulse signal, and the pressure sensor monitors the pressure value between the odometer wheel and the ground in real time;

[0084] S2. Convert the collected voltage signal and square wave pulse signal into real-time mileage data through the mileage calculation module, and perform normalization processing on the two-way data;

[0085] S3. Perform secondary real-time weight fusion on the preprocessed data through the data fusion module. First, initially allocate data weights to the mileage data of the wheel speed encoder and the acceleration sensor, and then perform secondary data weight allocation on the two-way mileage data according to the pressure correction factor;

[0086] S4. Output the obtained fusion data as a square wave pulse signal with a specific frequency change through the pulse generation module, and transmit it to the ground penetrating radar device for mileage trigger.

[0087] In the embodiment of the present invention, the voltage signal collected by the acceleration sensor and the square wave pulse signal collected by the wheel speed encoder are converted into real-time mileage data through the mileage calculation module. The data fusion module performs the initial weight distribution through adaptive weighting, and the pressure correction factor is updated in real time through the data of the pressure sensor at different times to perform the secondary weight distribution on the mileage data. Then, the fused data is output through the pulse generation module as a square wave pulse signal with a specific frequency change for triggering the ground penetrating radar. The present invention can effectively improve the adaptability of the system to complex road conditions, and bring great convenience to the subsequent radar data processing and disease point positioning.

[0088] Embodiment 2

[0089] As Figure 1 shown, this embodiment provides a vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion, which specifically includes the following steps:

[0090] S1. During the driving of the vehicle, the acceleration sensor and the wheel speed encoder respectively output a voltage signal and a square wave pulse signal for calculating mileage data, and the pressure sensor is used to monitor the pressure value between the mileage wheel and the ground in real time; the high-frequency sampling method is adopted to ensure accurate recording of the data of each sensor, and the sampling frequency is 1 kHz.

[0091] S2. The voltage signal collected by the acceleration sensor and the square wave pulse signal collected by the wheel speed encoder in step S1 are converted into real-time mileage data through the mileage calculation module, and the two-way data is normalized; the pressure correction factor is updated in real time according to the data of the pressure sensor.

[0092] The mileage calculation module reads the acceleration value measured by the acceleration sensor through the SPI protocol p a ( t ) and then converts it into the mileage data at time k D p ( k ) which is obtained by the following formula:

[0093]

[0094]

[0095] In the formula, a ( t ) is the acceleration in the driving direction measured by the acceleration sensor (it is assumed that the vehicle is driving in a straight line by default), v 0 is the initial speed, x 0 is the initial position.

[0096] The wheel speed encoder q ​​Conversion of Measured Square Wave Pulse Signal is k Mileage data at a certain moment D q ( k ) is obtained from the following formula:

[0097]

[0098] In the formula, N is the total number of pulses of the encoder per second, PPR is the number of pulses for the mileage wheel to rotate one week, L is the circumference of the mileage wheel.

[0099] Pressure sensor r Records k The measured value of the pressure sensor at a certain moment is S ( k ).

[0100] In this embodiment, to quickly respond to low pressure values, the designed pressure correction factor α obeys hypergeometric decay, and the formula is as follows:

[0101]

[0102] In the formula, S ( k ) is k the measured value of the pressure sensor at a certain moment, S th is the pressure threshold for the mileage wheel to be normally grounded, S min is the minimum effective pressure value, S th and S min are obtained by pre-experiment measurement and analysis. The specific measurement steps are as follows:

[0103] 1) Select three experimental scenarios including flat road surface, slippery road surface, and bumpy road surface;

[0104] 2) Let the vehicle pass through the three different road surfaces at speeds of 20 km / h, 40 km / h, and 60 km / h respectively;

[0105] 3) Record the acquisition data of the pressure sensor, acceleration sensor, and wheel speed sensor in each experimental scenario, and the acquisition distance is 5 km;

[0106] 4) Take the maximum value of the pressure sensor recorded data in each scenario as the pressure threshold for this scenario S th ;

[0107] 5) Take the average value of the pressure sensor when the errors of the acceleration sensor and the wheel speed sensor are 50% in each scenario as the minimum effective pressure value in that scenario. S min 。

[0108] During the actual experiment, the corresponding S th and S min can be selected according to the road conditions and speed at that time. The dynamic threshold adjustment method can improve the adaptability of the system in different environments and avoid misjudgments caused by fixed thresholds.

[0109] S3. Pass the data preprocessed in step S2 through the data fusion module for secondary real-time weight fusion. First, perform adaptive weighted fusion on the wheel speed encoder mileage data and the acceleration sensor mileage data to initially allocate data weights, and then perform secondary data weight allocation on the two-way mileage data according to the pressure correction factor.

[0110] In this embodiment, the initial data weight value is obtained by using the adaptive weighted fusion algorithm. For the acceleration sensor p and the wheel speed encoder q , there are measurement result signals D p ( k ) and D q ( k ). The measurement signal consists of the true signal D ( k ) and the observation error V p ( k ), V q ( k ). It is expressed as:

[0111]

[0112]

[0113] The observation error can be regarded as Gaussian white noise. The sensors p and q are independent of each other. The observation errors between the sensors p and q are uncorrelated. The mean value of the observation error is zero and it is uncorrelated with the true signal.

[0114] The cross-correlation function between the sensors p and q , R pq , R pp ,R qq The calculation formula is as follows, where E(·) is to find the mean value, and its expression is :

[0115]

[0116]

[0117] ;

[0118] sensor p and q have variances of and , respectively. By taking the difference between their autocorrelation function and cross-correlation function, it can be expressed as:

[0119]

[0120] ;

[0121] To obtain the variance estimation values of the sensors k at time p and q , it is necessary to take k sampling points near time n . Take the average of the measurement data at each sampling point to obtain the autocorrelation function and cross-correlation function at time k . The calculation formula is as follows:

[0122]

[0123]

[0124] ;

[0125] Take the average of the cross-correlation functions of the two sensors to further obtain the estimated value of the cross-correlation function:

[0126]

[0127] In the formula, m is the number of sensors, with a value of 2; the autocorrelation function and the estimated value of the cross-correlation function are subtracted to obtain the variance estimation value k of the sensors p and sensor q at time , k The unbiased estimation of the observed variance at time

[0128]

[0129]

[0130] Wherein, is the i th sampling point sensor p and the sensor q to obtain the observed variance, and then the weights of the sensors p and the sensor q are estimated using the following formula :

[0131]

[0132]

[0133] Thus, k the mileage estimate at time is as follows:

[0134] .

[0135] Furthermore, in this embodiment, in step S3, based on the initial allocation of data weights, a secondary weight allocation is performed according to the pressure correction factor α . It is determined whether the pressure value is between the threshold and the minimum effective value. If S min ≤ S ( k ) ≤ S th , then α dynamic weights are adopted; if S ( k ) ≥ S th , then α fixed weight 1 is adopted; if S ( k ) ≤ S min , then α fixed weight 0 is adopted.

[0136] The secondary allocated weight obtained after correction by the correction factor can be expressed as:

[0137]

[0138]

[0139] Then the mileage estimate k at time after pressure correction is:

[0140] 。

[0141] S4. Output the fused data obtained in step S3 as a square wave pulse signal with a specific frequency change through the pulse generation module, and transmit it to the ground penetrating radar device for mileage triggering.

[0142] Specifically, the fused data is output as a pulse signal with a specific frequency change through the pulse generation module. The pulse generation module uses the STM32 series of microcontrollers. When working, the timer is placed in the PWM mode. The specific steps are as follows:

[0143] In the high-frequency sampling mode, regard the mileage estimation obtained in step S3 as a continuously varying function , and the square wave pulse frequency f ( t ) is obtained from the following formula:

[0144]

[0145] In the formula, PPR is the number of pulses for one revolution of the mileage wheel, L is the circumference of the mileage wheel;

[0146] The output frequency of the STM32 timer satisfies the following formula:

[0147]

[0148] In the formula, is the timer clock frequency, PSC is the prescaler value, ARR is the auto-reload value.

[0149] Furthermore, by dynamically adjusting the ARR value according to the above formula, a square wave pulse signal with a specific frequency change can be output.

[0150] The above method in the embodiment of the present invention improves the confidence of the wheel speed encoder data through the mileage trigger mechanical structure, performs two weight assignments on the two-way mileage data from the acceleration sensor and the wheel speed encoder through the data fusion module, and can avoid false triggering caused by single-sensor data distortion by real-time updating the weights of the two-way mileage data, and can cope with the complex road conditions that may be faced during the experiment.

[0151] Embodiment 3

[0152] As Figure 2 、 Figure 4As shown in the figure, an embodiment of the present invention provides a vehicle-mounted ground penetrating radar mileage trigger device based on multi-parameter fusion, including a mileage trigger mechanical system 1 and a multi-sensor mileage trigger system. The mileage trigger mechanical system 1 includes a radar bracket 11 and a mileage wheel 12. The radar bracket 11 and the mileage wheel 12 are connected by a connecting mechanism. The multi-sensor mileage trigger system includes multiple sensor modules for collecting mileage signals and outputting signals through a data processor.

[0153] In this embodiment, a bearing 13 and a rotating shaft 14 are connected to the radar bracket 11. The connecting mechanism is provided with a connecting bracket and a telescopic spring 15. The mileage wheel 12 is connected to the rotating shaft 14 through the connecting bracket. The telescopic spring 15 is arranged between the mileage wheel 12 and the radar bracket 11.

[0154] Specifically, as Figure 2 、 Figure 3 shown, the connecting bracket includes an arc-shaped rod 16 and a straight rod 17. The arc-shaped rod 16 and the straight rod 17 are arranged at an angle. The upper end of the arc-shaped rod 16 is movably connected to the radar bracket 11 through the bearing 13 and the rotating shaft 14. By connecting the rotating shaft 14 and the bearing 13 with the mileage wheel 12, the flexibility of the mileage wheel 12 in the direction perpendicular to the ground is improved, and the height of the mileage wheel can be freely adjusted according to the unevenness of the road surface; the lower end of the arc-shaped rod 16 is connected to the mileage wheel 12, one end of the straight rod 17 is connected to the mileage wheel 12, and the second end of the straight rod 17 is connected to the telescopic spring 15. The bearing 13 and the rotating shaft 14 are arranged in the middle of the rear end of the radar bracket 11. The mileage wheel 12 is connected to the rotating shaft 14 through the arc-shaped rod 16, and the telescopic spring 15 is connected between the rotating shaft 14 and the straight rod 17.

[0155] In this embodiment, the bearing 13 is arranged at the end of the rotating shaft 14, the rotating shaft 14 can rotate, the lower end of the telescopic spring 15 is connected to the end of the straight rod 17, and the upper end of the telescopic spring 15 is connected to the radar bracket 11. In this embodiment, the height of the mileage wheel 12 can be adjusted by using the arc-shaped rod 16 through the bearing 13 and the rotating shaft 14, and the traction force can be provided through the telescopic spring 15 to increase the pressure and the degree of fitting between the mileage wheel 12 and the ground.

[0156] Specifically, as Figure 4As shown in the figure, when the system is on a horizontal ground, the arc-shaped rod 16 forms an angle of 30° with the vertical direction, and the telescopic spring 15 is in a stretched state, capable of providing a traction force of 30 N; when the ground is convex, the arc-shaped rod 16 forms an angle of at most 50° with the vertical direction, and the telescopic spring 15 can provide a traction force of 50 N; when the ground is concave, the arc-shaped rod 16 forms an angle of at least 10° with the vertical direction, and the telescopic spring 15 can provide a traction force of at least 10 N. Based on this, the angle between the arc-shaped rod 16 and the vertical direction can be dynamically adjusted between 10° and 50°, and the corresponding height of the mileage wheel can be adjusted by approximately 20 cm, which can meet the experimental scenarios under general circumstances. When encountering uneven ground conditions, the mechanical structure can flexibly adjust the horizontal height of the mileage wheel and the spring traction force, reducing its airborne time.

[0157] In this embodiment, as Figure 5 shown, the multi-sensor mileage trigger system includes an acceleration sensor 21, a wheel speed encoder 22, a pressure sensor 23, a mileage calculation module 24, a data fusion module 25, and a pulse generation module 26. Among them, the acceleration sensor 21 outputs a voltage signal, the wheel speed encoder 22 outputs a square wave pulse signal, the pressure sensor 23 is used for pressure monitoring and can be used to record the real-time pressure value between the mileage wheel 12 and the ground. The mileage calculation module 24 is used to convert the output signals of the acceleration sensor 21 and the wheel speed encoder 22 into real-time mileage data. The output ends of the mileage calculation module 24 and the pressure sensor 23 are connected to the data fusion module 25. The data fusion module 25 allocates weights in real time according to the data of the three sensors to predict the current mileage, and then converts the fused mileage data into a pulse signal through the pulse generation module 26 for triggering the ground penetrating radar.

[0158] Furthermore, in this embodiment, the acceleration sensor 21 used is a capacitive acceleration sensor MEMS, the wheel speed encoder 22 is of the MLX series, and the pressure sensor 23 uses the SP40 series.

[0159] The present invention proposes a method and device for triggering the mileage of a vehicle-mounted ground penetrating radar based on multi-parameter fusion, which solves the problems such as the distortion of the radar waveform and the difficulty in disease positioning caused by incorrect mileage data due to the complexity of road conditions during the underground information acquisition of the existing vehicle-mounted ground penetrating radar. The mileage trigger device of the present invention includes a mileage trigger mechanical system and a multi-sensor mileage trigger system. The telescopic spring 15 provides a traction force in the ground direction for the mileage wheel 12, improving the degree of fit between the mileage wheel 12 and the ground. When encountering uneven ground conditions, the mechanical structure can flexibly adjust the horizontal height of the mileage wheel and the spring traction force, reducing its airborne time.

[0160] In the present invention, the voltage signal collected by the acceleration sensor 21 and the square wave pulse signal collected by the wheel speed encoder 22 are converted into real-time mileage data through the mileage calculation module 24. The data fusion module 25 performs an initial weight assignment through adaptive weighting, and performs a secondary weight assignment on the mileage data by updating the pressure correction factor in real time with the data of the pressure sensor 23 at different times. Then, the fused data is output through the pulse generation module 26 as a square wave pulse signal with a specific frequency change for triggering the ground penetrating radar. The present invention can effectively improve the adaptability of the system to complex road conditions, and bring great convenience to the subsequent radar data processing and disease point positioning.

[0161] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present application.

[0162] In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, "a plurality" means two or more, unless otherwise specifically defined.

[0163] The above are only the preferred embodiments of the present application, and are not intended to limit the present application. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion, characterized in that: The following steps are involved: S1. During the driving process of the vehicle, the acceleration sensor and the wheel speed encoder output voltage signals and square wave pulse signals respectively, and the pressure sensor monitors the pressure value between the odometer wheel and the ground in real time; S2, converting the collected voltage signal and square wave pulse signal into real-time mileage data through the mileage calculation module, and normalizing the two data; S3, the pre-processed data is subjected to secondary real-time weight fusion through the data fusion module, firstly, the wheel speed encoder mileage data and the acceleration sensor mileage data are initially assigned data weights, and then the two mileage data are subjected to secondary data weight assignment according to the pressure correction factor; S4. The obtained fusion data is output as a square wave pulse signal with a specific frequency change through a pulse generation module, and transmitted to the ground penetrating radar device for mileage triggering.

2. The vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion according to claim 1 is characterized in that: The real-time mileage data calculation process is as follows: Accelerometer p Income k Time and mileage data D p ( k ) is obtained from the following formula: In the formula, a ( t ) is the acceleration in the driving direction measured by the acceleration sensor, v 0 is the initial speed, x 0 is the initial position; Wheel speed encoder q Income k Time and mileage data D q ( k ) is obtained from the following formula: In the formula, N is the total number of encoder pulses per second, PPR is the number of pulses per rotation of the mileage wheel, L is the circumference of the odometer wheel; Pressure Sensors r Record k The pressure sensor measured value at this moment is S ( k ).

3. The vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion according to claim 1 is characterized in that: The pressure correction factor α It obeys hypergeometric decay, and the formula is as follows: In the formula, S ( k )for k The pressure sensor measurement value at the moment, S th The pressure threshold for the normal grounding of the mileage wheel. S min is the minimum effective pressure value, S th and S min The specific measurement steps are as follows: Three experimental scenarios were selected, including smooth road surface, slippery road surface, and bumpy road surface; Let the vehicle pass through three different road surfaces at speeds of 20km / h, 40km / h, and 60km / h; Record the collected data of pressure sensor, acceleration sensor and wheel speed sensor in each experimental scenario; The maximum value of the pressure sensor data recorded in each scenario is taken as the pressure threshold of the scenario. S th ; The average value of the pressure sensor when the error between the acceleration sensor and the wheel speed sensor is 50% in each scenario is taken as the minimum effective pressure value in that scenario. S min .

4. The vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion according to claim 1 is characterized in that: In step S3, the initial data weight value is obtained by using an adaptive weighted fusion algorithm. p and wheel speed encoder q , there is a measurement result signal D p ( k )and D q ( k ), the measured signal is composed of the real signal D ( k ) and observation error V p ( k ), V q ( k ), expressed as: The observation error can be regarded as Gaussian white noise. p and q Independent of each other, the sensors p and q The observation errors between are uncorrelated, have a mean of zero and are uncorrelated with the true signal.

5. The vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion according to claim 4 is characterized in that: sensor p and q The cross-correlation function R pq , R pp , R qq The calculation formula is as follows, where E(·) is the mean value: ； sensor p and q The variances of and , expressed as: ； In order to get k Sensors at all times p and q The variance estimate of k Pick up near the time n The number of sampling points is calculated by taking the average value of the measured data at each sampling point. k The moment autocorrelation function and cross-correlation function are calculated as follows: ； The average value of the cross-correlation function of the two sensors is further calculated to obtain the estimated value of the cross-correlation function: In the formula, m is the number of sensors, the value is 2; autocorrelation function and cross-correlation function estimates The difference can be obtained k Time sensor p and sensors q The variance estimate of , k Unbiased Estimation of the Variance of Observations at Each Moment The formula is as follows: In the formula, For the i Sampling point sensors p and sensors q The observed variance is obtained, and then the sensor is obtained using the following formula p and sensors q The weight estimate : From this we can get k Time course estimation as follows: 。 6. The vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion according to claim 5 is characterized in that: Based on the initial data weight allocation, the pressure correction factor α Perform secondary weight distribution to determine whether the pressure value is between the threshold and the minimum effective value. S min ≤ S ( k ) ≤ S th ,but α Adopt dynamic weights; like S ( k ) ≥ S th ,but α Use a fixed weight of 1; like S ( k ) ≤ S min ,but α Use a fixed weight of 0; The secondary distribution weight is obtained after correction by the correction factor It can be expressed as: After pressure correction k Time and mileage estimation for: 。 7. The vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion according to claim 1 is characterized in that: In step S4, the fused data is output as a pulse signal with a specific frequency change through a pulse generation module. The pulse generation module uses a microcontroller STM32 series, and the timer is placed in PWM mode during operation. The specific steps are as follows: In the high-frequency sampling mode, the mileage estimate obtained in step S3 is Considered as a continuously changing function , square wave pulse frequency f ( t ) is obtained by the following formula: In the formula, PPR is the number of pulses per rotation of the mileage wheel, L is the circumference of the odometer wheel; The STM32 timer output frequency satisfies the following formula: In the formula, is the timer clock frequency, PSC is the prescaler value, ARR is the auto-reload value.

8. The vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion according to claim 1 is performed using a mileage triggering device, characterized in that: The mileage trigger device includes a mileage trigger mechanical system and a multi-sensor mileage trigger system. The mileage trigger mechanical system includes a radar bracket and a mileage wheel. The radar bracket is connected to the mileage wheel through a connecting mechanism. The multi-sensor mileage trigger system includes multiple sensor modules for mileage signal collection and data processor signal output.

9. The vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion according to claim 8, characterized in that: The radar bracket is connected with a bearing and a rotating shaft, the connecting mechanism is provided with a connecting bracket and a telescopic spring, the mileage wheel is connected with the rotating shaft through the connecting bracket, and the telescopic spring is arranged between the mileage wheel and the radar bracket.

10. The vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion according to claim 8, characterized in that: The multi-sensor mileage trigger system includes an acceleration sensor that outputs a voltage signal, a wheel speed encoder that outputs a square wave pulse signal, and a pressure sensor for pressure monitoring. The voltage signal and the square wave pulse signal are converted into output signals through a mileage calculation module. The output end of the mileage calculation module and the pressure sensor are connected to a data fusion module. The data fusion module performs data fusion and then outputs a pulse signal to the ground penetrating radar through a pulse generation module.

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