Ice detection radar equipment and method based on peak detection

Abstract

In order to solve the technical defects in the prior art, the invention provides an ice detection radar device and method based on peak detection, the complexity and cost of the device are increased due to the fact that an additional instrument needs to be arranged on an ice cover in the existing ice thickness detection technology, and the requirement for the environment is high, the technical scheme provided by the invention is as follows: the ice detection radar device based on peak detection is used for solving the technical defects in the prior art. Comprising an ice measurement signal acquisition unit, and the acquisition unit comprises an FPGA chip which comprises a time sequence control module and a data processing module; the time sequence control module is connected with the sampling circuit, and the sampling circuit is used for being connected with an external signal receiving module; the time sequence control module is connected with the delay transmitting module, and the delay transmitting module is used for being connected with an external signal transmitting module; and the data processing module is connected with the time sequence control module and is used for calculating the ice thickness according to an external signal. The method can be applied to ice layer thickness measurement and ice cover bearing capacity calculation.

Description

Technical Field

[0001] It involves the fields of radar technology and electromagnetics. Background Art

[0002] The existing ice thickness detection technologies mainly include: manual drilling and coring to measure the thickness of the ice layer, as well as the use of seismic waves and resistivity methods.

[0003] Manual core drilling for ice thickness measurement has its drawbacks. It requires on-site drilling, which is labor-intensive, time-consuming, and labor-intensive. Manual drilling requires tools such as drill rods and drill bits, and requires personnel to operate, making it prohibitively labor-intensive for measuring large ice areas. During the drilling process, the drill bit cuts into the ice, potentially breaking or deforming it, affecting the accuracy of the measurement. Furthermore, it only provides localized ice thickness information.

[0004] Measuring ice sheet thickness using seismic wave velocity. By placing seismic instruments on the ice sheet and recording the time and velocity of seismic wave propagation, the thickness of the ice sheet can be inferred. This method offers high precision and accuracy, enabling real-time monitoring of ice sheet thickness. However, this method requires placing seismic instruments on the ice sheet, increasing the complexity and cost of the equipment, and also placing high demands on the environment in which seismic waves propagate.

[0005] The thickness of the ice sheet is estimated using georesistivity measurements. By placing georesistivity instruments on the ice sheet, changes in the subsurface resistivity are measured, thereby inferring the thickness of the ice sheet. This method offers high precision and accuracy, enabling real-time monitoring of ice sheet thickness. However, this method requires placing georesistivity instruments on the ice sheet, increasing the complexity and cost of the equipment, and placing high demands on the subsurface resistivity measurements.

[0006] In summary, the disadvantages of existing technical means for ice thickness detection are that additional instruments need to be placed on the ice sheet, which increases the complexity and cost of the equipment, has high environmental requirements, and has low measurement efficiency. Summary of the Invention

[0007] The disadvantages of existing ice thickness detection technology are that it requires additional instruments to be placed on the ice sheet, which increases the complexity and cost of the equipment and places high demands on the environment. To address these technical shortcomings of the existing technology, the present invention provides the following technical solutions:

[0008] An ice detection signal acquisition unit, the acquisition unit comprising:

[0009] FPGA chip, including timing control module and data processing module;

[0010] The timing control module is connected to the sampling circuit, and the sampling circuit is used to connect to the external signal receiving module;

[0011] The timing control module is connected to the delay transmission module, and the delay transmission module is used to connect to the external signal transmission module;

[0012] The data processing module is connected to the timing control module and is used to calculate the ice thickness according to the external signal.

[0013] Furthermore, a preferred embodiment is provided, wherein the FPGA chip further includes: a GPS module connected to the timing control module.

[0014] Furthermore, a preferred embodiment is provided, wherein the FPGA chip further comprises: a display control module connected to the timing control module, and the display control module is used to connect to an external display screen.

[0015] Furthermore, a preferred embodiment is provided, wherein the FPGA chip further comprises: a WIFI module connected to the timing control module, and the WIFI module is used to connect to an external WIFI antenna.

[0016] Furthermore, a preferred embodiment is provided, wherein the FPGA chip further comprises: a voice module connected to the timing control module, and the voice module is used to connect to an external speaker.

[0017] Furthermore, a preferred embodiment is provided, wherein the FPGA chip further comprises: a key circuit connected to the timing control module, wherein the key circuit is used to connect to an external key to realize the input of an external signal.

[0018] Based on the same inventive concept, the present invention also provides an ice detection radar device based on peak detection, and the ice detection radar device based on peak detection includes the ice detection signal acquisition unit.

[0019] Based on the same inventive concept, the present invention further provides an ice thickness measurement method based on peak detection. The method is implemented based on the ice thickness measurement radar device based on peak detection, and the method includes:

[0020] Steps for collecting preset algorithms and algorithm parameters;

[0021] The step of preprocessing the collected high-frequency electromagnetic wave echo signal according to the preset algorithm;

[0022] A step of performing peak detection on the pre-processed high-frequency electromagnetic wave echo signal;

[0023] A step of obtaining a layer detection result of the preprocessed high-frequency electromagnetic wave echo signal according to the result of the peak detection;

[0024] The step of obtaining the thickness of the ice layer according to the result of the layer detection.

[0025] Based on the same inventive concept, the present invention also provides a computer storage medium for storing a computer program. When the computer program is read by a computer, the computer executes the method described above.

[0026] Based on the same inventive concept, the present invention also provides a computer, comprising a processor and a storage medium. When the processor reads the computer program stored in the storage medium, the computer executes the method described above.

[0027] Compared with the prior art, the technical solution provided by the present invention is beneficial in that:

[0028] The ice thickness measurement method provided by the present invention utilizes electromagnetic principles to enable ground-penetrating radar to efficiently and non-destructively detect the distribution of ice layer media. This operating principle enables the solution to accurately determine the distribution of ice layer thickness.

[0029] The ice thickness measurement method provided by this invention uses peak detection and correlation detection algorithms to achieve real-time tracking of ice thickness. By setting algorithm parameters and performing data processing, the ice thickness can be accurately calculated, reducing the need for manual operation and improving measurement accuracy and efficiency. This algorithmic process enables the solution to automatically identify and calculate ice thickness.

[0030] The ice thickness measurement method provided by the present invention can collect echo data from underground media in real time and store the data in a host computer in digital form, allowing for immediate data processing and analysis. The distribution of underground media and ice thickness can be visually observed, increasing immediacy.

[0031] The ice thickness measurement method provided by the present invention can implement a voice broadcast function, which can improve safety for people who need to carry out activities on the ice surface. By broadcasting information such as ice thickness through voice, users can judge the safety of the ice surface and avoid dangers caused by thin ice. Because the information is directly conveyed by voice, users do not need to focus on the screen or other display devices, and can perform other operations or activities simultaneously. This eliminates the need for users to view the screen or other display devices, making it convenient for users to obtain measurement results in a timely manner.

[0032] The ice thickness measurement method provided by this invention can assess the bearing capacity of an ice sheet by measuring the ice thickness and applying a bearing capacity calculation formula, thereby determining the loads that can be sustained on the ice sheet and the safety of activities. This is very important for the safety of personnel and equipment on the ice sheet.

[0033] The ice thickness measurement method provided by this invention incorporates positioning information to more accurately determine the distribution of underground objects, thereby improving measurement accuracy. Positioning information provides a spatial reference for measurement results, making them more comparable and interpretable. Furthermore, it is associated with the measured data, facilitating subsequent data processing and analysis.

[0034] The ice thickness measurement method provided by this invention can complete the entire system's transmission and control functions, including timing control, radar signal conditioning, acquisition, data buffering, and preprocessing. This hardware structure enables the stable operation of peak-detection-based ice-measuring radar equipment and accurate data acquisition.

[0035] Compared with traditional ice layer measurement methods, the ice thickness measurement method provided by the present invention is capable of measuring ice layer thickness efficiently and non-destructively using ice detection radar equipment based on peak detection, without the need for destructive operations such as drilling.

[0036] The ice layer thickness measurement method provided by the present invention can be applied to ice layer thickness measurement and ice sheet bearing capacity calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a schematic diagram of the working principle of ground penetrating radar;

[0038] Figure 2 This is a schematic diagram of the ground penetrating radar echo curve;

[0039] Figure 3 This is a schematic diagram of the ice detection radar system based on peak detection;

[0040] Figure 4 This is a schematic diagram of the operation process of the ice detection radar. DETAILED DESCRIPTION

[0041] In order to make the advantages and benefits of the technical solution provided by the present invention more clearly reflected, the technical solution provided by the present invention is now further described in detail with reference to the accompanying drawings, specifically:

[0042] Embodiment 1: This embodiment provides an ice detection signal acquisition unit, which includes:

[0043] FPGA chip, including timing control module and data processing module;

[0044] The timing control module is connected to the sampling circuit, and the sampling circuit is used to connect to the external signal receiving module;

[0045] The timing control module is connected to the delay transmission module, and the delay transmission module is used to connect to the external signal transmission module;

[0046] The data processing module is connected to the timing control module and is used to calculate the ice thickness according to the external signal.

[0047] Implementation method 2: This implementation method further limits the ice detection signal acquisition unit provided in implementation method 1. The FPGA chip further includes: a GPS module connected to the timing control module.

[0048] Implementation method three: This implementation method further limits the ice detection signal acquisition unit provided in implementation method one. The FPGA chip further includes: a display control module connected to the timing control module, and the display control module is used to connect to an external display screen.

[0049] Implementation 4: This implementation further limits the ice detection signal acquisition unit provided in Implementation 1. The FPGA chip further includes: a WIFI module connected to the timing control module, and the WIFI module is used to connect to an external WIFI antenna.

[0050] Implementation method 5: This implementation method further limits the ice detection signal acquisition unit provided in implementation method 1. The FPGA chip further includes: a voice module connected to the timing control module, and the voice module is used to connect to an external speaker.

[0051] Implementation method 6: This implementation method further limits the ice detection signal acquisition unit provided in implementation method 1. The FPGA chip further includes: a key circuit connected to the timing control module, and the key circuit is used to connect an external key to realize the input of an external signal.

[0052] Embodiment 7: This embodiment provides an ice detection radar device based on peak detection, and the ice detection radar device based on peak detection includes the ice detection signal acquisition unit provided in Embodiment 1.

[0053] Embodiment 8: This embodiment provides an ice thickness measurement method based on peak detection. The method is implemented based on the ice measurement radar device based on peak detection provided in Embodiment 7. The method includes:

[0054] Steps for collecting preset algorithms and algorithm parameters;

[0055] The step of preprocessing the collected high-frequency electromagnetic wave echo signal according to the preset algorithm;

[0056] A step of performing peak detection on the pre-processed high-frequency electromagnetic wave echo signal;

[0057] A step of obtaining a layer detection result of the preprocessed high-frequency electromagnetic wave echo signal according to the result of the peak detection;

[0058] The step of obtaining the thickness of the ice layer according to the result of the layer detection.

[0059] Specifically, the methods include:

[0060] Step 1: Algorithm parameter setting

[0061] Configure parameters related to data files, such as storage path, header byte length, etc.

[0062] Set the filter parameters, including the FIR filter order, filter type, and cutoff frequency.

[0063] Set the initial layer position and roughly set the radar wave layer positions for the upper and lower layers of the ice surface.

[0064] Set the number of A-Scan data channels collected at each measuring point, generally 2 to the power of N.

[0065] Step 2: Data preprocessing

[0066] The data format processed by the algorithm is multi-channel A-Scan data with time as the horizontal axis, and each channel of A-Scan data contains 1024 sampling points.

[0067] The sampled data is filtered using a bandpass FIR filter to remove high-frequency and low-frequency noise.

[0068] Step 3: Ice surface peak detection

[0069] Peak detection is used on each A-scan data channel to search near the initially set upper layer of the ice surface. The extreme value is recorded as the upper layer reference signal. The ice surface position detected by multiple data channels is averaged to obtain the ice layer position. This signal is also recorded as the ice surface position reference signal.

[0070] Step 4: Ice bottom peak detection algorithm

[0071] The background of multiple A-Scan data is removed, and then each A-Scan data is processed and back-differentiated to obtain a differential sequence.

[0072] The difference function is binarized to obtain a binarized sequence.

[0073] Perform the difference operation on the binarized sequence again to obtain the peak sequence.

[0074] Traverse each positive and negative peak, take the initially set reference point of the bottom of the ice layer as the starting point, and search for the maximum value on both sides to determine the peak position of the bottom of the ice layer.

[0075] The ice bottom position detected by multiple channels of data is averaged and recorded as the ice bottom position. This signal is then used as the ice bottom position reference signal.

[0076] In single-point acquisition mode, proceed directly to step 7. In continuous acquisition mode, steps 5 and 6 are also required:

[0077] Step 5: Related calculations

[0078] Use the FFT algorithm to perform correlation calculations between the reference signal and the acquired signal to quickly determine the layer position.

[0079] Fine positioning correction is performed through peak detection to reduce positioning errors.

[0080] Step 6: Exception handling

[0081] Handle situations such as tracking loss and abnormal jumps, including expanding the search range to re-detect, using the previous detection data and skipping detection, etc., to enhance the robustness of the algorithm.

[0082] Step 7: Calculate ice thickness

[0083] The ice thickness is calculated by combining the average ice surface and ice bottom layers calculated from the multi-channel A-Scan data obtained in steps 3 and 4, and combining the sampling rate and the electromagnetic parameters of the ice.

[0084] Implementation method 9: This implementation method provides a computer storage medium for storing a computer program. When the computer program is read by a computer, the computer executes the method provided in implementation method 7.

[0085] Implementation 10: This implementation provides a computer, including a processor and a storage medium. When the processor reads the computer program stored in the storage medium, the computer executes the method provided in Implementation 7.

[0086] Implementation Method 11: Combination Figure 1-4 This embodiment further describes the above technical solution in detail and completely through specific examples, specifically:

[0087] Ground penetrating radar is different from traditional radar. It is a detection instrument for detecting the distribution of underground media. It has the characteristics of high efficiency and non-destructiveness. Its working principle is as follows Figure 1 Utilizing electromagnetic principles, the radar transmits high-frequency electromagnetic waves underground, receives reflected echoes, and determines the distribution of underground objects based on the echo characteristics. The received echoes are stored as data in a host computer, where various data processing operations can be performed and then displayed using data visualization methods.

[0088] Echo curve Figure 2As shown in Figure 2, when electromagnetic waves propagate underground, the distribution and composition of the underground medium will cause the echo to change. Therefore, the underground medium can be interpreted based on the characteristics of the echo, such as time delay and amplitude.

[0089] The handheld ice detection radar equipment system based on peak detection consists of a pulse receiving / transmitting unit, a signal acquisition unit (i.e., ice detection signal acquisition unit), and display and control peripherals. The signal acquisition unit is the core part of the system, and its main functions are: the signal acquisition unit receives information sent by peripherals such as buttons, and sets the equipment, including setting parameters and control commands, such as sampling frequency, number of sampling points, dielectric constant, detection mode, average channel number and other acquisition parameters, while completing the timing control of the entire system, radar signal conditioning, acquisition, data buffering, preprocessing and other transmission and control functions, and can transmit data to the cloud server in an orderly manner through the WIFI module, playing a role in controlling the operation of the entire radar system. Figure 3 shown.

[0090] The ice detection radar device based on peak detection is powered by 12V voltage. The working process of the whole device is as follows: the device is powered on by long pressing the switch button. After power on, the signal acquisition unit communicates with the display screen through the display control part. The operator sends parameters and working instructions to the ice detection radar device based on peak detection by pressing buttons, etc. The FPGA receives the instructions, controls the DDS chip to generate the transceiver control signal and controls the AD chip to collect data. The collected data is sent to the internal cache of the FPGA, equivalent sampling splicing, filtering and other processing, and then displayed on the screen through the display control module. At the same time, the data can be sent to the cloud platform for storage, processing and display through the WIFI module. Figure 3 shown.

[0091] The ice thickness measurement algorithm mainly relies on peak detection and correlation detection, which can realize real-time tracking of ice thickness.

[0092] When setting the algorithm parameters, you need to configure parameters related to the data file, the filter, and the initial layer position. Data file parameters include the read path and header byte length. Correctly setting these parameters ensures accurate reading of A-Scan data. Filter parameters involve the FIR filter order, filter type, and cutoff frequency. These parameters are used to calculate the FIR filter response. The initial layer position is set for the radar wave layer in the first data entry for the direct wave, upper ice layer, and lower ice layer. Excessive precision is not required, as these are automatically corrected later.

[0093] To reduce the sudden interference errors associated with collecting only one channel of data, the algorithm processes data in the form of multiple A-Scans with time as the horizontal axis. Each A-Scan contains 1024 sampling points. The number of A-Scan channels collected can be set on the device, typically in powers of 2, with a default of 32. Because the data is raw, preliminary processing is required. The algorithm uses a bandpass FIR filter to filter the sampled data to remove high- and low-frequency noise, thereby improving the signal-to-noise ratio.

[0094] During the first detection, since there is no reference signal and a fixed layer, it is necessary to use peak detection to search near the initially set layer and take the extreme value as the layer reference position. After positioning, the signal is intercepted as the reference signal. The peak detection calculation steps are as follows:

[0095] First, perform backward difference according to the following formula: f(k) is the original sampling sequence, and g(k) is the difference sequence.

[0096]

[0097] When detecting the peak, the difference function can be simply binarized. m(k) is the binarized sequence.

[0098]

[0099] Then, we differentiate m(k) again to get the peak sequence n(k). The value of 1 indicates a positive peak, and the value of -1 indicates a negative peak.

[0100]

[0101] Traverse each positive and negative peak and find the maximum value.

[0102] Starting from the second detection, the reference signal and the acquired signal are correlated using the FFT algorithm to quickly determine the layer position. Based on this, fine positioning correction is performed through peak detection to reduce positioning errors. Based on the current positioning position, the intercepted signal is used as the newly generated reference signal, mixed with the original signal at a weight of 1:9, and the reference signal is updated for subsequent detection. The relevant calculation steps are as follows:

[0103] According to the parity and even imaginary and real properties, we can know that for real sequence x(n):

[0104] DFT(x(n))=X(k)DFT(x(-n))=X * (k);

[0105] FFT can be considered as linear convolution if the following equation is satisfied: where N1 is the original length of the x(i) sequence, N2 is the original length of the y(i) sequence, and N is the length of the x(i) and y(i) sequences after zero padding.

[0106] N1+N2-1≤N;

[0107] Therefore, the correlation calculation can be written as follows. Where x(i) is the sequence to be detected, y(i) is the reference signal sequence, r xy (k) is the sequence of correlation functions.

[0108]

[0109] From the above formula, we can know that we can calculate the FFT transforms X(k) and Y(k) of x(n) and y(n) respectively, take the conjugate of Y(k), and then multiply them to get the inverse transform.

[0110] The exception handling section is used to handle situations such as tracking loss and abnormal jumps. Methods for handling this problem include expanding the search range and retesting, using the last detection data and skipping detection, etc. Exception handling can enhance the robustness of the algorithm.

[0111] Ultimately, by integrating the layer calculated from each A-Scan data, combined with the sampling rate and the electromagnetic parameters of the ice, the ice thickness can be calculated, achieving the goal of the automatic ice thickness identification algorithm.

[0112] This embodiment also provides a method for calculating the ice sheet bearing capacity, including:

[0113] P=Ah 2 ;

[0114] Where P is the allowable bearing capacity, in t; h is the effective thickness of ice, in m; A is a coefficient determined by the ice strength, crack coefficient, and temperature influence coefficient. The specific formula is as follows:

[0115]

[0116] Where N represents the strength and crack coefficient. The default value is N = 1 for cracks and N = 1.143 for no cracks. K represents the temperature influence coefficient, and e is the absolute value of the average temperature over the past three days. K only works when the average temperature is below zero. For zero and above, K = 1.

[0117] The above bearing capacity calculation formula is for intact, well-frozen ice sheets and is not applicable to accumulated ice sheets or ice sheets with cracks. Furthermore, the ice sheet thickness for a single person walking on it should be at least 10 cm, for a snowmobile at least 18 cm, and for a 4x4 vehicle at least 38 cm.

[0118] In January 2024, the equipment was tested on the surface of the Songhua River in Harbin, Heilongjiang Province, and a set of data was collected. The average temperature for the first three days was -18°C. A hole drilling verification was performed. The drilling results were consistent with those measured by a handheld peak detection-based ice detection radar device, with an absolute measurement error of less than 0.5cm. As shown in the following table:

[0119]

[0120] The above further describes the technical solution provided by the present invention in detail through several specific embodiments in order to highlight the advantages and benefits of the technical solution provided by the present invention. However, the several specific embodiments described above are not intended to limit the present invention. Any reasonable modification and improvement of the present invention, combination of embodiments and equivalent replacement based on the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0121] The descriptions in this specification refer only to preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Furthermore, reference to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples" implies that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative descriptions of these 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 any one or N embodiments or examples. Furthermore, those skilled in the art may combine and integrate the different embodiments or examples described in this specification, as well as features from different embodiments or examples, unless otherwise specified. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed to indicate or imply relative importance or to implicitly specify the number of the technical features indicated. Therefore, features designated "first" or "second" may explicitly or implicitly include at least one of these features. In the description of the present invention, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined. Any process or method description in a flowchart or otherwise described herein can be understood to represent a module, segment, or portion of code comprising one or more executable instructions for implementing a custom logic function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may be performed in a different order than shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which the embodiments of the present invention pertain. The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing a logic function, can be embodied in any computer-readable medium for use by an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device), or in conjunction with such instruction execution systems, apparatuses, or devices. For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by an instruction execution system, apparatus, or device, or in conjunction with such instruction execution systems, apparatuses, or devices. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection having one or N wirings (electronic devices), a portable computer disk cartridge (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read-only memory (CDROM).In addition, the computer-readable medium may even be paper or other suitable medium on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, then editing, interpreting, or processing in other suitable ways as necessary, and then storing it in a computer memory. It should be understood that the various parts of the present invention can be implemented with hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented with software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented with hardware, as in another embodiment, any one of the following technologies known in the art or their combination can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0122] Those skilled in the art will appreciate that all or part of the steps carried out in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment. In addition, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

Claims

1. Ice detection signal acquisition unit, characterized in that: The acquisition unit includes: FPGA chip, including timing control module and data processing module; The timing control module is connected to the sampling circuit, and the sampling circuit is used to connect to the external signal receiving module; The timing control module is connected to the delay transmission module, and the delay transmission module is used to connect to the external signal transmission module; The data processing module is connected to the timing control module and is used to calculate the ice thickness according to the external signal.

2. The ice detection signal acquisition unit according to claim 1, characterized in that: The FPGA chip also includes a GPS module connected to the timing control module.

3. The ice detection signal acquisition unit according to claim 1, characterized in that: The FPGA chip further includes: a display control module connected to the timing control module, and the display control module is used to connect to an external display screen.

4. The ice detection signal acquisition unit according to claim 1, characterized in that: The FPGA chip further includes: a WIFI module connected to the timing control module, and the WIFI module is used to connect to an external WIFI antenna.

5. The ice detection signal acquisition unit according to claim 1, characterized in that: The FPGA chip further includes: a voice module connected to the timing control module, and the voice module is used to connect to an external speaker.

6. The ice detection signal acquisition unit according to claim 1, characterized in that: The FPGA chip further includes: a key signal processing circuit connected to the timing control module, and the key circuit is used to connect to an external key to realize the input of an external signal.

7. An ice detection radar device based on peak detection, comprising the ice detection signal acquisition unit according to claim 1.

8. The ice thickness measurement method based on peak detection is characterized by: The method is implemented based on the peak detection-based ice detection radar device according to claim 7, and the method includes: Steps for collecting preset algorithms and algorithm parameters; The step of preprocessing the collected high-frequency electromagnetic wave echo signal according to the preset algorithm; A step of performing peak detection on the pre-processed high-frequency electromagnetic wave echo signal; A step of obtaining a layer detection result of the preprocessed high-frequency electromagnetic wave echo signal according to the result of the peak detection; The step of obtaining the thickness of the ice layer according to the result of the layer detection.

9. A computer storage medium for storing a computer program, wherein when the computer program is read by a computer, the computer executes the method according to claim 8.

10. A computer comprising a processor and a storage medium, wherein when the processor reads a computer program stored in the storage medium, the computer executes the method according to claim 8.

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