A method for life detection and positioning after disaster in coal mine based on ultra-wideband radar

Abstract

This invention discloses a method for post-disaster life detection and location in coal mines based on ultra-wideband radar, belonging to the field of radar engineering and signal processing technology. It is used for post-disaster life detection and location in coal mines, including: collecting echo signals from explosion-proof UWB radar at different preset measurement points; performing time-domain multiple differential averaging enhancement on the echo matrix of each measurement point; conducting FFT spectrum analysis on the enhanced signal; extracting candidate breathing frequencies through dynamic thresholding; confirming valid life forms and their breathing frequencies through multi-measurement point cross-verification; constructing a reference signal using the confirmed breathing frequencies; extracting the life form echo travel time by calculating the Pearson correlation coefficient; and combining the measurement point coordinates and electromagnetic wave velocity to calculate the precise three-dimensional coordinates of the life form using a time-difference positioning algorithm. This invention achieves direct enhancement of weak life signals through a time-domain multiple differential averaging algorithm, exhibiting significantly higher robustness and reliability in extreme rescue scenarios with scarce data and unknown interference patterns.

Description

Technical Field

[0001] This invention discloses a method for post-disaster life detection and location in coal mines based on ultra-wideband radar, belonging to the field of radar engineering and signal processing technology. Background Technology

[0002] Following a coal mine disaster (such as a collapse or gas explosion), quickly and accurately locating buried survivors is the primary task of rescue operations. In the post-disaster environment, survivors' vital signs (such as breathing and heartbeat) are typically extremely weak due to injuries, confined spaces, and exhaustion. Meanwhile, accident sites are often filled with high-intensity, non-stationary background noise and interference. These interference signals are often tens or even hundreds of times stronger than the target vital signs, and their frequencies widely overlap, creating an extremely complex acoustic, optical, and electromagnetic environment with a very low signal-to-noise ratio, a large dynamic range, and time-varying non-stationarity. Therefore, there is an urgent need for a coal mine post-disaster life detection solution that can balance strong anti-interference capabilities, equipment portability, detection reliability, and positioning accuracy in the complex and highly interfering post-disaster environment of underground coal mines.

[0003] Radar life detection technology, due to its non-contact and high-penetration characteristics, is widely used in the field of vital sign monitoring. One existing technology involves a life detection method and system based on radar signal processing. This method first transmits orthogonal frequency division multiplexing (OFDM) dual-frequency continuous wave radar signals to the target area, collects radar echoes, and demodulates them to obtain the baseband signal. Then, the extracted feature vectors are input into a multi-task deep learning network with an integrated attention mechanism to achieve feature fusion and target recognition, resulting in a second processed signal. Finally, by analyzing the time-frequency distribution of this signal, the time-varying characteristics and amplitude patterns of respiratory and heart rate components are extracted to determine whether life exists in the target area. A multi-base station collaborative positioning algorithm is used to calculate the three-dimensional spatial coordinates of the living organism, and the detection result, containing the spatial coordinates and the organism's characteristic information, is output. Summary of the Invention

[0004] The purpose of this invention is to provide a method for post-disaster life detection and location in coal mines based on ultra-wideband radar, in order to solve the problems in the existing technology, which requires huge computing power, has inconvenient rescue equipment, and is difficult to provide accurate location in complex mine environments.

[0005] A method for post-disaster life detection and location in coal mines based on ultra-wideband radar, comprising: S1. Using an explosion-proof ultra-wideband radar in an underground coal mine to collect echo signals, including setting up an explosion-proof host computer on the floor of the roadway outside the coal mine disaster area, using the location of the explosion-proof host computer as the coordinate origin, preset measurement point positions at different heights, and sequentially setting the air-coupled radar antenna at the measurement point positions. Operating the host computer, controlling the air-coupled radar antenna through cables, transmitting UWB pulses to the coal mine disaster area and receiving echoes, calculating the echo time window by preset relative permittivity and preset detection distance, and collecting echo signals at fixed time intervals. The explosion-proof ultra-wideband radar in an underground coal mine includes an explosion-proof host computer, cables, and an air-coupled radar antenna. S2. The echo signals from each measuring point are combined into an echo matrix. The time-domain multiple difference averaging algorithm is executed to calculate the enhanced signal. The enhanced signal is subjected to fast Fourier transform to obtain the frequency spectrum amplitude. Based on the average value and standard deviation of the frequency spectrum amplitude, a dynamic threshold is set to construct a candidate respiratory frequency set. The frequency tolerance is preset. Pairing operations are performed between different measuring points to screen effective living targets and construct the final confirmed respiratory frequency sequence. S3. Based on the finally confirmed respiratory rate, construct a reference sine wave signal with matching column number of the echo matrix, and calculate the single-row Pearson correlation coefficient between the reference sine wave signal and the echo matrix. Determine the index of the maximum value of the Pearson correlation coefficient and multiply it with the sampling interval within the echo time window to obtain the life body echo travel time. Based on the propagation speed of electromagnetic waves in the covering, use the life body echo travel time at different measurement points to calculate the spatial coordinates of the life body target.

[0006] S1 includes, S1.1, setting the location of the explosion-proof host computer as the coordinate origin, and pre-setting measurement points from low to high. Measurement points and measuring points The air-coupled radar antenna sequentially transmits UWB pulses to the coal mine disaster area at three measurement points and receives the echoes. The echo time window... Calculated from a preset relative permittivity and a preset detection distance: ; In the formula, At the speed of light, To preset the detection range, To preset the relative permittivity, The sampling interval within the echo time window. This represents the number of echo sampling points.

[0007] S1 includes S1.2, data collection at fixed time intervals dT. Secondary echo signal, satisfy: ; In the formula, This is for the integer operation.

[0008] S2 includes, S2.1, assembling the echo signals collected from each measuring point into an echo data matrix. , for OK Column, to Execute the time-domain multiple differential averaging algorithm to calculate the enhanced signal. : ; In the formula, For modulo operation, It is by A one-dimensional time series composed of elements For indexing a one-dimensional time series, for row index, , for column index, .

[0009] S2 includes, S2.2, and... Perform a fast Fourier transform to obtain frequency spectrum amplitude : ; In the formula, For Fourier transform, For discrete frequency values, At the preset vital breathing rate Within the range; Calculated using statistical methods average with standard deviation Set dynamic threshold : ; exist Internal search for all amplitudes greater than The frequency point, and determine whether the frequency point is within the range. If the frequencies are adjacent, extract the frequency with the highest frequency among the adjacent frequencies; if the frequencies are not adjacent, record them as independent frequency points. Based on the frequency point with the highest frequency among adjacent frequency points and independent frequency points, a candidate respiratory frequency set for the living target at the current measurement point is constructed. , The target number of living organisms.

[0010] S2 includes S2.3, let... , and The candidate respiratory frequencies are respectively , , ; Pairing operations include comparison. Candidate respiratory rates and Candidate respiratory rates ,set up For the preset frequency tolerance, if the following conditions are met... ,determination Corresponding frequency points and The corresponding frequency points point to the same life form target, forming a pair; right , , Candidate respiratory frequencies at different measurement points are paired up.

[0011] S2 includes S2.4, which counts the frequency of each candidate respiratory frequency in the three measurement points and the frequency point matching results. If the candidate respiratory frequency forms a pair in at least two measurement point sets, it is confirmed as a valid living target. The average of the paired candidate respiratory rates is taken as the final confirmed respiratory rate. The final confirmed respiratory rate sequence was obtained. , The target number of effective life forms.

[0012] S3 includes, S3.1, and As prior knowledge, construct and Reference sine wave signal for matrix column matching : ; In the formula, For the first The reference sine wave signal of the column; calculate and Single-row Pearson correlation coefficient ,right Find the absolute value , and search Global maximum value The travel time of the echo of living organisms for: .

[0013] S3 includes S3.2, calculation , and Life form echo travel time , and Calculate the propagation speed of electromagnetic waves in the covering. : ; according to , and Calculate the square of the distance from the living target to the measuring point: ; ; ; In the formula, For the goal of life The square of the distance, For the goal of life The square of the distance, For the goal of life The square of the distance; The target spatial coordinates of the living organism satisfy: ; ; ; In the formula, The x-axis coordinate of the living organism target. Let y be the y-coordinate of the living organism target. The z-axis coordinate of the living target.

[0014] S3 includes S3.3, which involves iterating through steps S3.1 and S3.2 based on the number of valid life targets to calculate the spatial coordinates of all valid life targets.

[0015] Compared to existing technologies, this invention offers the following advantages: extremely strong anti-interference robustness, and no reliance on large datasets or black-box models. The invention's pioneering "time-domain multiple difference averaging" algorithm, starting from the physical essence of signals, utilizes the fundamental difference in correlation between the periodicity of vital signs and the randomness of strong electromagnetic interference in mines to directly enhance weak life signals. The algorithm's principle is clear, its calculations are deterministic, and it does not rely on massive amounts of training data. In extreme rescue scenarios where data is scarce and interference patterns are unknown, its robustness and reliability are significantly higher.

[0016] The algorithm is computationally efficient, meeting the real-time requirements of rescue operations. The differential averaging, FFT, and cross-correlation algorithms described in this invention are all classic signal processing operations with controllable computational complexity, requiring no expensive GPU computing power or network connection. The entire processing flow can be completed in real time on an explosion-proof host computer deployed on-site, with a short time delay from data acquisition to outputting positioning results, fully meeting the urgent needs of coal mine disaster relief where every second counts.

[0017] The reliability of detection and decision-making is doubly guaranteed, resulting in a low false alarm rate. This invention introduces a "multi-point respiratory rate cross-validation" mechanism into its technical process. This mechanism does not add extra hardware; it provides a physically meaningful second layer of verification for the core determination of the presence of life simply by logically comparing independent measurement results from different spaces. Compared to existing technologies that rely on a single model or single sensor output for decision-making, the detection results of this invention are more reliable, effectively suppressing false alarms caused by occasional strong interference or random errors, and significantly improving the overall reliability of the system. Attached Figure Description

[0018] Figure 1 This is a flowchart of the invention; Figure 2 This is a diagram showing the relative permittivity distribution of the simulation model; Figure 3 This is a simulated echo electric field data graph of measurement point S1; Figure 4 This is a line graph showing the enhanced signal at measurement point S1; Figure 5 This is the spectrum of measurement point S1 from 0.1 to 0.5 Hz. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention are described clearly and completely below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] A method for post-disaster life detection and location in coal mines based on ultra-wideband radar, comprising: S1. Using an explosion-proof ultra-wideband radar in an underground coal mine to collect echo signals, including setting up an explosion-proof host computer on the floor of the roadway outside the coal mine disaster area, using the location of the explosion-proof host computer as the coordinate origin, preset measurement point positions at different heights, and sequentially setting the air-coupled radar antenna at the measurement point positions. Operating the host computer, controlling the air-coupled radar antenna through cables, transmitting UWB pulses to the coal mine disaster area and receiving echoes, calculating the echo time window by preset relative permittivity and preset detection distance, and collecting echo signals at fixed time intervals. The explosion-proof ultra-wideband radar in an underground coal mine includes an explosion-proof host computer, cables, and an air-coupled radar antenna. S2. The echo signals from each measuring point are combined into an echo matrix. The time-domain multiple difference averaging algorithm is executed to calculate the enhanced signal. The enhanced signal is subjected to fast Fourier transform to obtain the frequency spectrum amplitude. Based on the average value and standard deviation of the frequency spectrum amplitude, a dynamic threshold is set to construct a candidate respiratory frequency set. The frequency tolerance is preset. Pairing operations are performed between different measuring points to screen effective living targets and construct the final confirmed respiratory frequency sequence. S3. Based on the finally confirmed respiratory rate, construct a reference sine wave signal with matching column number of the echo matrix, and calculate the single-row Pearson correlation coefficient between the reference sine wave signal and the echo matrix. Determine the index of the maximum value of the Pearson correlation coefficient and multiply it with the sampling interval within the echo time window to obtain the life body echo travel time. Based on the propagation speed of electromagnetic waves in the covering, use the life body echo travel time at different measurement points to calculate the spatial coordinates of the life body target.

[0021] S1 includes, S1.1, setting the location of the explosion-proof host computer as the coordinate origin, and pre-setting measurement points from low to high. Measurement points and measuring points The air-coupled radar antenna sequentially transmits UWB pulses to the coal mine disaster area at three measurement points and receives the echoes. The echo time window... Calculated from a preset relative permittivity and a preset detection distance: ; In the formula, At the speed of light, To preset the detection range, To preset the relative permittivity, The sampling interval within the echo time window. This represents the number of echo sampling points.

[0022] S1 includes S1.2, data collection at fixed time intervals dT. Secondary echo signal, satisfy: ; In the formula, This is for the integer operation.

[0023] S2 includes, S2.1, assembling the echo signals collected from each measuring point into an echo data matrix. , for OK Column, to Execute the time-domain multiple differential averaging algorithm to calculate the enhanced signal. : ; In the formula, For modulo operation, It is by A one-dimensional time series composed of elements For indexing a one-dimensional time series, for row index, , for column index, .

[0024] S2 includes, S2.2, and... Perform a fast Fourier transform to obtain frequency spectrum amplitude : ; In the formula, For Fourier transform, For discrete frequency values, At the preset vital breathing rate Within the range; Calculated using statistical methods average with standard deviation Set dynamic threshold : ; exist Internal search for all amplitudes greater than The frequency point, and determine whether the frequency point is within the range. If the frequencies are adjacent, extract the frequency with the highest frequency among the adjacent frequencies; if the frequencies are not adjacent, record them as independent frequency points. Based on the frequency point with the highest frequency among adjacent frequency points and independent frequency points, a candidate respiratory frequency set for the living target at the current measurement point is constructed. , The target number of living organisms.

[0025] S2 includes S2.3, let... , and The candidate respiratory frequencies are respectively , , ; Pairing operations include comparison. Candidate respiratory rates and Candidate respiratory rates ,set up For the preset frequency tolerance, if the following conditions are met... ,determination Corresponding frequency points and The corresponding frequency points point to the same life form target, forming a pair; right , , Candidate respiratory frequencies at different measurement points are paired up.

[0026] S2 includes S2.4, which counts the frequency of each candidate respiratory frequency in the three measurement points and the frequency point matching results. If the candidate respiratory frequency forms a pair in at least two measurement point sets, it is confirmed as a valid living target. The average of the paired candidate respiratory rates is taken as the final confirmed respiratory rate. The final confirmed respiratory rate sequence was obtained. , The target number of effective life forms.

[0027] S3 includes, S3.1, and As prior knowledge, construct and Reference sine wave signal for matrix column matching : ; In the formula, For the first The reference sine wave signal of the column; calculate and Single-row Pearson correlation coefficient ,right Find the absolute value , and search Global maximum value The travel time of the echo of living organisms for: .

[0028] S3 includes S3.2, calculation , and Life form echo travel time , and Calculate the propagation speed of electromagnetic waves in the covering. : ; according to , and Calculate the square of the distance from the living target to the measuring point: ; ; ; In the formula, For the goal of life The square of the distance, For the goal of life The square of the distance, For the goal of life The square of the distance; The target spatial coordinates of the living organism satisfy: ; ; ; In the formula, The x-axis coordinate of the living organism target. Let y be the y-coordinate of the living organism target. The z-axis coordinate of the living target.

[0029] S3 includes S3.3, which involves iterating through steps S3.1 and S3.2 based on the number of valid life targets to calculate the spatial coordinates of all valid life targets.

[0030] The following description, in conjunction with the accompanying drawings and embodiments, further illustrates the process of this invention. Figure 1As shown, an explosion-proof ultra-wideband radar for underground coal mines is used to collect echo signals. This includes installing an explosion-proof host computer on the floor of the roadway outside the coal mine disaster area. Using the location of the host computer as the coordinate origin, different height measurement points are preset. Air-coupled radar antennas are sequentially placed at these measurement points. The host computer is operated to control the air-coupled radar antennas via cables, transmitting UWB pulses into the coal mine disaster area and receiving echoes. The echo time window is calculated using preset relative permittivity and preset detection distance. Echo signals are collected at fixed time intervals. The explosion-proof ultra-wideband radar for underground coal mines includes an explosion-proof host computer, cables, and air-coupled radar antennas. The echo signals from each measurement point are combined into an echo matrix. A time-domain multiple differential averaging algorithm is executed to calculate the enhanced signal. A strong signal is subjected to a Fast Fourier Transform (FFT) to obtain the frequency spectrum amplitude. Based on the average value and standard deviation of the frequency spectrum amplitude, a dynamic threshold is set to construct a candidate respiratory frequency set. A frequency tolerance is preset, and pairing operations are performed between different measurement points to screen valid living targets and construct a final confirmed respiratory frequency sequence. Based on the final confirmed respiratory frequencies, a reference sine wave signal with matching echo matrix column numbers is constructed, and the single-row Pearson correlation coefficient between the reference sine wave signal and the echo matrix is ​​calculated. The index of the maximum value of the Pearson correlation coefficient is determined and multiplied by the sampling interval within the echo time window to obtain the living target echo travel time. Based on the propagation speed of electromagnetic waves in the covering, the spatial coordinates of the living target are calculated using the living target echo travel time at different measurement points.

[0031] The implementation method is further illustrated by a numerical simulation example. The electromagnetic wave field numerical simulation code is implemented based on the time-domain finite-difference algorithm of the two-dimensional Maxwell's equations, and the boundary adopts a PML perfectly matched layer absorbing boundary. Since this simulation is in a 2D plane, all y-coordinates are 0.

[0032] Using an explosion-proof ultra-wideband radar operating in the 500MHz to 1GHz frequency band for underground coal mines as a single transceiver module, the explosion-proof host computer is placed on a safe and stable roadway floor outside the suspected rescue area to establish a system such as... Figure 2 The simulation model of the relative permittivity distribution shown is 3.5m wide and 2.9m high, with the model origin as the coordinate origin (0, 0, 0). The center point of the human chest cavity cross-section is set at (2.38, 0, 0.66), approximately 36cm long and 25cm wide, and placed at a 45° angle. Based on a preset respiratory rate of 0.3Hz, the size of the chest cavity cross-section changes over time. The relative permittivity of air is 1, and there are two types of covering materials with relative permittivity of 3 and 6 respectively. The equivalent relative permittivity of the human chest cavity cross-section is set to 50. The emission source is a Ricker wavelet with a center frequency of 800MHz.

[0033] The coordinates of the three measuring points are s1(0.3,0,0.7), s2(0.3,0,1.4), and s3(0.3,0,2.2). The preset target detection distance is... Take the global equivalent relative permittivity Time window , , Number of repeated samples , The simulated echo electric field E at each measuring point is obtained, such as... Figure 3 As shown, this forms the data matrix S.

[0034] Life signal enhancement, extraction, and cross-validation based on time-domain multiple difference averaging algorithm. Calculation of enhanced signal. The result is as follows Figure 4 As shown, and for the enhanced signal Perform a Fast Fourier Transform (FFT) to obtain its frequency spectrum amplitude. .

[0035] ; Preset life breathing rate The range is Its spectrum is as follows Figure 5 As shown. A set of candidate respiratory frequencies was obtained using statistical methods. Assuming a small frequency tolerance After picking candidate respiratory rates at measurement points s1, s2, and s3 respectively, it was determined that this model has one vital signal with a frequency of [missing information]. As is consistent with the model preset, the method of this patent can obviously effectively pick up the preset respiratory rate signal.

[0036] by Construct a sine wave and calculate the Pearson coefficients for each row of the S matrix. And extract the index of the maximum modulus. The maximum indexes of the three measurement points are respectively , , The echo travel time of the living organism was calculated, and the final three-dimensional coordinates of the target living organism were calculated to be (2.13,0,0.64). This position is the electromagnetic reflection point on the surface of the chest cavity, which is 0.25m away from the center position of the preset chest cavity section of the model. This can accurately locate the position of the trapped person.

[0037] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for post-disaster life detection and location in coal mines based on ultra-wideband radar, characterized in that, include: S1. Using an explosion-proof ultra-wideband radar in an underground coal mine to collect echo signals, including setting up an explosion-proof host computer on the floor of the roadway outside the coal mine disaster area, using the location of the explosion-proof host computer as the coordinate origin, preset measurement point positions at different heights, and sequentially setting the air-coupled radar antenna at the measurement point positions. Operating the host computer, controlling the air-coupled radar antenna through cables, transmitting UWB pulses to the coal mine disaster area and receiving echoes, calculating the echo time window by preset relative permittivity and preset detection distance, and collecting echo signals at fixed time intervals. The explosion-proof ultra-wideband radar in an underground coal mine includes an explosion-proof host computer, cables, and an air-coupled radar antenna. S2. The echo signals from each measuring point are combined into an echo matrix. The time-domain multiple difference averaging algorithm is executed to calculate the enhanced signal. The enhanced signal is subjected to fast Fourier transform to obtain the frequency spectrum amplitude. Based on the average value and standard deviation of the frequency spectrum amplitude, a dynamic threshold is set to construct a candidate respiratory frequency set. The frequency tolerance is preset. Pairing operations are performed between different measuring points to screen effective living targets and construct the final confirmed respiratory frequency sequence. S3. Based on the finally confirmed respiratory rate, construct a reference sine wave signal with matching column number of the echo matrix, and calculate the single-row Pearson correlation coefficient between the reference sine wave signal and the echo matrix. Determine the index of the maximum value of the Pearson correlation coefficient and multiply it with the sampling interval within the echo time window to obtain the life body echo travel time. Based on the propagation speed of electromagnetic waves in the covering, use the life body echo travel time at different measurement points to calculate the spatial coordinates of the life body target.

2. The method for post-disaster life detection and location in coal mines based on ultra-wideband radar according to claim 1, characterized in that, S1 includes, S1.1, setting the location of the explosion-proof host computer as the coordinate origin, and pre-setting measurement points from low to high. Measurement points and measuring points The air-coupled radar antenna sequentially transmits UWB pulses to the coal mine disaster area at three measurement points and receives the echoes. The echo time window... Calculated from a preset relative permittivity and a preset detection distance: ； In the formula, At the speed of light, To preset the detection range, To preset the relative permittivity, The sampling interval within the echo time window. This represents the number of echo sampling points.

3. A method for post-disaster life detection and location in coal mines based on ultra-wideband radar according to claim 2, characterized in that, S1 includes S1.2, data collection at fixed time intervals dT. Secondary echo signal, satisfy: ； In the formula, This is for the integer operation.

4. A method for post-disaster life detection and location in coal mines based on ultra-wideband radar according to claim 3, characterized in that, S2 includes, S2.1, assembling the echo signals collected from each measuring point into an echo data matrix. , for OK Column, to Execute the time-domain multiple differential averaging algorithm to calculate the enhanced signal. : ； In the formula, For modulo operation, It is by A one-dimensional time series composed of elements For indexing a one-dimensional time series, for row index, , for column index, .

5. A method for post-disaster life detection and location in coal mines based on ultra-wideband radar according to claim 4, characterized in that, S2 includes, S2.2, and... Perform a fast Fourier transform to obtain frequency spectrum amplitude : ； In the formula, For Fourier transform, For discrete frequency values, At the preset vital breathing rate Within the range; Calculated using statistical methods average with standard deviation Set dynamic threshold : ； exist Internal search for all amplitudes greater than The frequency point, and determine whether the frequency point is within the range. If the frequencies are adjacent, extract the frequency with the highest frequency among the adjacent frequencies; if the frequencies are not adjacent, record them as independent frequency points. Based on the frequency point with the highest frequency among adjacent frequency points and independent frequency points, a candidate respiratory frequency set for the living target at the current measurement point is constructed. , The target number of living organisms.

6. A method for post-disaster life detection and location in coal mines based on ultra-wideband radar according to claim 5, characterized in that, S2 includes S2.3, let... , and The candidate respiratory frequencies are respectively , , ; Pairing operations include comparison. Candidate respiratory rates and Candidate respiratory rates ,set up For the preset frequency tolerance, if the following conditions are met... ,determination Corresponding frequency points and The corresponding frequency points point to the same life form target, forming a pair; right , , Candidate respiratory frequencies at different measurement points are paired up.

7. A method for post-disaster life detection and location in coal mines based on ultra-wideband radar according to claim 6, characterized in that, S2 includes S2.4, which counts the frequency of each candidate respiratory frequency in the three measurement points and the frequency point matching results. If the candidate respiratory frequency forms a pair in at least two measurement point sets, it is confirmed as a valid living target. The average of the paired candidate respiratory rates is taken as the final confirmed respiratory rate. The final confirmed respiratory rate sequence was obtained. , The target number of effective life forms.

8. A method for post-disaster life detection and location in coal mines based on ultra-wideband radar according to claim 7, characterized in that, S3 includes, S3.1, and As prior knowledge, construct and Reference sine wave signal for matrix column matching : ； In the formula, For the first The reference sine wave signal of the column; calculate and Single-row Pearson correlation coefficient ,right Find the absolute value , and search Global maximum value The travel time of the echo of living organisms for: 。 9. A method for post-disaster life detection and location in coal mines based on ultra-wideband radar according to claim 8, characterized in that, S3 includes S3.2, calculation , and Life form echo travel time , and Calculate the propagation speed of electromagnetic waves in the covering. : ； according to , and Calculate the square of the distance from the living target to the measuring point: ； ； ； In the formula, For the goal of life The square of the distance, For the goal of life The square of the distance, For the goal of life The square of the distance; The target spatial coordinates of the living organism satisfy: ； ； ； In the formula, The x-axis coordinate of the living organism target. Let y be the y-coordinate of the living organism target. The z-axis coordinate of the living target.

10. A method for post-disaster life detection and location in coal mines based on ultra-wideband radar according to claim 9, characterized in that, S3 includes S3.3, which involves iterating through steps S3.1 and S3.2 based on the number of valid life targets to calculate the spatial coordinates of all valid life targets.

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