Tree height measurement method based on woodpecker bionic vibration mark and millimeter wave radar

Abstract

The invention discloses a tree height measurement method based on a woodpecker bionic vibration mark and a millimeter wave radar, and relates to the field of tree height measurement, and the tree height measurement method comprises the steps: simplifying the vibration of tree crowns, branches and leaves into a spring-damping model; the working parameters of the wood pecking machine are adjusted through the pecking strength selection model, so that the optimal pecking frequency and force amplitude are achieved; determining three-dimensional coordinates of the tree bottom based on the configured communication signals of the UWB foot ring and the UWB base station and a compensation strategy; predicting an expected vibration mode of pecking branches and leaves of a current tree crown by using a spring-damping model, and obtaining a to-be-processed signal related to tree crown vibration in vibration signals captured by a radar; separating noise signals from the to-be-processed signals through a filtering model to obtain crown vibration signals; marking a crown feature area through the crown vibration signal; the three-dimensional coordinates of the tree top are calculated through the marked tree crown feature region, and the tree height is obtained according to the attenuation model, the three-dimensional coordinates of the tree top and the three-dimensional coordinates of the tree bottom, so that the accuracy of tree height measurement is improved.

Description

Technical Field

[0001] The present invention relates to the field of tree height measurement, and in particular to a tree height measurement method based on woodpecker bionic vibration marking and millimeter wave radar. Background Art

[0002] In the current field of tree height measurement, although a variety of methods and technical means have been widely used, there are still some significant technical challenges. First, traditional methods based on laser ranging or optical image analysis are powerless when faced with dense forest environments, especially in areas with high vegetation coverage. Due to the limited penetration of light, these methods are difficult to provide accurate tree height data. In addition, the difficulty of operation under complex terrain conditions further limits the application scope and accuracy of these technologies. Therefore, how to achieve accurate and rapid measurement of tree height in various environments without affecting the ecological environment has become an urgent problem to be solved.

[0003] On the other hand, with the development of wireless communication technology and radar detection technology, although UWB (ultra-wideband) technology and millimeter-wave radar have begun to be applied to the detection and monitoring of natural objects such as trees, they still face many challenges in practical application. For example, UWB signals will experience severe attenuation and multipath effects when passing through vegetation layers, which not only reduces signal quality but also affects positioning accuracy. These problems are particularly prominent in conditions of high humidity and dense vegetation cover. Therefore, developing a technical solution that can effectively compensate for UWB signal attenuation and reduce the impact of multipath effects is crucial to improving the accuracy of tree height measurement.

[0004] Furthermore, the existing technology also has deficiencies in processing vibration signals. Trees are affected by external factors (such as wind speed, woodpecker pecking, etc.) to produce complex vibration patterns, and existing vibration signal processing technologies are often unable to effectively separate useful vibration information from noise, especially when the background noise is strong. This problem is more obvious. Therefore, how to construct an effective filtering model to improve the signal-to-noise ratio of the vibration signal and accurately extract vibration information that reflects the structural characteristics of the tree has become the key to improving the technical level of tree health monitoring and growth status assessment. The existence of the above problems has promoted the proposal and development of the present invention. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention proposes a tree height measurement method based on woodpecker bionic vibration markers and millimeter wave radar, which is applied to a tree height detection system. The system includes:

[0006] The ground calibration platform includes: a woodpecker for generating mechanical vibrations on the tree trunk; a UWB foot ring for calibrating the position of the tree bottom;

[0007] The aerial detection platform includes: a radar for capturing vibration signals caused by the woodpecker on the trees being tested; a UWB base station for communicating with the UWB foot ring;

[0008] The tree height measurement method comprises the steps of:

[0009] The optimal UWB signal frequency band is obtained by conducting penetration tests at different UWB signal frequency bands; an attenuation model is constructed based on environmental factors and the UWB signal attenuation coefficient; and a compensation strategy is developed to compensate for UWB signal attenuation and time delay caused by multipath effects.

[0010] The vibration of tree crown branches and leaves was simplified into a spring-damper model, and the vibration parameters were determined. A filtering model was constructed to separate the tree crown vibration signal from the noise signal. A pecking intensity selection model was constructed based on the woodpecker's pecking frequency, the maximum displacement detectable by the radar, and the natural frequency of the tree crown. The UWB leg ring and UWB base station were configured using the obtained optimal UWB signal frequency band and attenuation model. The pecking intensity selection model was used to adjust the woodpecker's operating parameters to achieve the optimal pecking frequency and force amplitude.

[0011] The three-dimensional coordinates of the tree base are determined based on the communication signals between the configured UWB foot ring and the UWB base station, as well as the compensation strategy. The woodpecker, after adjusting its parameters, pecks the tree trunk and uses a spring-damper model to predict the expected vibration pattern of the crown branches and leaves under the current pecking. The processed signal related to the crown vibration is obtained from the vibration signal captured by the radar. The noise signal in the processed signal is separated using a filtering model to obtain the crown vibration signal. The crown vibration signal is then used to mark the characteristic areas of the crown.

[0012] The three-dimensional coordinates of the tree top are calculated by marking the characteristic area of ​​the tree crown, and the tree height is obtained based on the attenuation model, the three-dimensional coordinates of the tree top and the three-dimensional coordinates of the tree base.

[0013] Furthermore, the environmental factors include: vertical thickness of the canopy and leaf area index;

[0014] The formula of the attenuation model is:

[0015] L toatl =L FS +L canopy +L multipath ;in:

[0016]

[0017] Where, L toatl Indicates the total loss; L FS represents the free space path loss; L canopy represents the canopy penetration loss; L multipathrepresents multipath attenuation; p1 and p2 are path loss coefficients; f represents signal frequency; d represents propagation distance; c represents the speed of light; d canpoy represents the vertical thickness of the canopy through which the signal passes; LAI represents the leaf area index; MC represents the ambient humidity; k1, k2, and k3 represent the canopy penetration coefficient; η represents the ambient reflection coefficient; h branch Indicates the vertical distance from the bottom of the canopy to the ground.

[0018] Furthermore, the compensation strategy is constructed as follows:

[0019] Fit a multivariable nonlinear equation to predict signal loss:

[0020] Where, k1, k2, k3, k4, k5, and k6 are canopy penetration coefficients; L toatl Indicates the total loss;

[0021] The goodness of fit of the multivariate nonlinear equation is tested by an evaluation formula; the evaluation formula is:

[0022] Where, L m Indicates the measured value, that is, the actual observed signal loss, L p Represents the predicted value, i.e., the signal loss calculated by the multivariable nonlinear equation, Represents the average value of the measured values ​​obtained by multiple measurements; R 2 represents the coefficient of determination;

[0023] Adjusting the canopy penetration coefficient of the multivariable nonlinear equation based on the value of the determination coefficient to obtain the target multivariable nonlinear equation;

[0024] A compensation strategy is constructed based on the target multivariable nonlinear equation. The construction formula of the compensation strategy is:

[0025] L compensted =L total -aexp(-hb ranc h);

[0026] Where a represents the compensation amplitude, L compensted Indicates the total loss after compensation.

[0027] Furthermore, the three-dimensional coordinates of the tree bottom are determined based on the communication signal between the configured UWB foot ring and the UWB base station and the compensation strategy, specifically:

[0028] The communication signal is compensated by the compensation strategy, and the communication parameters are calculated based on the compensated communication signal: the straight-line distance between the UWB tag in the UWB foot ring and any UWB antenna in the UWB base station, and the azimuth and elevation angles between the UWB tag and each UWB antenna;

[0029] According to the calculated communication parameters and the coordinates of the detection platform above (x u ,y u ,z u ) Calculate the three-dimensional coordinates of the tree bottom (x b ,y b ,z b ); The calculation formula for the three-dimensional coordinates of the tree bottom is:

[0030]

[0031] Where θ represents the elevation angle of any UWB antenna, and φ represents the azimuth angle of the UWB antenna corresponding to θ; D is represents the straight-line distance between the UWB tag and the UWB antenna corresponding to θ.

[0032] Furthermore, the spring-damper model is used to predict the expected vibration mode of the crown branches and leaves under the current pecking, and the signal to be processed related to the crown vibration in the vibration signal captured by the radar is obtained, specifically:

[0033] The vibration displacement z(t) of the crown branches and leaves is predicted by the correlation formula between the Doppler frequency shift and vibration velocity measured by radar and the spring-damping model; the formula of the spring-damping model is: az"+bz'+cz=F0sin(2πf p t); the relevant relationship is:

[0034] Where F0 represents the amplitude of the pecking force; f p represents the pecking frequency; t represents the pecking time point; a, b, and c represent the inversion parameters, where a represents the inertia parameter of the spring-damper model, b represents the resistance motion parameter, and c represents the spring restoring force strength parameter; z′=f d , represents the vibration velocity; z″ represents the vibration acceleration, and z represents the vibration displacement of the crown branches and leaves;

[0035] According to the vibration displacement z(t), a formula for obtaining the phase change caused by the micro-deformation due to vibration is constructed. The expression of the formula is: Where z(t) = Δz; ω represents the radar wave incident angle, λ represents the radar wavelength, and Δξ represents the phase change caused by micro-deformation.

[0036] Based on the phase change acquisition formula, the predicted vibration displacement z(t) is mapped to the phase change of the radar echo signal to obtain the signal to be processed related to the crown vibration; the mapping formula is:

[0037] Where,

[0038] Δξ(t) represents the radar phase change caused by the vibration displacement of the crown branches and leaves from time 0 to time t; 4π represents the constant term, which is used to convert the displacement change into the phase change; z(o) represents the vibration displacement at time point o; cos(ω) represents the cosine value of the radar wave incident angle ω; do is the differential symbol, which represents a small increment to time point o.

[0039] Furthermore, the construction of a filtering model for separating the crown vibration signal and the noise signal is specifically as follows:

[0040] A mixed noise model is constructed to separate the different types of signal components received by the radar. The model formula is:

[0041] S r (t) = S v (t)+S w (t)+S c (t)+S t (t); where S v (t) is the crown vibration signal, S w (t) is the wind noise, S c (t) is the interference noise reflected by the neighboring tree, S t (t) is Gaussian white noise, S r (t) represents the signal to be processed;

[0042] The weight value of the adaptive filter is updated based on the wind speed sensor data, and the wind noise in the mixed noise model is suppressed based on the updated adaptive filter. The update formula is:

[0043] w(n+1)=w(n)+ue(n)S wr (n)

[0044] e(n)=S w (n)-w T (n)S w (n);

[0045] Where w(n) represents the current weight vector of the adaptive filter, e(n) represents the error signal vector, which represents the difference between the output of the adaptive filter and the actual wind noise signal; n represents the discrete time index; S wr (n) represents wind speed sensor data; u is the step factor; T represents matrix transpose;

[0046] A time-frequency domain joint filtering function is established, through which the crown vibration characteristics of the mixed noise model suppressed by the adaptive filter are enhanced.

[0047] Furthermore, the formula expression of the pecking intensity selection model is:

[0048]

[0049] Where, f p represents the pecking frequency, f0 represents the crown natural frequency, Z max represents the maximum displacement that can be detected by the radar; k1 and k2 represent the canopy penetration coefficient; F opt Indicates the optimal pecking intensity.

[0050] Furthermore, the pecking intensity selection model is used to adjust the working parameters of the woodpecker to achieve the optimal pecking frequency and force amplitude, specifically:

[0051] Set the acceptable range of pecking frequency to avoid resonance with the natural frequency of the crown, and adjust the pecking frequency within the acceptable range so that the F in the pecking intensity selection model opt Reached maximum value.

[0052] Furthermore, the three-dimensional coordinates of the treetop are calculated by using the marked crown feature area, specifically:

[0053] The quadratic surface fitting of the marked crown characteristic area is performed to obtain multiple equation coefficients;

[0054] The quadratic surface equation is constructed by the equation coefficients, and the three-dimensional coordinates of the tree top are calculated by the quadratic surface equation: (x t ,y t , z t );

[0055] The formula expression of the quadratic surface equation is:

[0056] zt=axt 2 +byt 2 +cxtyt+dxt+eyt+f; where:

[0057]

[0058] Where a, b, c, d, e, and f represent the coefficients of the equation.

[0059] Furthermore, the tree height is obtained according to the attenuation model, the three-dimensional coordinates of the tree top and the three-dimensional coordinates of the tree bottom, specifically:

[0060] The initial value of the tree height H is calculated by the three-dimensional coordinates of the tree bottom and the three-dimensional coordinates of the tree top. The calculation formula is: H = z t -zb;

[0061] Select the optimal signal frequency f through the attenuation model UWB ;

[0062] Based on the optimal signal frequency f UWB Calibrate the initial value H of the tree height to get the tree height; the calibration formula is:

[0063]

[0064] Where, L c represents the canopy attenuation compensation coefficient, H J Indicates the calibrated tree height.

[0065] Compared with the prior art, the present invention has at least the following beneficial effects:

[0066] (1) The present invention simplifies the vibration of the crown branches and leaves into a spring-damping model; configures the UWB foot ring and the UWB base station through the obtained optimal UWB signal frequency band and attenuation model; adjusts the working parameters of the woodpecker through the pecking intensity selection model to achieve the optimal pecking frequency and force amplitude; determines the three-dimensional coordinates of the tree bottom based on the communication signal between the configured UWB foot ring and the UWB base station and the compensation strategy; uses the woodpecker with adjusted parameters to peck the tree trunk, and uses the spring-damping model to predict the expected vibration mode of the crown branches and leaves under the current pecking, and obtains the signal to be processed related to the crown vibration in the vibration signal captured by the radar; separates the noise signal in the signal to be processed through the filtering model to obtain the crown vibration. The system uses the vibration signal of the crown to mark the characteristic area of ​​the crown; the three-dimensional coordinates of the tree top are calculated based on the marked characteristic area of ​​the crown, and the tree height is obtained based on the attenuation model, the three-dimensional coordinates of the tree top and the three-dimensional coordinates of the tree base. This method not only improves the accuracy of tree height measurement, but also adapts to the measurement needs under different environmental conditions. The mechanical vibration generated by the woodpecker is used to induce tree vibration, and the millimeter wave radar is used to capture these vibration signals to accurately calculate the tree height. This method overcomes the problem that UWB signals will suffer from severe attenuation and multipath effects when passing through the vegetation layer, resulting in reduced signal quality, and the problem that existing vibration signal processing technology is often unable to effectively separate useful vibration information from noise.

[0067] (2) The present invention takes into account the impact of environmental factors on UWB signal propagation, constructs an attenuation model and compensation strategy, and effectively addresses problems such as multipath effects and signal attenuation. This enables the present invention to maintain high measurement accuracy under different environmental conditions (such as changes in vegetation density and humidity), greatly improving the applicability and robustness of the present invention.

[0068] (3) The present invention predicts the expected vibration mode of the crown branches and leaves by constructing a spring-damper model and uses a filtering model to separate the crown vibration signal from the noise signal. The present invention can effectively extract useful vibration information from the complex background noise. This processing method greatly improves the quality of the vibration signal.

[0069] (4) The present invention proposes a pecking intensity selection model to adjust the working parameters of the woodpecker to achieve the optimal pecking frequency and force amplitude; this not only maximizes the crown vibration signal intensity detected by the millimeter-wave radar, but also minimizes the influence of external interference factors, ensuring the accuracy of the measurement results;

[0070] (5) The present invention simplifies the vibration of tree crown branches and leaves into a spring-damping model, and combines the selection and attenuation model of the optimal UWB signal frequency band to accurately configure the UWB foot ring and base station. At the same time, the pecking intensity selection model is used to optimize the working parameters of the woodpecker, thereby achieving high-precision measurement of tree height. This method not only effectively overcomes the problems of severe attenuation and multipath effect of UWB signals in the vegetation layer, but also accurately separates useful vibration signals from complex background noise by constructing a filtering model, greatly improving the quality of vibration signals. In addition, the present invention considers the impact of environmental factors on signal propagation and constructs a compensation strategy, so that the system can maintain high-precision measurement under different environmental conditions (such as vegetation density, humidity changes, etc.), significantly improving the applicability and robustness of the system. In summary, the present invention provides an efficient, accurate and adaptable tree height measurement solution that can not only maximize the vibration signal intensity detected by the radar, but also minimize external interference, ensuring the accuracy of the measurement results. It is suitable for multiple fields such as forest resource management and ecological environment monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 This is a flow chart of a tree height measurement method based on woodpecker bionic vibration marking and millimeter wave radar;

[0072] Figure 2 Schematic diagram of communication between UWB tags and UWB antennas in UWB base stations. DETAILED DESCRIPTION

[0073] The following are specific embodiments of the present invention and the accompanying drawings to further describe the technical solutions of the present invention, but the present invention is not limited to these embodiments.

[0074] Example 1

[0075] In order to overcome the problems of severe attenuation and multipath effects of UWB signals in the vegetation layer, and to accurately separate useful vibration signals from complex background noise, the present invention, based on previous research on the use of ultra-wideband (UWB) penetration technology for tree positioning, is inspired by the "high-frequency knocking" behavior of woodpeckers and the detection of small movements (such as breathing and heartbeats) by millimeter-wave radar, and proposes an innovative "penetration-woodpecking" tree height detection method. This method aims to deeply explore the mechanism behind it, so as to break through the limitations of complex occlusion environments on measurements, thereby achieving high-precision and high-efficiency detection of tree height. By combining the woodpecker's bionic vibration markers with advanced millimeter-wave radar technology, the present invention is committed to developing a new way to accurately measure tree height in complex environments such as dense vegetation. This method not only improves the application scope and accuracy of traditional UWB technology, but also provides strong technical support for forest resource management and ecological environment monitoring. Based on this, such as Figure 1 As shown, this embodiment proposes a tree height measurement method based on woodpecker bionic vibration markers and millimeter wave radar, which is applied to a tree height detection system. The system includes:

[0076] The ground calibration platform includes: a woodpecker for generating mechanical vibrations on the tree trunk; a UWB foot ring for calibrating the position of the tree bottom;

[0077] The aerial detection platform includes: a radar for capturing vibration signals caused by the woodpecker on the trees being tested; a UWB base station for communicating with the UWB foot ring;

[0078] In this embodiment, the aerial detection platform is a drone, which is equipped with a radar, a UWB base station, a wind speed sensor (for obtaining wind speed sensing data), a binocular obstacle avoidance camera (for ensuring flight safety: the field of view angle is 120° and the obstacle avoidance response time is <50ms), and an RGB camera (for measuring the leaf area index).

[0079] The present invention adopts an air-ground collaborative working mode (combining a ground calibration platform with an overhead detection platform) that not only overcomes the limitations of a single data source, but also significantly improves the accuracy and coverage of the data. By integrating the advantages of multiple ground and air sensors (including radar and UWB foot rings), this mode can provide more comprehensive and accurate measurement results and adapt to complex and changing natural environments. Its efficiency and reliability enable researchers and practitioners to obtain higher-quality data support in multiple application scenarios such as forest resource management and ecological environment monitoring, promoting the continuous development of related technologies.

[0080] The tree height measurement method comprises the steps of:

[0081] The optimal UWB signal frequency band is obtained by conducting penetration tests at different UWB signal frequency bands; an attenuation model is constructed based on environmental factors and the UWB signal attenuation coefficient; and a compensation strategy is developed to compensate for UWB signal attenuation and time delay caused by multipath effects.

[0082] The environmental factors include: vertical thickness of the canopy and leaf area index;

[0083] The formula of the attenuation model is:

[0084] L toatl =L FS +L canopy +L multipath ;in:

[0085]

[0086] Where, L total Indicates the total loss; L FS represents the free space path loss; L canopy represents the canopy penetration loss; L multipath represents multipath attenuation; p1 and p2 are path loss coefficients; f represents signal frequency; d represents propagation distance; c represents the speed of light; d canopy represents the vertical thickness of the canopy through which the signal passes; LAI represents the leaf area index; MC represents the ambient humidity; k1, k2, and k3 represent the canopy penetration coefficient; η represents the ambient reflection coefficient; h branch Indicates the vertical distance from the bottom of the canopy to the ground.

[0087] In this embodiment, the path loss coefficient is determined by regression of field experimental data:

[0088] For example, an experiment was conducted in an open area, measuring the received power of a UWB signal at different distances (e.g., 10m, 20m, 50m, and 100m), with the transmit power held constant. By inputting this data into a regression analysis tool, the path loss coefficient most suitable for that environment can be obtained.

[0089] The method for constructing the compensation strategy is specifically as follows:

[0090] Fit a multivariable nonlinear equation to predict signal loss:

[0091] Where, k1, k2, k3, k4, k5, and k6 are canopy penetration coefficients; L toatl Indicates the total loss;

[0092] The goodness of fit of the multivariate nonlinear equation is tested by an evaluation formula; the evaluation formula is:

[0093] Where, L m Indicates the measured value, that is, the actual observed signal loss, L p Represents the predicted value, i.e., the signal loss calculated by the multivariable nonlinear equation, Represents the average value of the measured values ​​obtained by multiple measurements; R 2 It represents the coefficient of determination, which is a number between 0 and 1. The closer it is to 1, the better the model fit is; the closer it is to 0, the worse the model fit is.

[0094] Adjusting the canopy penetration coefficient of the multivariable nonlinear equation based on the value of the determination coefficient to obtain the target multivariable nonlinear equation;

[0095] A compensation strategy is constructed based on the target multivariable nonlinear equation. The construction formula of the compensation strategy is:

[0096] L compensted =L total -aexp(-h branch );

[0097] Where a represents the compensation amplitude, L compensted Indicates the total loss after compensation.

[0098] It should be noted that L in the attenuation model toat1 and L in multivariable nonlinear equations toat1 Means the same thing, except that L in the attenuation model toat1 It is the result obtained based on empirical formula or simplified model; while L in multivariable nonlinear equation toat1 It is a more detailed mathematical model that estimates signal attenuation through specific environmental parameters, thus providing higher accuracy and flexibility.

[0099] In complex environments (such as forests), UWB signals experience additional attenuation during propagation due to multipath effects caused by factors such as tree canopies and terrain. Multipath effects can cause a time delay in the signal reaching the receiver, thereby affecting the positioning accuracy based on time difference (such as TDOA, Time Difference of Arrival). Compensation strategies use algorithm adjustments to reduce the error caused by this time delay, ensuring a more accurate calculated distance. In other words, the core of the compensation strategy is to accurately quantify and correct the UWB signal propagation loss and time delay affected by multipath interference to improve the accuracy and reliability of the tree height detection system. This ensures that accurate tree height information can be obtained even in complex obscured environments.

[0100] The present invention takes into account the impact of environmental factors on UWB signal propagation, constructs an attenuation model and compensation strategy, and effectively addresses problems such as multipath effects and signal attenuation. This enables the present invention to maintain high measurement accuracy under different environmental conditions (such as changes in vegetation density, humidity, etc.), greatly improving the applicability and robustness of the present invention.

[0101] In this embodiment, the canopy penetration coefficient (these parameters are obtained by fitting the field experimental data using the least squares method or machine learning method):

[0102] k1: represents the coefficient related to canopy thickness. It reflects the degree of influence of canopy thickness on UWB signal attenuation;

[0103] k2: represents the square root of leaf area index (LAI) and frequency The coefficient of the product correlation. This represents the effect of vegetation density and its frequency-dependent effect on signal attenuation.

[0104] k3: Represents the coefficient related to humidity (MC). Humidity affects the dielectric properties of the medium, thereby changing the propagation characteristics of the signal.

[0105] k4: indicates that branch The coefficient related to the product of the frequency-related terms. This term takes into account the impact of low-branch height on multipath effects.

[0106] k5 and k6: These two coefficients are used to adjust the base level of the model.

[0107] The vibration of tree crown branches and leaves was simplified into a spring-damper model, and the vibration parameters were determined. A filtering model was constructed to separate the tree crown vibration signal from the noise signal. A pecking intensity selection model was constructed based on the woodpecker's pecking frequency, the maximum displacement detectable by the radar, and the natural frequency of the tree crown. The UWB leg ring and UWB base station were configured using the obtained optimal UWB signal frequency band and attenuation model. The pecking intensity selection model was used to adjust the woodpecker's operating parameters to achieve the optimal pecking frequency and force amplitude.

[0108] It should be noted that the natural frequency of the crown refers to the frequency of the natural vibration of the tree crown when it is subjected to external excitation (such as wind, mechanical vibration, etc.). Specifically, this refers to the free vibration frequency of the tree crown as an elastic system due to the initial disturbance in the absence of continuous external forces. This frequency is determined by the physical properties of the tree itself, including factors such as the mass distribution, stiffness and damping characteristics of the crown. In the present invention, the natural frequency of the crown is used to construct a pecking intensity selection model. By understanding the natural frequency of the crown, the pecking frequency of the woodpecker can be avoided from resonating with the natural frequency of the crown, thereby preventing unnecessary vibration amplification or structural damage.

[0109] In this embodiment, the UWB foot ring and the UWB base station are configured by obtaining the optimal UWB signal frequency band and attenuation model, specifically:

[0110] 1. Determine the specific values ​​based on the various parameters in the attenuation model (such as path loss coefficient, signal frequency, propagation distance, etc.). For example:

[0111] Path loss coefficient: Adjust the path loss coefficient according to actual environmental conditions (such as vegetation density, humidity, etc.).

[0112] Signal frequency: Use the previously selected optimal UWB signal frequency band.

[0113] Propagation distance: Measure or estimate the distance between the UWB tag and the UWB base station.

[0114] 2. Specific configuration of UWB foot ring and UWB base station:

[0115] Set the frequency band: Set the operating frequency band of the UWB footband and UWB base station to the previously selected optimal UWB signal band.

[0116] Adjust power: Based on the total loss calculated by the attenuation model and the total loss after compensation, adjust the transmit power of the UWB foot ring and UWB base station to ensure that the received signal strength reaches the expected value.

[0117] Apply filters: Apply adaptive filters at the receiving end to further reduce noise interference and improve the signal-to-noise ratio (SNR).

[0118] The filter model for separating the crown vibration signal and the noise signal is constructed as follows:

[0119] A mixed noise model is constructed to separate the different types of signal components received by the radar. The model formula is:

[0120] S r (t) = S v (t)+S w (t)+S c (t)+S t (t); where S v (t) is the crown vibration signal, S w (t) is the wind noise, S c (t) is the interference noise reflected by the neighboring tree, S t (t) is Gaussian white noise, S r (t) represents the signal to be processed;

[0121] The weight value of the adaptive filter is updated based on the wind speed sensor data, and the wind noise in the mixed noise model is suppressed based on the updated adaptive filter. The update formula is:

[0122] w(n+1)=w(n)+ue(n)S wr (n)

[0123] e(n)=S w (n)-w T (n)S w (n);

[0124] Where w(n) represents the current weight vector of the adaptive filter, e(n) represents the error signal vector, which represents the difference between the output of the adaptive filter and the actual wind noise signal; n represents the discrete time index; S wr (n) represents wind speed sensor data; u is the step factor; T represents matrix transpose;

[0125] A time-frequency domain joint filtering function is established, through which the crown vibration characteristics of the mixed noise model suppressed by the adaptive filter are enhanced.

[0126] The formula of the pecking intensity selection model is:

[0127]

[0128] Where, f p represents the pecking frequency, f0 represents the crown natural frequency, Z max represents the maximum displacement that can be detected by the radar; k1 and k2 represent the canopy penetration coefficient; F opt Indicates the optimal pecking intensity.

[0129] The pecking intensity selection model is used to adjust the working parameters of the woodpecker to achieve the optimal pecking frequency and force amplitude, specifically:

[0130] Set the acceptable range of pecking frequency to avoid resonance with the natural frequency of the crown, and adjust the pecking frequency within the acceptable range so that the F in the pecking intensity selection model opt Reached maximum value.

[0131] The three-dimensional coordinates of the tree base are determined based on the communication signals between the configured UWB foot ring and the UWB base station, as well as the compensation strategy. The woodpecker, after adjusting its parameters, pecks the tree trunk and uses a spring-damper model to predict the expected vibration pattern of the crown branches and leaves under the current pecking. The processed signal related to the crown vibration is obtained from the vibration signal captured by the radar. The noise signal in the processed signal is separated using a filtering model to obtain the crown vibration signal. The crown vibration signal is then used to mark the characteristic areas of the crown.

[0132] This invention uses a filtering model to separate crown vibration signals from noise signals, effectively extracting useful vibration information from complex background noise. This processing method significantly improves the quality of the vibration signal. Furthermore, the proposed pecking intensity selection model adjusts the woodpecker's operating parameters to achieve the optimal pecking frequency and force amplitude. This not only maximizes the crown vibration signal strength detected by the millimeter-wave radar, but also minimizes the influence of external interference factors, ensuring the accuracy of the measurement results.

[0133] The three-dimensional coordinates of the tree bottom are determined based on the communication signals between the configured UWB foot ring and the UWB base station and the compensation strategy, specifically:

[0134] The communication signal is compensated by the compensation strategy, and the communication parameters are calculated based on the compensated communication signal: the straight-line distance between the UWB tag in the UWB foot ring and any UWB antenna in the UWB base station, and the azimuth and elevation angles between the UWB tag and each UWB antenna;

[0135] In this embodiment, the compensated total loss is applied to the original communication signal to correct errors caused by multipath effects and signal attenuation. This step ensures the accuracy and reliability of subsequent calculations.

[0136] Figure 2 The figure shows the communication relationship between the UWB tag and each UWB antenna in the UWB base station (UWB antenna 1, UWB antenna 2, UWB antenna 3, and UWB antenna 4).

[0137] The small square represents a pulse signal. The UWB tag sends a pulse signal at time T1. The pulse signal sent by the UWB tag at time T1 is received by UWB antenna 1 at time T2. The pulse signal is reflected back to the UWB tag at time T3. The UWB tag receives the reflected signal at time T4, and the reflected signal is sent back to UWB antenna 1 at time T5.

[0138] The pulse signal sent by the UWB tag at time T1 is received by UWB antenna 2 at time T6 after multiple round-trip transmissions. The pulse signal received by UWB antenna 2 is sent to UWB antenna 3, and then the pulse signal received by UWB antenna 3 is sent to UWB antenna 4.

[0139] Figure 2 The communication process of the pulse signal (for the sake of convenience of explanation, this embodiment sets it as the first pulse signal) is shown, where: rd1 represents the time difference between T1 and T4, that is, the time difference between the first emission time of the pulse signal and the reception time of the reflected signal corresponding to the first reflection of the signal; t rp1represents the time difference between T4 and T5, that is, the time difference between the reception time of the first reflected signal and the transmission time of the reflected signal again; t pp Indicates the one-way time difference from transmission to reception ( Figure 2 Each t in pp t k1 represents the time difference between the time T6 when UWB antenna 1 sends a pulse signal to UWB antenna 2 and the time when UWB antenna 2 receives the pulse signal; t k2 represents the time difference between the time when UWB antenna 2 sends a pulse signal to UWB antenna 3 and the time when UWB antenna 3 receives the pulse signal; t k3 It represents the time difference between the time when the UWB antenna 3 sends a pulse signal to the UWB antenna 4 and the time when the UWB antenna 4 receives the pulse signal.

[0140] The communication parameters are calculated by the communication signal, specifically:

[0141] 1. Calculate the straight-line distance between the UWB tag in the UWB foot ring and any UWB antenna in the UWB base station. The calculation formula is:

[0142]

[0143] In this embodiment, t rd1 With t rp1 is the time difference corresponding to the first pulse signal sent by the UWB tag. Similarly, t rd2 With t rp2 is the time difference corresponding to the second pulse signal newly sent by the UWB tag (for detailed explanation, see t rd1 With t rp1 ).

[0144] 2. Construct the phase difference calculation formula between the UWB tag and each UWB antenna:

[0145]

[0146] Where z represents the spacing between UWB antennas; rad is the time-phase function; λ represents the wavelength;

[0147] The θ pitch angle is the vertical angle from the horizontal plane to the target direction, that is, the angle between the line connecting the UWB tag and the specific UWB antenna and the horizontal plane. For each UWB antenna, this angle reflects the vertical position of the UWB tag.

[0148] The φ azimuth is the horizontal angle measured clockwise from a reference direction (usually due north) to the target direction. This angle is the angle between the horizontal projection of the line connecting the UWB tag and a specific UWB antenna and the reference direction. This angle reflects the horizontal position of the UWB tag.

[0149] 3. Construct the calculation formula for the horizontal direction (azimuth):

[0150]

[0151] 4. Construct the calculation formula for the vertical direction (pitch angle):

[0152]

[0153] Where:

[0154] Horizontal spacing d x : Refers to the distance between two adjacent UWB antennas in the horizontal direction. For example, in a two-dimensional antenna array, if the antennas are arranged in the horizontal direction, then d x is the horizontal spacing between these antennas; d x Used to calculate the phase difference caused by horizontal spacing.

[0155] Vertical spacing d y : Refers to the distance between two adjacent UWB antennas in the vertical direction. Similarly, in a two-dimensional antenna array, if the antennas are arranged in the vertical direction, then d y is the vertical spacing between these antennas; d y Used to calculate the phase difference due to vertical spacing.

[0156] 5. Combine the phase difference calculation formula, the horizontal direction (azimuth angle) calculation formula, and the vertical direction (elevation angle) calculation formula to solve the elevation angle θ and azimuth angle φ between the UWB tag and each UWB antenna.

[0157] According to the calculated communication parameters and the coordinates of the detection platform above (x u ,y u ,z u ) Calculate the three-dimensional coordinates of the tree bottom (x b ,y b ,z b ); The calculation formula for the three-dimensional coordinates of the tree bottom is:

[0158]

[0159] Where θ represents the elevation angle of any UWB antenna, and φ represents the azimuth angle of the UWB antenna corresponding to θ; D isrepresents the straight-line distance between the UWB tag and the UWB antenna corresponding to θ.

[0160] The spring-damper model is used to predict the expected vibration mode of the crown branches and leaves under the current pecking, and the signal to be processed related to the crown vibration in the vibration signal captured by the radar is obtained, specifically:

[0161] The vibration displacement z(t) of the crown branches and leaves is predicted by the correlation formula between the Doppler frequency shift and vibration velocity measured by radar and the spring-damping model; the formula of the spring-damping model is: az"+bz'+cz=F0sin(2πf p t); the relevant relationship is:

[0162] Where F0 represents the amplitude of the pecking force; f p represents the pecking frequency; t represents the pecking time point; a, b, and c represent the inversion parameters, where a represents the inertia parameter of the spring-damper model, b represents the resistance motion parameter, and c represents the spring restoring force strength parameter; z′=f d , represents the vibration velocity; z″ represents the vibration acceleration, and z represents the vibration displacement of the crown branches and leaves;

[0163] According to the vibration displacement z(t), a formula for obtaining the phase change caused by the micro-deformation due to vibration is constructed. The expression of the formula is: Where z(t) = Δz; ω represents the radar wave incident angle, λ represents the radar wavelength, and Δξ represents the phase change caused by micro-deformation.

[0164] Based on the phase change acquisition formula, the predicted vibration displacement z(t) is mapped to the phase change of the radar echo signal to obtain the signal to be processed related to the crown vibration; the mapping formula is:

[0165] Where,

[0166] Δξ(t) represents the radar phase change caused by the vibration displacement of the crown branches and leaves from time 0 to time t; 4π represents the constant term, which is used to convert the displacement change into the phase change; z(o) represents the vibration displacement at time point o; cos(ω) represents the cosine value of the radar wave incident angle ω; do is the differential symbol, which represents a small increment to time point o.

[0167] The three-dimensional coordinates of the tree top are calculated by marking the characteristic area of ​​the tree crown, and the tree height is obtained based on the attenuation model, the three-dimensional coordinates of the tree top and the three-dimensional coordinates of the tree base.

[0168] The present invention simplifies the vibration of tree crown branches and leaves into a spring-damping model; configures the UWB foot ring and UWB base station through the obtained optimal UWB signal frequency band and attenuation model; adjusts the working parameters of the woodpecker through the pecking intensity selection model to achieve the optimal pecking frequency and force amplitude; determines the three-dimensional coordinates of the tree bottom based on the communication signal between the configured UWB foot ring and the UWB base station and the compensation strategy; uses the woodpecker with adjusted parameters to peck the tree trunk, and uses the spring-damping model to predict the expected vibration mode of the tree crown branches and leaves under the current pecking, and obtains the to-be-processed signal related to the tree crown vibration in the vibration signal captured by the radar; and separates the noise signal in the to-be-processed signal through the filtering model to obtain the tree crown vibration. signal; mark the crown feature area through the crown vibration signal; calculate the three-dimensional coordinates of the tree top through the marked crown feature area, and obtain the tree height based on the attenuation model, the three-dimensional coordinates of the tree top and the three-dimensional coordinates of the tree bottom; it not only improves the accuracy of tree height measurement, but also can adapt to the measurement needs under different environmental conditions, uses the mechanical vibration generated by the woodpecker to induce tree vibration, and uses millimeter wave radar to capture these vibration signals, so as to accurately calculate the height of the tree; it overcomes the problem that UWB signals will suffer severe attenuation and multipath effects when passing through the vegetation layer, resulting in reduced signal quality, and the problem that existing vibration signal processing technology is often unable to effectively separate useful vibration information from noise.

[0169] The three-dimensional coordinates of the treetop are calculated by marking the crown feature area, specifically:

[0170] The quadratic surface fitting of the marked crown characteristic area is performed to obtain multiple equation coefficients;

[0171] The quadratic surface equation is constructed by the equation coefficients, and the three-dimensional coordinates of the tree top are calculated by the quadratic surface equation: (x t ,y t , z t );

[0172] The formula expression of the quadratic surface equation is:

[0173] z t =ax t 2 +by t 2 +cxty t +dx t +ey t +f; where:

[0174]

[0175] Where a, b, c, d, e, and f represent the coefficients of the equation.

[0176] The tree height is obtained according to the attenuation model, the three-dimensional coordinates of the tree top and the three-dimensional coordinates of the tree bottom, specifically:

[0177] The initial value of the tree height H is calculated by the three-dimensional coordinates of the tree bottom and the three-dimensional coordinates of the tree top. The calculation formula is: H = zt-z b ;

[0178] Select the optimal signal frequency f through the attenuation model UWB ;

[0179] Based on the optimal signal frequency f UWB Calibrate the initial value H of the tree height to get the tree height; the calibration formula is:

[0180]

[0181] Where, L c represents the canopy attenuation compensation coefficient, H J Indicates the calibrated tree height.

[0182] The present invention simplifies the vibration of tree crown branches and leaves into a spring-damping model, and combines the selection and attenuation model of the optimal UWB signal frequency band to accurately configure the UWB foot ring and base station, and uses the pecking intensity selection model to optimize the working parameters of the woodpecker, thereby achieving high-precision measurement of tree height; this method not only effectively overcomes the problems of severe attenuation and multipath effects of UWB signals in the vegetation layer, but also accurately separates useful vibration signals from complex background noise by constructing a filtering model, greatly improving the quality of vibration signals; in addition, the present invention takes into account the impact of environmental factors on signal propagation and constructs a compensation strategy, so that the system can maintain high-precision measurement under different environmental conditions (such as vegetation density, humidity changes, etc.), significantly improving the applicability and robustness of the system. In summary, the present invention provides an efficient, accurate and adaptable tree height measurement solution that can not only maximize the intensity of the vibration signal detected by the radar, but also minimize external interference to ensure the accuracy of the measurement results. It is suitable for multiple fields such as forest resource management and ecological environment monitoring.

[0183] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0184] In addition, in the present invention, descriptions such as "first," "second," and "one" are for descriptive purposes only and should not be understood to indicate or imply their relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include at least one of such features. In the description of the present invention, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0185] In the present invention, unless otherwise specified or limited, the terms "connection" and "fixation" should be understood in a broad sense. For example, "fixation" can mean fixed connection, detachable connection, or integration; mechanical connection or electrical connection; direct connection or indirect connection through an intermediate medium; internal communication between two elements or interaction between two elements, unless otherwise specified. Those skilled in the art will be able to understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0186] In addition, the technical solutions between the various embodiments of the present invention can be combined with each other, but it must be based on the fact that ordinary technicians in this field can implement it. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

Claims

1. A tree height measurement method based on woodpecker bionic vibration markers and millimeter wave radar, characterized in that: Applied to tree height detection system, the system includes: The ground calibration platform includes: a woodpecker for generating mechanical vibrations on the tree trunk; a UWB foot ring for calibrating the position of the tree bottom; The aerial detection platform includes: a radar for capturing vibration signals caused by the woodpecker on the trees being tested; a UWB base station for communicating with the UWB foot ring; The tree height measurement method comprises the steps of: The optimal UWB signal frequency band is obtained by conducting penetration tests at different UWB signal frequency bands; an attenuation model is constructed based on environmental factors and the UWB signal attenuation coefficient; and a compensation strategy is developed to compensate for UWB signal attenuation and time delay caused by multipath effects. The vibration of tree crown branches and leaves was simplified into a spring-damper model, and the vibration parameters were determined. A filtering model was constructed to separate the tree crown vibration signal from the noise signal. A pecking intensity selection model was constructed based on the woodpecker's pecking frequency, the maximum displacement detectable by the radar, and the natural frequency of the tree crown. The UWB leg ring and UWB base station were configured using the obtained optimal UWB signal frequency band and attenuation model. The pecking intensity selection model was used to adjust the woodpecker's operating parameters to achieve the optimal pecking frequency and force amplitude. The three-dimensional coordinates of the tree base are determined based on the communication signals between the configured UWB foot ring and the UWB base station, as well as the compensation strategy. The woodpecker, after adjusting its parameters, pecks the tree trunk and uses a spring-damper model to predict the expected vibration pattern of the crown branches and leaves under the current pecking. The processed signal related to the crown vibration is obtained from the vibration signal captured by the radar. The noise signal in the processed signal is separated using a filtering model to obtain the crown vibration signal. The crown vibration signal is then used to mark the characteristic areas of the crown. The three-dimensional coordinates of the tree top are calculated by marking the characteristic area of ​​the tree crown, and the tree height is obtained based on the attenuation model, the three-dimensional coordinates of the tree top and the three-dimensional coordinates of the tree base.

2. The tree height measurement method based on woodpecker bionic vibration marker and millimeter wave radar according to claim 1 is characterized in that: The environmental factors include: vertical thickness of the canopy and leaf area index; The formula of the attenuation model is: L toatl =L FS +L canopy +L multipath ; in: Where, L toatl Indicates the total loss; L FS represents the free space path loss; L canopy represents the canopy penetration loss; L multipath represents multipath attenuation; p1 and p2 are path loss coefficients; f represents signal frequency; d represents propagation distance; c represents the speed of light; d canopy represents the vertical thickness of the canopy through which the signal passes; LAI represents the leaf area index; MC represents the ambient humidity; k1, k2, and k3 represent the canopy penetration coefficient; η represents the ambient reflection coefficient; h branch Indicates the vertical distance from the bottom of the canopy to the ground.

3. The tree height measurement method based on woodpecker bionic vibration marker and millimeter wave radar according to claim 2 is characterized in that: The method for constructing the compensation strategy is specifically as follows: Fit a multivariable nonlinear equation to predict signal loss: Where, k1, k2, k3, k4, k5, and k6 are canopy penetration coefficients; L toatl Indicates the total loss; The goodness of fit of the multivariate nonlinear equation is tested by an evaluation formula; the evaluation formula is: Where, L m Indicates the measured value, that is, the actual observed signal loss, L p Represents the predicted value, i.e., the signal loss calculated by the multivariable nonlinear equation, Represents the average value of the measured values ​​obtained by multiple measurements; R 2 represents the coefficient of determination; Adjusting the canopy penetration coefficient of the multivariable nonlinear equation based on the value of the determination coefficient to obtain the target multivariable nonlinear equation; A compensation strategy is constructed based on the target multivariable nonlinear equation. The construction formula of the compensation strategy is: L compensted =L total -aexp(-h branch ); Where a represents the compensation amplitude, L compensted Indicates the total loss after compensation.

4. The tree height measurement method based on woodpecker bionic vibration marker and millimeter wave radar according to claim 3 is characterized in that: The three-dimensional coordinates of the tree bottom are determined based on the communication signals between the configured UWB foot ring and the UWB base station and the compensation strategy, specifically: The communication signal is compensated by the compensation strategy, and the communication parameters are calculated based on the compensated communication signal: the straight-line distance between the UWB tag in the UWB foot ring and any UWB antenna in the UWB base station, and the azimuth and elevation angles between the UWB tag and each UWB antenna; According to the calculated communication parameters and the coordinates of the detection platform above (x u ,y u ,z u ) Calculate the three-dimensional coordinates of the tree bottom (x b ,y b ,z b ); The calculation formula for the three-dimensional coordinates of the tree bottom is: Where θ represents the elevation angle of any UWB antenna, and φ represents the azimuth angle of the UWB antenna corresponding to θ; D is represents the straight-line distance between the UWB tag and the UWB antenna corresponding to θ.

5. The tree height measurement method based on woodpecker bionic vibration marker and millimeter wave radar according to claim 4 is characterized in that: The spring-damper model is used to predict the expected vibration mode of the crown branches and leaves under the current pecking, and the signal to be processed related to the crown vibration in the vibration signal captured by the radar is obtained, specifically: The vibration displacement z(t) of the crown branches and leaves is predicted by the correlation formula between the Doppler frequency shift and vibration velocity measured by radar and the spring-damping model; the formula of the spring-damping model is: az"+bz'+cz=F0sin(2πf p t); the relevant relationship is: Where F0 represents the amplitude of the pecking force; f p represents the pecking frequency; t represents the pecking time point; a, b, and c represent the inversion parameters, where a represents the inertia parameter of the spring-damper model, b represents the resistance motion parameter, and c represents the spring restoring force strength parameter; z′=f d , represents the vibration velocity; z″ represents the vibration acceleration, and z represents the vibration displacement of the crown branches and leaves; According to the vibration displacement z(t), a formula for obtaining the phase change caused by the micro-deformation due to vibration is constructed. The expression of the formula is: Where z(t) = Δz; ω represents the radar wave incident angle, λ represents the radar wavelength, and Δξ represents the phase change caused by micro-deformation. Based on the phase change acquisition formula, the predicted vibration displacement z(t) is mapped to the phase change of the radar echo signal to obtain the signal to be processed related to the crown vibration; the mapping formula is: Where, Δξ(t) represents the radar phase change caused by the vibration displacement of the crown branches and leaves from time 0 to time t; 4π represents the constant term, which is used to convert the displacement change into the phase change; z(o) represents the vibration displacement at time point o; cos(ω) represents the cosine value of the radar wave incident angle ω; do is the differential symbol, which represents a small increment to time point o.

6. The tree height measurement method based on woodpecker bionic vibration marker and millimeter wave radar according to claim 5 is characterized in that: The filter model for separating the crown vibration signal and the noise signal is constructed as follows: A mixed noise model is constructed to separate the different types of signal components received by the radar. The model formula is: S r (t) = S v (t)+S w (t)+S c (t)+S t (t); where S v (t) is the crown vibration signal, S w (t) is the wind noise, S c (t) is the interference noise reflected by the neighboring tree, S t (t) is Gaussian white noise, S r (t) represents the signal to be processed; The weight value of the adaptive filter is updated based on the wind speed sensor data, and the wind noise in the mixed noise model is suppressed based on the updated adaptive filter. The update formula is: Where w(n) represents the current weight vector of the adaptive filter, e(n) represents the error signal vector, which represents the difference between the output of the adaptive filter and the actual wind noise signal; n represents the discrete time index; S wr (n) represents wind speed sensor data; u is the step factor; T represents matrix transpose; A time-frequency domain joint filtering function is established, through which the crown vibration characteristics of the mixed noise model suppressed by the adaptive filter are enhanced.

7. The tree height measurement method based on woodpecker bionic vibration marker and millimeter wave radar according to claim 6 is characterized in that: The formula of the pecking intensity selection model is: Where, f p represents the pecking frequency, f0 represents the crown natural frequency, Z max represents the maximum displacement that can be detected by the radar; k1 and k2 represent the canopy penetration coefficient; F opt Indicates the optimal pecking intensity.

8. The tree height measurement method based on woodpecker bionic vibration marker and millimeter wave radar according to claim 7 is characterized in that: The pecking intensity selection model is used to adjust the working parameters of the woodpecker to achieve the optimal pecking frequency and force amplitude, specifically: Set the acceptable range of pecking frequency to avoid resonance with the natural frequency of the crown, and adjust the pecking frequency within the acceptable range so that the F in the pecking intensity selection model opt Reached maximum value.

9. The tree height measurement method based on woodpecker bionic vibration marker and millimeter wave radar according to claim 8, characterized in that: The three-dimensional coordinates of the treetop are calculated by marking the crown feature area, specifically: The quadratic surface fitting of the marked crown characteristic area is performed to obtain multiple equation coefficients; The quadratic surface equation is constructed by the equation coefficients, and the three-dimensional coordinates of the tree top are calculated by the quadratic surface equation: (x t ,y t , z t ); The formula expression of the quadratic surface equation is: z t =ax t 2 +by t 2 +cxty t +dx t +ey t +f; where: Where a, b, c, d, e, and f represent the coefficients of the equation.

10. The tree height measurement method based on woodpecker bionic vibration marker and millimeter wave radar according to claim 9, characterized in that: The tree height is obtained according to the attenuation model, the three-dimensional coordinates of the tree top and the three-dimensional coordinates of the tree bottom, specifically: The initial value of the tree height H is calculated by the three-dimensional coordinates of the tree bottom and the three-dimensional coordinates of the tree top. The calculation formula is: H = z t -z b ; Select the optimal signal frequency f through the attenuation model UWB ; Based on the optimal signal frequency f UWB Calibrate the initial value H of the tree height to get the tree height; the calibration formula is: Where Lc represents the canopy attenuation compensation coefficient, H J Indicates the calibrated tree height.

Images