Vehicle-mounted ground penetrating radar mileage triggering method and device based on multi-parameter fusion

Abstract

The invention discloses a vehicle-mounted ground penetrating radar mileage triggering method and device based on multi-parameter fusion, and belongs to the technical field of ground penetrating radars. The system comprises a mileage triggering mechanical system and a multi-sensor mileage triggering system, a voltage signal collected by an acceleration sensor and a square wave pulse signal collected by a wheel speed encoder are converted into real-time mileage data through a mileage calculation module, and a data fusion module carries out initial weight distribution through adaptive weighting; a pressure correction factor is updated in real time through pressure sensor data at different moments, secondary weight distribution is carried out on mileage data, and a square wave pulse signal with specific frequency change is output from fused data through a pulse generation module and used for ground penetrating radar triggering. According to the invention, the adaptability of the system to complex road conditions can be effectively improved, and great convenience is brought to later 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 structure and defects 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 conditions of the road surface, it has high requirements for the uniform speed of the test vehicle, otherwise it will cause the overlap and stretching of the radar wave signal, making it difficult to analyze the data later. Therefore, at this stage, the mileage triggering method is often used in specific experiments, that is, the vehicle-mounted ground penetrating radar system is equipped with a mileage triggering device, and the pulse signal generated by the rotation of the vehicle's mileage wheel is input into the ground penetrating radar for triggering. However, when facing complex road conditions such as uneven and slippery surfaces, the mileage wheel is vacant or idling, and cannot fit the ground well, causing the mileage trigger signal to be distorted, affecting the accuracy of the ground penetrating radar data.

[0003] At present, in order to improve the accuracy of mileage trigger signals, 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 optimize the three-way mileage signals in real time to improve the trigger accuracy; at the same time, the prior art also discloses a vehicle-mounted ground-penetrating radar mileage trigger device, including a mileage wheel, a filtering processing module, a mileage optimization module, an orthogonal decoding module, and a mileage calculation module, which optimizes and decodes multiple mileage signals and then calculates the mileage value, thereby improving the anti-interference ability of the vehicle-mounted ground-penetrating radar. However, the current measures are limited in applicable scenarios and require at least one mileage wheel to be in effective contact with the detection surface, which 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 solving 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] In order to solve the above technical problems, the present invention provides the following technical solutions: A vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion, comprising the following steps: 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.

[0006] Preferably, 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:

[0007]

[0008] In the formula, a ( t ) is the acceleration in the driving direction measured by the acceleration sensor, v 0 is the initial velocity, 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:

[0009] 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 ).

[0010] Preferably, the pressure correction factor α It obeys hypergeometric decay, and the formula is as follows:

[0011] In the formula, S ( k )for k The pressure sensor measurement value at the moment, Sth 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 .

[0012] Preferably, 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:

[0013]

[0014] 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.

[0015] Preferably, the sensor p andq The cross-correlation function R pq , R pp , R qq The calculation formula is as follows, where E(·) is the mean value, and its expression is :

[0016]

[0017] ; sensor p and q The variances of and , expressed as:

[0018] ; 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 of each sampling point. k The calculation formulas of the autocorrelation function and cross-correlation function at each moment are as follows:

[0019]

[0020] ; 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:

[0021] 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:

[0022]

[0023] 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 :

[0024]

[0025] From this we can get k Time course estimation as follows: .

[0026] Preferably, 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 Use dynamic weights; if S ( k ) ≥ S th ,but α Use a fixed weight of 1; if 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:

[0027]

[0028] After pressure correction k Time and mileage estimation for: .

[0029] Preferably, 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 adopts 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:

[0030] 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:

[0031] In the formula, is the timer clock frequency, PSC is the prescaler value, ARR is the auto-reload value.

[0032] 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 and outputting data processing signals.

[0033] 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 mileage wheel is connected to the rotating shaft via the connecting bracket, and the telescopic spring is arranged between the mileage wheel and the radar bracket.

[0034] Preferably, 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.

[0035] Compared with the prior art, the present invention has the following beneficial effects: The mileage trigger device of the embodiment of the present invention includes a mileage trigger mechanical system and a multi-sensor mileage trigger 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 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 pressure sensor data at different times to perform 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 ground penetrating radar triggering. The present invention can effectively improve the adaptability of the system to complex road conditions, and greatly facilitate the later radar data processing and disease point positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0037] Figure 1 It is a flow chart of an embodiment of a vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion of the present invention; Figure 2 It is a three-dimensional structural schematic diagram of an embodiment of a mileage triggering mechanical system of the present invention; Figure 3 It is a top view of the structure of an embodiment of the mileage triggering mechanical system of the present invention; Figure 4 A schematic diagram of the posture adjustment structure of the mileage-triggered mechanical system embodiment of the present invention; Figure 5 The diagram is a schematic diagram of the system layout of an embodiment of a multi-sensor mileage trigger system of the present invention.

[0038] Explanation of symbols in the figure: 1. Mileage trigger mechanical system; 11. Radar bracket; 12. Mileage wheel; 13. Bearing; 14. Rotating shaft; 15. Telescopic spring; 16. Curved rod; 17. Straight rod; 21. Acceleration sensor; 22. Wheel speed encoder; 23. Pressure sensor; 24. Odometer calculation module; 25. Data fusion module; 26. Pulse generation module. DETAILED DESCRIPTION

[0039] In order to make the technical problems, technical solutions and beneficial effects to be solved by this application more clearly understood, the following is a further detailed description of a vehicle-mounted ground penetrating radar mileage triggering method and device based on multi-parameter fusion provided by this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0040] Example 1 See also Figure 1 The embodiment of the present invention provides a vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion, comprising the following steps: 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.

[0041] The embodiment of 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 the mileage calculation module, and the data fusion module performs the initial weight distribution through adaptive weighting, and updates the pressure correction factor in real time through the pressure sensor data at different times to perform secondary weight distribution on the mileage data, and then outputs the fused data through the pulse generation module to output a square wave pulse signal with a specific frequency change for ground penetrating radar triggering. The present invention can effectively improve the adaptability of the system to complex road conditions, and greatly facilitate the later radar data processing and disease point positioning.

[0042] Example 2 like Figure 1 As shown, this embodiment provides a vehicle-mounted ground penetrating radar mileage triggering method based on multi-parameter fusion, which specifically includes the following steps: S1. During vehicle driving, the acceleration sensor and wheel speed encoder respectively output voltage signals and square wave pulse signals 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; high-frequency sampling is used to ensure accurate recording of each sensor data, and the sampling frequency is 1khz.

[0043] S2. Convert the voltage signal collected by the acceleration sensor and the square wave pulse signal collected by the wheel speed encoder in step S1 into real-time mileage data through the mileage calculation module, and normalize the two data; update the pressure correction factor in real time according to the pressure sensor data.

[0044] The mileage calculation module reads the acceleration sensor through the SPI protocol p Measured acceleration value a ( t ), then it is converted to k Time and mileage data D p ( k ) is obtained from the following formula:

[0045]

[0046] In the formula, a ( t ) is the acceleration in the driving direction measured by the acceleration sensor (the vehicle is traveling in a straight line by default), v 0 is the initial velocity, x 0 is the initial position.

[0047] Wheel speed encoder q Measured square wave pulse signal conversion k Time and mileage data D q ( k ) is obtained from the following formula:

[0048] 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.

[0049] Pressure Sensors r Record k The pressure sensor measured value at this moment is S ( k ).

[0050] In this embodiment, in order to quickly respond to low pressure conditions, the pressure correction factor is designed α It obeys hypergeometric decay, and the formula is as follows:

[0051] 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: 1) Select three experimental scenarios including flat road, slippery road, and bumpy road; 2) Let the vehicle pass through three different road surfaces at speeds of 20km / h, 40km / h, and 60km / h; 3) Record the data collected by the pressure sensor, acceleration sensor, and wheel speed sensor in each experimental scenario, with a collection distance of 5 km; 4) The maximum value of the pressure sensor data recorded in each scenario is taken as the pressure threshold for that scenario S th ; 5) 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 .

[0052] In actual experiments, the corresponding S th and S min ,The dynamic threshold adjustment method can improve the adaptability of the system in different ,environments and avoid the misjudgment caused by fixed thresholds.

[0053] S3. The data after preprocessing in step S2 is subjected to secondary real-time weight fusion through the data fusion module. First, the wheel speed encoder mileage data and the acceleration sensor mileage data are adaptively weighted fused to initially assign data weights, and then the two mileage data are subjected to secondary data weight assignment according to the pressure correction factor.

[0054] In this embodiment, 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:

[0055]

[0056] 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.

[0057] 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, and its expression is :

[0058]

[0059] ; sensor p and q The variances of and , taking the difference between its autocorrelation function and its cross-correlation function, it can be expressed as:

[0060] ; 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 of each sampling point. k The calculation formulas of the autocorrelation function and cross-correlation function at each moment are as follows:

[0061]

[0062] ; 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:

[0063] 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:

[0064]

[0065] 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 :

[0066]

[0067] From this we can get k Time course estimation as follows: .

[0068] Furthermore, in this embodiment, in step S3, 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 Use dynamic weights; if S ( k ) ≥ S th ,but α Use a fixed weight of 1; if S ( k ) ≤ S min ,butα Use a fixed weight of 0.

[0069] The secondary distribution weight is obtained after correction by the correction factor It can be expressed as:

[0070]

[0071] After pressure correction k Time and mileage estimation for: .

[0072] S4. The fused data obtained in step S3 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.

[0073] Specifically, 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. When working, the timer is placed in PWM mode. 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:

[0074] 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:

[0075] In the formula, is the timer clock frequency, PSC is the prescaler value, ARR is the auto-reload value.

[0076] Furthermore, according to the above formula, dynamic adjustment ARR The value of can output a square wave pulse signal with a specific frequency change.

[0077] The above method of the embodiment of the present invention improves the confidence of the wheel speed encoder data through the mileage triggering mechanical structure, and distributes the weights of the two-way mileage data from the acceleration sensor and the wheel speed encoder twice through the data fusion module. By updating the weights of the two-way mileage data in real time, it can avoid false triggering caused by distortion of a single sensor data, and can cope with the complex road conditions that may be encountered during the experiment.

[0078] Example 3 like Figure 2 , Figure 4 As shown, 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 is connected to the mileage wheel 12 through a connecting mechanism. The multi-sensor mileage trigger system includes multiple sensor modules for mileage signal collection and data processor signal output.

[0079] In this embodiment, a bearing 13 and a rotating shaft 14 are connected to the radar bracket 11, and a 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, and the telescopic spring 15 is arranged between the mileage wheel 12 and the radar bracket 11.

[0080] Specifically, Figure 2 , Figure 3 As shown, the connecting bracket includes an arc rod 16 and a straight rod 17, the arc rod 16 and the straight rod 17 are arranged at an angle, the upper end of the arc rod 16 is movably connected to the radar bracket 11 through the bearing 13 and the rotating shaft 14, and the rotating shaft 14 and the bearing 13 are connected by the mileage wheel 12 to improve the flexibility of the mileage wheel 12 in the vertical direction of the ground, 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 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 rod 16, and the telescopic spring 15 is connected between the rotating shaft 14 and the straight rod 17.

[0081] 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 rod 16 through the bearing 13 and the rotating shaft 14, and the telescopic spring 15 can provide traction to increase the pressure and fit between the mileage wheel 12 and the ground.

[0082] Specifically, Figure 4As shown, when the system is on the horizontal ground, the arc rod 16 is 30° with the vertical direction, and the telescopic spring 15 is in a stretched state, which can provide 30N of traction; when the ground is convex, the arc rod 16 is at most 50° with the vertical direction, and the telescopic spring 15 can provide 50N of traction; when the ground is concave, the arc rod 16 is at least 10° with the vertical direction, and the telescopic spring 15 can provide at least 10N of traction. Based on this, the angle between the arc rod 16 and the vertical direction can be dynamically adjusted between 10° and 50°, and the corresponding adjustable height of the mileage wheel is about 20cm, which can meet the experimental scenarios under normal circumstances. When encountering uneven ground conditions, the mechanical structure can flexibly adjust the horizontal height of the mileage wheel and the spring traction to reduce its air time.

[0083] In this embodiment, Figure 5 As 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, wherein 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 predicts the current mileage according to the real-time weight allocation of the three-way sensor data, and then converts the fused mileage data into a pulse signal for ground penetrating radar triggering through the pulse generation module 26.

[0084] Furthermore, in this embodiment, the acceleration sensor 21 used is a capacitive acceleration sensor MEMS, the wheel speed encoder 22 is an MLX series, and the pressure sensor 23 is an SP40 series.

[0085] The present invention proposes a mileage triggering method and device for a vehicle-mounted ground-penetrating radar based on multi-parameter fusion, which solves the problems of radar waveform distortion and difficulty in locating defects caused by mileage data errors due to complex road conditions when the existing vehicle-mounted ground-penetrating radar collects underground information. The mileage triggering device of the present invention includes a mileage triggering mechanical system and a multi-sensor mileage triggering system, and uses a telescopic spring 15 to provide ground directional traction to the mileage wheel 12 to improve the 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 to reduce its air time.

[0086] The present invention converts the voltage signal collected by the acceleration sensor 21 and the square wave pulse signal collected by the wheel speed encoder 22 into real-time mileage data through the mileage calculation module 24, and the data fusion module 25 performs the initial weight distribution through adaptive weighting, and updates the pressure correction factor in real time through the data of the pressure sensor 23 at different times to perform the secondary weight distribution on the mileage data, and then outputs the fused data through the pulse generation module 26 to form a square wave pulse signal with a specific frequency change for ground penetrating radar triggering. The present invention can effectively improve the adaptability of the system to complex road conditions, and greatly facilitate the later radar data processing and disease point positioning.

[0087] In the description of the present invention, it is necessary to understand that the orientation or positional relationship indicated by terms such as "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application.

[0088] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0089] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should 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 ) is composed of: 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 1 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. A vehicle-mounted ground penetrating radar mileage triggering device based on multi-parameter fusion, characterized in that: It 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 device 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 device 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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