Rotating object parameter estimation and stability analysis method based on vortex electromagnetic waves

Abstract

The invention discloses a rotating object parameter estimation and stability analysis method based on vortex electromagnetic waves, and the method comprises the steps: taking a rotating object as an ideal scattering point, and building an electric field intensity expression of the scattering point; performing frequency mixing on the echo signal to obtain a baseband signal containing a radial velocity and an angular velocity; establishing a double-domain dictionary composed of a radial speed dictionary and an angular speed dictionary, and preliminarily estimating the radial speed and the angular speed by matching the double-domain dictionary with the baseband signal; constructing a correlation function based on the preliminary estimation result, and designing dynamic step iterative optimization until convergence to obtain high-precision final parameter estimation; and constructing a regularization objective function by using the obtained final parameter estimation, and quantifying the stability of the motion of the rotating object through iterative optimization and calculation of an entropy value of scattering coefficient probability distribution. The method has high parameter estimation precision and robustness under the condition that the signal-to-noise ratio exists.

Description

Technical Field

[0001] The present invention belongs to the technical field of machine learning, and in particular relates to a method for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves. Background Art

[0002] As an emerging economic model, the low-altitude economy offers broad application prospects in a variety of fields, including urban transportation, emergency rescue, and logistics. Helicopters, with their advantages of vertical takeoff and landing and maneuverability, play an irreplaceable role in medical rescue, emergency relief, and outdoor search and rescue. Safe and efficient takeoff, landing, and hovering operations in complex environments are key prerequisites for the safe operation of the low-altitude economy. Especially in complex urban environments, the stability of helicopter takeoffs and landings directly impacts rescue and emergency response missions. Therefore, accurately sensing and estimating the motion parameters of rotating flight targets, such as helicopters, and assessing their stability during takeoff and landing are crucial for ensuring operational safety.

[0003] Vortex electromagnetic waves are a special type of electromagnetic wave that carries orbital angular momentum. Their wavefront has a spiral structure and can produce a spatial phase modulation effect on the target. In recent years, the use of vortex electromagnetic waves to detect rotating objects has gradually attracted attention, especially in the microwave frequency band, and initial progress has been made in theoretical modeling and verification. However, in some application scenarios, rotating objects are often accompanied by complex motions, such as axial rotation and radial motion. In this case, the coupling effect of axial rotation and radial motion is significantly aggravated, making the decoupling ability of traditional estimation methods insufficient and plagued by high-precision requirements. In addition, existing research has not yet analyzed the stability of the target motion. Therefore, how to fully utilize the physical properties of vortex electromagnetic waves to achieve synchronous and high-precision estimation of the motion parameters of rotating objects under complex motion conditions and further quantitatively evaluate their motion stability is of great research significance. Summary of the Invention

[0004] The main purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art and provide a method for parameter estimation and stability analysis of rotating objects based on vortex electromagnetic waves. First, a uniform circular array antenna is used to generate vortex electromagnetic waves, and the rotating object is regarded as an ideal scattering point, and an expression for the electric field intensity of the scattering point is established. Secondly, the echo signal is mixed to obtain a baseband signal containing radial velocity and angular velocity. Then, by constructing a dual-domain dictionary model and designing dynamic step size optimization, the effective separation and accurate estimation of the motion parameters of the rotating object under complex motion conditions are achieved. Finally, by iteratively optimizing the regularized objective function, the scattering coefficient is obtained and the entropy value of the probability distribution of the scattering coefficient is calculated to achieve the stability analysis of its motion.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves, comprising the following steps: Using a uniform circular array antenna to generate vortex electromagnetic waves, the rotating object is regarded as an ideal scattering point, and the electric field intensity expression of the scattering point is established; Mixing the echo signal to obtain a baseband signal containing radial velocity and angular velocity; A dual-domain dictionary consisting of a radial velocity dictionary and an angular velocity dictionary is established, and the radial velocity and angular velocity are preliminarily estimated by matching the dual-domain dictionary with the baseband signal; Based on the preliminary estimation results, a correlation function is constructed, and a dynamic step size is designed for iterative optimization until convergence, resulting in a high-precision final parameter estimate. The obtained final parameter estimation is used to construct a regularized objective function, and the stability of the rotating object's motion is quantified by iterative optimization and calculation of the entropy value of the scattering coefficient probability distribution. The lower the entropy value, the higher the motion stability.

[0006] As a preferred technical solution, the electric field strength expression is specifically: ; in, E s represents the electric field strength, B Indicates the number of antenna units, represents an imaginary number, j represents the imaginary part of a complex number, k represents the wave number, l represents the mode of vortex electromagnetic wave, f 0 indicates the carrier frequency, t is the variable that represents the time-varying electric field, θ and φ denote the elevation angle and azimuth angle respectively, α represents the radius of the antenna, J l ( kα sin θ ) is the first category l Bessel function of order.

[0007] As a preferred technical solution, the baseband signal expression is: ; in, E r represents the baseband signal, represents the scattering coefficient, j represents the imaginary part of a complex number, v and Ω represent radial velocity and angular velocity respectively, λ represents the wavelength, l represents the mode of vortex electromagnetic wave,t represents the time-varying variable of the baseband signal, n ( t ) represents additive white Gaussian noise.

[0008] As a preferred technical solution, the dual-domain dictionary is defined as: ; in D Represents a dual-domain dictionary, Indicates that the dimension is 1× NM Matrix of represents the dictionary candidate set composed of radial velocities, f D ( v N )=2 v N / λ , v represents the radial velocity, λ represents the wavelength, t 1, ..., t N represents the discrete representation of the radial velocity dictionary candidate set, Indicates that the dimension is 1× N Matrix of Represents the dictionary candidate set composed of angular velocity, l represents the mode of the vortex electromagnetic wave, Ω represents the angular velocity, t 1, ..., t M represents the discrete representation of the candidate set of angular velocity dictionary, Indicates that the dimension is 1× M Matrix of j represents the imaginary part of a complex number, Represents a tensor product.

[0009] As a preferred technical solution, the matching is: ; in, Z NM Indicates the matching degree between the dual-domain dictionary and the baseband signal, U NM represents the weighting factor, E r represents the baseband signal, D Represents a dual-domain dictionary, N and M Indicates the dimensions of different dictionaries, v represents radial velocity, and Ω represents angular velocity.

[0010] As a preferred technical solution, the correlation function and dynamic step size are: ; ; ; ; in, F ( v , Ω) represents the correlation function, E r represents the baseband signal, E r(0) represents the baseband signal after preliminary estimation of parameters, v s Indicates the s The radial velocity of the iteration, v s+1 Indicates the s+ Radial velocity at 1 iteration, μ s Indicates the s The step size of the iteration, μ s+1 Indicates the s+ The step size of 1 iteration, Denotes the correlation function of radial velocity variables v The differential of Ω s Indicates the s The angular velocity of the iteration, Ω s+1 Indicates the s+ Angular velocity at 1 iteration, represents the differential of the correlation function with respect to the angular velocity variable Ω, F s Indicates the s The correlation function of the iteration, F s+1 Indicates the s+ The correlation function for 1 iteration, β and δ Is the adjustment factor, the value is between 0 and 1, δ To ensure that the equation does not converge to zero, when | F s+1 - F s |< ε , ε When is the set threshold, we get v and the final parameter estimates of Ω.

[0011] As a preferred technical solution, the final parameter estimate is used to construct a regularized objective function, the scattering coefficient is solved through iterative optimization, and the entropy value of the probability distribution of the scattering coefficient is calculated. The stability of the rotating object motion is quantified based on the entropy value, specifically: Constructing the objective function Q : ; in, D Represents a dual-domain dictionary, A' represents the scattering coefficient, E r represents the baseband signal, L represents the smoothing operator, O 1 and O 2 represents the regularization term, and min represents the scattering coefficient that minimizes the value of the entire expression. A' , represents the square of the Euclidean norm, represents the Manhattan norm; Iterative optimization solves the objective function: ; in, ; ; soft represents the soft threshold function, O 1 and O 2 represents the regularization term, q Represents the adjustment factor, its value should be greater than W The largest eigenvalue of the matrix, O 1 / q represents the threshold value, m Indicates the m iterations, m+ 1 means the m+ 1 iteration, β Is the adjustment factor, the value is between 0 and 1, A' represents the scattering coefficient, △ A' Indicates the m At the iteration, the difference between the current iteration value and the previous iteration value, D Represents a dual-domain dictionary, H represents the matrix transpose, E r represents the baseband signal, L represents the smoothing operator, when the scattering coefficient m+ 1 iteration value and m When the difference between the iteration values ​​is less than the threshold, the iteration is stopped and the scattering coefficient is obtained; Calculate the entropy value based on the scattering coefficient: ; in, is the probability distribution of the scattering coefficient.

[0012] In a second aspect, the present invention provides a rotating object parameter estimation and stability analysis system based on vortex electromagnetic waves, characterized in that it is applied to the rotating object parameter estimation and stability analysis method based on vortex electromagnetic waves, including a mathematical model construction module, an echo baseband signal acquisition module, a dual-domain dictionary construction module, a dynamic step size optimization module and a stability analysis module; The mathematical model building module is used to generate vortex electromagnetic waves using a uniform circular array antenna, regard the rotating object as an ideal scattering point, and establish an expression for the electric field intensity of the scattering point; The echo baseband signal acquisition module is used to mix the echo signal to obtain a baseband signal containing radial velocity and angular velocity; The dual-domain dictionary building module is used to establish a dual-domain dictionary consisting of a radial velocity dictionary and an angular velocity dictionary, and preliminarily estimate the radial velocity and angular velocity by matching the dual-domain dictionary with the baseband signal; The dynamic step size optimization module is used to construct a correlation function based on the preliminary estimation results, and to design a dynamic step size iterative optimization until convergence, thereby obtaining a high-precision final parameter estimate; The stability analysis module is used to construct a regularized objective function using the obtained final parameter estimate, and quantify the stability of the rotating object's motion by iterative optimization and calculating the entropy value of the scattering coefficient probability distribution. The lower the entropy value, the higher the motion stability.

[0013] In a third aspect, the present invention provides an electronic device, comprising: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores computer program instructions that can be executed by the at least one processor. The computer program instructions are executed by the at least one processor to enable the at least one processor to perform the rotating object parameter estimation and stability analysis method based on vortex electromagnetic waves.

[0014] In a fourth aspect, the present invention provides a computer-readable storage medium storing a program, which, when executed by a processor, implements the method for parameter estimation and stability analysis of rotating objects based on vortex electromagnetic waves.

[0015] Compared with the prior art, the present invention has the following advantages and beneficial effects: Traditional parameter estimation methods for the combined motion (rotational + radial) of rotating objects typically require emitting a pair of vortex electromagnetic wave beams with opposite modes to first estimate the radial velocity and then the angular velocity. This requires sequential processing to separate the parameters. This process is not only complex but also susceptible to parameter estimation accuracy in scenarios with high signal-to-noise ratios, making efficient and simultaneous parameter extraction difficult.

[0016] In response to the above problems, the present invention proposes an innovative parameter estimation method for the composite motion of rotating objects. The core steps of this method are to achieve the separation and synchronous estimation of radial velocity and angular velocity by constructing a dual-domain dictionary model and introducing a dynamic step-size optimization mechanism, which significantly improves the efficiency of parameter estimation. This method still has high parameter estimation accuracy and robustness under conditions containing additive Gaussian white noise. In addition, in order to further characterize the dynamic characteristics of the object's motion, the present invention also designs a regularization-based objective function, combined with iterative optimization to accurately estimate the scattering coefficient of the target. On this basis, the entropy value of the scattering coefficient is introduced as a measure of motion stability. By calculating the entropy value, the degree of motion stability of the target over a period of time can be effectively reflected. The smaller the entropy value, the more stable the motion state, thereby providing a reliable basis for long-term monitoring and abnormality identification of the target state.

[0017] In summary, the present invention has obvious advantages in the synchronous estimation of compound motion parameters of rotating objects and quantitative evaluation of stability, breaking through the technical bottleneck of traditional methods and having broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 is a schematic diagram of an application scenario of an embodiment; Figure 2 is a method flow chart of an embodiment; Figure 3 is a two-dimensional color map of simultaneous estimation of radial velocity and angular velocity parameters in an embodiment; Figure 4 is a relative error diagram of parameter estimation under different candidate set conditions of the embodiment dictionary; Figure 5 is a relative error diagram of radial velocity and angular velocity under different signal-to-noise ratio conditions in the embodiment; Figure 6 is the amplitude map reconstructed by the embodiment, i.e., the scattering coefficient map; Figure 7 is the phase diagram reconstructed by the embodiment; Figure 8 1 is a block diagram of a rotating object parameter estimation and stability analysis system based on vortex electromagnetic waves according to an embodiment of the present invention; Figure 9 2 is a structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0021] References to "embodiments" in this application mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0022] The present invention relates to a method for parameter estimation and stability analysis of rotating objects based on vortex electromagnetic waves. This method is based on the Doppler effect generated by the interaction between vortex electromagnetic waves and rotating objects. First, a signal model of the rotating target under the composite motion (rotation + radial) is constructed and mixed processing is performed to obtain its baseband signal. Subsequently, a dual-domain dictionary model is constructed, and dynamic step size optimization and regularization constraints are designed to effectively decouple the composite motion parameters and achieve accurate estimation. At the same time, this method covers the analysis process of target motion stability. Even in the presence of additive Gaussian white noise, this method still maintains high parameter estimation accuracy and robustness, and is suitable for application scenarios such as low-altitude target parameter estimation, state monitoring (especially for rotor-type rotating targets such as helicopters), etc. Figure 1 It has significant engineering application value and promotion potential.

[0023] like Figure 2 As shown, the present invention provides a method for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves, which specifically includes the following steps: S1. Construct a mathematical model: Use a uniform circular array antenna to generate vortex electromagnetic waves, treat the rotating object as an ideal scattering point, and establish the electric field strength of the scattering point. E s expression.

[0024] In this embodiment, the rotating object is the rotor of a helicopter. The rotor is regarded as an ideal scattering point. The electric field intensity generated by the scattering point in space is E s Expressed as: ; (1) in,E s represents the electric field strength, B Indicates the number of antenna units, represents an imaginary number, j represents the imaginary part of a complex number, k represents the wave number, l represents the mode of vortex electromagnetic waves, f 0 indicates the carrier frequency, t is the variable that represents the time-varying electric field, θ and φ denote the elevation angle and azimuth angle respectively, α represents the radius of the antenna, J l ( kα sin θ ) is the first category l Bessel function of order.

[0025] S2. Obtain echo baseband signal: Mix the received echo signal to obtain a baseband signal containing radial velocity and angular velocity E r .

[0026] Furthermore, consider the case of a rotating object performing a complex motion, including the rotation of the helicopter rotor around its axis and the radial motion of the helicopter relative to the antenna array. The rotating object is located above the uniform circular array antenna and generates an echo signal under the irradiation of the vortex electromagnetic wave. The echo signal carries the target's motion parameter information. Assuming that the initial azimuth angle of the vortex electromagnetic wave is zero, the received echo signal is mixed and processed to obtain its corresponding baseband signal. E r It is expressed as follows: ; (2) in, E r represents the baseband signal, represents the scattering coefficient, j represents the imaginary part of a complex number, v and Ω represent radial velocity and angular velocity respectively, λ represents the wavelength, l represents the mode of vortex electromagnetic waves, t represents the time-varying variable of the baseband signal, n ( t ) represents additive white Gaussian noise.

[0027] S3. Construct a dual-domain dictionary model, establish a dual-domain dictionary consisting of a radial velocity dictionary and an angular velocity dictionary, and preliminarily estimate the radial velocity and angular velocity by matching the dual-domain dictionary with the baseband signal.

[0028] Furthermore, step S3 includes the following steps: S31. The dual-domain dictionary is represented as follows: ;(3) in D Represents a dual-domain dictionary, Indicates that the dimension is 1× NM Matrix of represents the dictionary candidate set composed of radial velocities, f D ( v N )=2 v N / λ , v represents the radial velocity, λ represents the wavelength, t 1, ..., t N represents the discrete representation of the radial velocity dictionary candidate set, Indicates that the dimension is 1× N Matrix of Represents the dictionary candidate set composed of angular velocity, l represents the mode of the vortex electromagnetic wave, Ω represents the angular velocity, t 1, ..., t M represents the discrete representation of the candidate set of angular velocity dictionary, Indicates that the dimension is 1× M Matrix of j represents the imaginary part of a complex number, Represents a tensor product.

[0029] S32. Evaluate the degree of match between the dictionary and the signal Z NM : ; (4) in, Z NM Indicates the matching degree between the dual-domain dictionary and the baseband signal, U NM represents the weighting factor, E r represents the baseband signal, D Represents a dual-domain dictionary, N and M Indicates the dimensions of different dictionaries, v represents radial velocity, and Ω represents angular velocity.

[0030] S33. Preliminary estimation of radial velocity and angular velocity based on the matching degree , the formula is as follows: ; (5) in, N and M Indicates different dictionary dimensions, Z NM Indicates the matching degree between the dual-domain dictionary and the baseband signal, argmax indicates the value used to return the Z NM The index at which the maximum value is obtained ( N , M ), v (0) represents a preliminary estimate of the radial velocity, Ω (0) Represents a preliminary estimate of the angular velocity.

[0031] S4. Dynamic step size optimization: Construct a correlation function based on the preliminary estimation results, and design a dynamic step size iterative optimization until convergence to obtain a high-precision final parameter estimate.

[0032] Furthermore, step S4 is specifically as follows: ;(6) ; ; ;(7) in, F ( v , Ω) represents the correlation function, E r represents the baseband signal, E r(0) represents the baseband signal after preliminary estimation of parameters, v s Indicates the s The radial velocity of the iteration, v s+1 Indicates the s+ Radial velocity at 1 iteration, μ s Indicates the s The step size of the iteration, μ s+1 Indicates the s+ The step size of 1 iteration, Denotes the correlation function of radial velocity variables v The differential of Ω s Indicates the s The angular velocity of the iteration, Ω s+1 Indicates the s+ Angular velocity at 1 iteration, represents the differential of the correlation function with respect to the angular velocity variable Ω, F sIndicates the s The correlation function of the iteration, F s+1 Indicates the s+ The correlation function for 1 iteration, β and δ Is the adjustment factor, the value is between 0 and 1, δ To ensure that the equation does not converge to zero, when | F s+1 - F s |< ε , ε When is the set threshold, we get v and the final parameter estimates of Ω.

[0033] S5. Stability analysis: The final parameter estimate is used to construct a regularized objective function. The stability of the rotating object's motion is quantified by iterative optimization and calculation of the entropy value of the scattering coefficient probability distribution. The lower the entropy value, the higher the motion stability.

[0034] Furthermore, step S5 is specifically as follows: S51. Constructing the objective function Q ; ; (8) in, D Represents a dual-domain dictionary, A' represents the scattering coefficient, E r represents the baseband signal, L represents the smoothing operator, O 1 and O 2 represents the regularization term, and min represents the scattering coefficient that minimizes the value of the entire expression. A' , represents the square of the Euclidean norm, represents the Manhattan norm; S52, iterative optimization to solve the objective function; Due to the regularization term, directly solving the objective function cannot obtain the optimal closed-form solution. Therefore, this embodiment uses the following iterative optimization to solve the objective function: ; (9) in, ; ; (10) soft represents the soft threshold function, O 1 and O 2 represents the regularization term, q Represents the adjustment factor, its value should be greater than WThe largest eigenvalue of the matrix, O 1 / q represents the threshold value, m Indicates the m iterations, m+ 1 means the m+ 1 iteration, β Is the adjustment factor, the value is between 0 and 1, A' represents the scattering coefficient, △ A' Indicates the m At the iteration, the difference between the current iteration value and the previous iteration value, D Represents a dual-domain dictionary, H represents the matrix transpose, E r represents the baseband signal, L represents the smoothing operator, when the scattering coefficient m+ 1 iteration value and m When the difference between the iteration values ​​is less than the threshold, the iteration is stopped and the scattering coefficient is obtained.

[0035] S53. Calculate the entropy value according to the scattering coefficient.

[0036] ; (11) in, is the probability distribution of the scattering coefficient. Entropy is used here as a measure of instability, with lower entropy values ​​indicating regular and stable motion, and thus inferring the stability of the motion of the rotating object.

[0037] In the simulation, a helicopter is assumed to undergo a complex motion during landing. Landing is primarily achieved by adjusting the angle of attack of the rotor blades, so the angular velocity is typically kept constant. In addition to the rotation of the rotor blades, radial velocity relative to the antenna array is also involved. During landing, the rotating object is positioned above the uniform circular array antenna, effectively illuminating the helicopter with a vortex electromagnetic wave beam. Within a certain distance range, the intensity of the reflected signal increases, ensuring that the signal can be detected. Assume that the antenna frequency is 2.4 GHz, the antenna radiates vortex electromagnetic waves in mode 1, the angular velocity of the rotating object is 10π rad / s, and the radial velocity is 0.2 m / s. Additive white Gaussian noise is introduced to evaluate the robustness of the method.

[0038] The signal in step S2 is mixed, and then the baseband signal obtained is processed in steps S3 and S4. Figure 3 The final estimated values ​​of radial velocity and angular velocity obtained by processing in steps S3 and S4 are shown. Specifically, the two-dimensional color map shows v And the distribution on the candidate set of Ω, through the dual-domain dictionary model and dynamic step size optimization, we get ( v, Ω), which is shown as a bright spot on the 2D color map. This point corresponds to the estimated values ​​of radial velocity and angular velocity. In addition, the estimation accuracy of the parameters is related to the size of the dictionary candidate set. Figure 4 The relative error of the parameters for different candidate set sizes is shown. It can be observed that the relative errors of radial velocity and angular velocity gradually decrease as the number of dictionary candidate sets increases. This trend confirms that this embodiment can converge with higher accuracy when considering more dictionary candidate sets.

[0039] In order to evaluate the robustness of this embodiment, the signal-to-noise ratio is set to 5 dB to 20 dB and the dictionary candidate set size is 300. Figure 5 As can be seen in the figure, at 5 dB, the relative error between the reference and estimated values ​​is 0.35% for radial velocity and 0.25% for angular velocity; as the signal-to-noise ratio increases, the errors in radial velocity and angular velocity further decrease to 0.25% and 0.17%, respectively. These results confirm that the present embodiment has reliable performance and that accuracy improves with increasing signal-to-noise ratio. This improvement in accuracy is attributed to dynamic step size optimization, which improves parameter estimation accuracy by prioritizing highly correlated regions in the parameter space. At low signal-to-noise ratios, the accuracy of parameter estimation also decreases due to the reduced correlation in dictionary matching.

[0040] After obtaining the parameters of radial velocity and angular velocity, the phase of the signal can be reconstructed, which is the basis for solving the scattering coefficient. Subsequently, according to step S5, iterative optimization is used to solve the regularized objective function to obtain the scattering coefficient, that is, the amplitude of the signal. Figure 6 and Figure 7 The reconstructed amplitude and phase over time for a signal-to-noise ratio of 20 dB are shown. The amplitude stabilizes near the expected value, while the phase becomes more continuous. Because the relative error in parameter estimation is lowest and the amplitude fluctuations are relatively small when the signal-to-noise ratio is 20 dB, the entropy of the scattering coefficient is calculated under this condition as the basis for estimating the stability of the helicopter during landing. The scattering coefficient is discretized and the entropy is calculated, resulting in an entropy value of 0.69. Since entropy can be considered a measure of instability, lower entropy values ​​indicate more stable motion. As can be seen, this relatively low entropy value indicates the stability of the helicopter during landing.

[0041] Compared with existing methods, the method of the present invention not only realizes the synchronous estimation of the parameters of the rotating object, but also has higher accuracy and robustness, and also has the ability to analyze the motion stability of the rotating object.

[0042] It should be noted that, for the sake of convenience, the aforementioned method embodiments are all expressed as a series of action combinations, but those skilled in the art should know that the present invention is not limited to the described order of actions, because according to the present invention, certain steps can be performed in other orders or simultaneously.

[0043] Based on the same concept as the method for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves in the above-mentioned embodiment, the present invention also provides a system for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves, which can be used to execute the above-mentioned method for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves. For ease of explanation, the structural diagram of the embodiment of the system for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves only shows the parts related to the embodiment of the present invention. Those skilled in the art will understand that the illustrated structure does not constitute a limitation of the device, and may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0044] See also Figure 8 In another embodiment of the present application, a rotating object parameter estimation and stability analysis system 100 based on vortex electromagnetic waves is provided, the system comprising a mathematical model construction module 101, an echo baseband signal acquisition module 102, a dual-domain dictionary construction module 103, a dynamic step size optimization module 104, and a stability analysis module 105; The mathematical model building module 101 is used to generate vortex electromagnetic waves using a uniform circular array antenna, regard the rotating object as an ideal scattering point, and establish an expression for the electric field intensity of the scattering point; The echo baseband signal acquisition module 102 is used to perform frequency mixing processing on the received echo signal to obtain a baseband signal including radial velocity and angle; The dual-domain dictionary building module 103 is used to build a dual-domain dictionary consisting of a radial velocity dictionary and an angular velocity dictionary, and preliminarily estimate the radial velocity and angular velocity by matching the dual-domain dictionary with the baseband signal; The dynamic step size optimization module 104 is used to construct a correlation function based on the preliminary estimation results, and to design a dynamic step size iterative optimization until convergence, thereby obtaining a high-precision final parameter estimate; The stability analysis module 105 is used to construct a regularized objective function using the final parameter estimate obtained, solve the scattering coefficient through iterative optimization, and calculate the entropy value of the probability distribution of the scattering coefficient. The stability of the rotating object motion is quantified according to the entropy value, and the lower the entropy value, the higher the motion stability.

[0045] It should be noted that the rotating object parameter estimation and stability analysis system based on vortex electromagnetic waves of the present invention corresponds one-to-one to the rotating object parameter estimation and stability analysis method based on vortex electromagnetic waves of the present invention. The technical features and beneficial effects described in the above-mentioned embodiment of the rotating object parameter estimation and stability analysis method based on vortex electromagnetic waves are all applicable to the embodiment of the rotating object parameter estimation and stability analysis method based on vortex electromagnetic waves. For specific contents, please refer to the description in the embodiment of the method of the present invention. No further details will be given here. This is hereby declared.

[0046] In addition, in the implementation of the rotating object parameter estimation and stability analysis system based on vortex electromagnetic waves in the above-mentioned embodiment, the logical division of each program module is only an example. In actual application, the above-mentioned functions can be assigned to different program modules as needed, for example, for the configuration requirements of the corresponding hardware or the convenience of software implementation. That is, the internal structure of the rotating object parameter estimation and stability analysis system based on vortex electromagnetic waves is divided into different program modules to complete all or part of the functions described above.

[0047] See also Figure 9 In one embodiment, an electronic device for implementing a method for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves is provided. The electronic device 200 may include a first processor 201, a first memory 202 and a bus, and may also include a computer program stored in the first memory 202 and executable on the first processor 201, such as a program 203 for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves.

[0048] Wherein, the first memory 202 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (for example, SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the first memory 202 can be an internal storage unit of the electronic device 200, such as a mobile hard disk of the electronic device 200. In other embodiments, the first memory 202 can also be an external storage device of the electronic device 200, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 200. Further, the first memory 202 can also include both an internal storage unit of the electronic device 200 and an external storage device. The first memory 202 can not only be used to store application software and various types of data installed in the electronic device 200, such as the code of the rotating object parameter estimation and stability analysis program 203 based on vortex electromagnetic waves, but can also be used to temporarily store data that has been output or is to be output.

[0049] In some embodiments, the first processor 201 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including a combination of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The first processor 201 is the control core (Control Unit) of the electronic device, connecting the various components of the entire electronic device using various interfaces and lines, and executing or executing programs or modules stored in the first memory 202, as well as calling data stored in the first memory 202, to perform various functions of the electronic device 200 and process data.

[0050] Figure 9 Only the electronic device with components is shown, and it can be understood by those skilled in the art that Figure 9 The structure shown does not constitute a limitation on the electronic device 200 , and the electronic device 200 may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0051] The rotating object parameter estimation and stability analysis program 203 based on vortex electromagnetic waves stored in the first memory 202 of the electronic device 200 is a combination of multiple instructions. When running in the first processor 201, it can achieve the following: Using a uniform circular array antenna to generate vortex electromagnetic waves, the rotating object is regarded as an ideal scattering point, and the electric field intensity expression of the scattering point is established; Mixing the echo signal to obtain a baseband signal containing radial velocity and angular velocity; A dual-domain dictionary consisting of a radial velocity dictionary and an angular velocity dictionary is established, and the radial velocity and angular velocity are preliminarily estimated by matching the dual-domain dictionary with the baseband signal; Based on the preliminary estimation results, a correlation function is constructed, and a dynamic step size is designed for iterative optimization until convergence, resulting in a high-precision final parameter estimate. The obtained final parameter estimation is used to construct a regularized objective function, and the stability of the rotating object's motion is quantified by iterative optimization and calculation of the entropy value of the scattering coefficient probability distribution. The lower the entropy value, the higher the motion stability.

[0052] Furthermore, if the modules / units integrated in the electronic device 200 are implemented as software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium. The computer-readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0053] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0054] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0055] The above embodiments are preferred implementations of the present invention, but the implementations of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be considered equivalent replacement methods and are included in the scope of protection of the present invention.

Claims

1. A method for parameter estimation and stability analysis of rotating objects based on vortex electromagnetic waves, characterized in that: The steps include: Using a uniform circular array antenna to generate vortex electromagnetic waves, the rotating object is regarded as an ideal scattering point, and the electric field intensity expression of the scattering point is established; Mixing the echo signal to obtain a baseband signal containing radial velocity and angular velocity; A dual-domain dictionary consisting of a radial velocity dictionary and an angular velocity dictionary is established, and the radial velocity and angular velocity are preliminarily estimated by matching the dual-domain dictionary with the baseband signal; Based on the preliminary estimation results, a correlation function is constructed, and a dynamic step size is designed for iterative optimization until convergence, resulting in a high-precision final parameter estimate. The obtained final parameter estimation is used to construct a regularized objective function, and the stability of the rotating object's motion is quantified by iterative optimization and calculation of the entropy value of the scattering coefficient probability distribution. The lower the entropy value, the higher the motion stability.

2. The method for parameter estimation and stability analysis of rotating objects based on vortex electromagnetic waves according to claim 1, characterized in that: The electric field strength expression is specifically: ； in, E s represents the electric field strength, B Indicates the number of antenna units, represents an imaginary number, j represents the imaginary part of a complex number, k represents the wave number, l represents the mode of vortex electromagnetic wave, f 0 indicates the carrier frequency, t is the variable that represents the time-varying electric field, θ and φ denote the elevation angle and azimuth angle respectively, α represents the radius of the antenna, J l ( kα sin θ ) is the first category l Bessel function of order.

3. The method for parameter estimation and stability analysis of rotating objects based on vortex electromagnetic waves according to claim 1, characterized in that: The baseband signal expression is: ； in, E r represents the baseband signal, represents the scattering coefficient, j represents the imaginary part of a complex number, v and Ω represent radial velocity and angular velocity respectively, λ represents the wavelength, l represents the mode of vortex electromagnetic wave, t represents the time-varying variable of the baseband signal, n ( t ) represents additive white Gaussian noise.

4. The method for parameter estimation and stability analysis of rotating objects based on vortex electromagnetic waves according to claim 1, characterized in that: The dual-domain dictionary is defined as: ； in D Represents a dual-domain dictionary, Indicates that the dimension is 1× NM Matrix of represents the dictionary candidate set composed of radial velocities, f D ( v N )=2 v N / λ , v represents the radial velocity, λ represents the wavelength, t 1, ..., t N represents the discrete representation of the radial velocity dictionary candidate set, Indicates that the dimension is 1× N Matrix of Represents the dictionary candidate set composed of angular velocity, l represents the mode of the vortex electromagnetic wave, Ω represents the angular velocity, t 1, ..., t M represents the discrete representation of the candidate set of angular velocity dictionary, Indicates that the dimension is 1× M Matrix of j represents the imaginary part of a complex number, Represents a tensor product.

5. The method for parameter estimation and stability analysis of rotating objects based on vortex electromagnetic waves according to claim 1, characterized in that: The matching is: ； in, Z NM Indicates the matching degree between the dual-domain dictionary and the baseband signal, U NM represents the weighting factor, E r represents the baseband signal, D Represents a dual-domain dictionary, N and M Indicates the dimensions of different dictionaries, v represents radial velocity, and Ω represents angular velocity.

6. The method for parameter estimation and stability analysis of rotating objects based on vortex electromagnetic waves according to claim 1, characterized in that: The correlation function and dynamic step size are: ； ； ； ； in, F ( v , Ω) represents the correlation function, E r represents the baseband signal, E r(0) represents the baseband signal after preliminary estimation of parameters, v s Indicates the s The radial velocity of the iteration, v s+1 Indicates the s+ Radial velocity at 1 iteration, μ s Indicates the s The step size of the iteration, μ s+1 Indicates the s+ The step size of 1 iteration, Denotes the correlation function of radial velocity variables v The differential of Ω s Indicates the s The angular velocity of the iteration, Ω s+1 Indicates the s+ Angular velocity at 1 iteration, represents the differential of the correlation function with respect to the angular velocity variable Ω, F s Indicates the s The correlation function of the iteration, F s+1 Indicates the s+ The correlation function for 1 iteration, β and δ Is the adjustment factor, the value is between 0 and 1, δ To ensure that the equation does not converge to zero, when | F s+1 - F s |< ε , ε When is the set threshold, we get v and the final parameter estimates of Ω.

7. The method for parameter estimation and stability analysis of rotating objects based on vortex electromagnetic waves according to claim 1, characterized in that: The final parameter estimate is used to construct a regularized objective function. The scattering coefficient is solved through iterative optimization, and the entropy of the probability distribution of the scattering coefficient is calculated. The stability of the rotating object motion is quantified based on the entropy value, specifically: Constructing the objective function Q : ； in, D Represents a dual-domain dictionary, A' represents the scattering coefficient, E r represents the baseband signal, L represents the smoothing operator, O 1 and O 2 represents the regularization term, and min represents the scattering coefficient that minimizes the value of the entire expression. A' , represents the square of the Euclidean norm, represents the Manhattan norm; Iterative optimization solves the objective function: ； in, ； ； soft represents the soft threshold function, O 1 and O 2 represents the regularization term, q Represents the adjustment factor, its value should be greater than W The largest eigenvalue of the matrix, O 1 / q represents the threshold value, m Indicates the m iterations, m+ 1 means the m+ 1 iteration, β Is the adjustment factor, the value is between 0 and 1, A' represents the scattering coefficient, △ A' Indicates the m At the iteration, the difference between the current iteration value and the previous iteration value, D Represents a dual-domain dictionary, H represents the matrix transpose, E r represents the baseband signal, L represents the smoothing operator, when the scattering coefficient m+ 1 iteration value and m When the difference between the iteration values ​​is less than the threshold, the iteration is stopped and the scattering coefficient is obtained; Calculate the entropy value based on the scattering coefficient: ； in, is the probability distribution of the scattering coefficient.

8. A rotating object parameter estimation and stability analysis system based on vortex electromagnetic waves, characterized in that: A method for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves, applied to any one of claims 1-7, comprising a mathematical model construction module, an echo baseband signal acquisition module, a dual-domain dictionary construction module, a dynamic step size optimization module, and a stability analysis module; The mathematical model building module is used to generate vortex electromagnetic waves using a uniform circular array antenna, regard the rotating object as an ideal scattering point, and establish an expression for the electric field intensity of the scattering point; The echo baseband signal acquisition module is used to mix the echo signal to obtain a baseband signal containing radial velocity and angular velocity; The dual-domain dictionary building module is used to establish a dual-domain dictionary consisting of a radial velocity dictionary and an angular velocity dictionary, and preliminarily estimate the radial velocity and angular velocity by matching the dual-domain dictionary with the baseband signal; The dynamic step size optimization module is used to construct a correlation function based on the preliminary estimation results, and to design a dynamic step size iterative optimization until convergence, thereby obtaining a high-precision final parameter estimate; The stability analysis module is used to construct a regularized objective function using the obtained final parameter estimate, and quantify the stability of the rotating object's motion by iterative optimization and calculating the entropy value of the scattering coefficient probability distribution. The lower the entropy value, the higher the motion stability.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores computer program instructions that can be executed by the at least one processor, and the computer program instructions are executed by the at least one processor so that the at least one processor can execute the rotating object parameter estimation and stability analysis method based on vortex electromagnetic waves as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a program, characterized in that: When the program is executed by a processor, the method for parameter estimation and stability analysis of a rotating object based on vortex electromagnetic waves according to any one of claims 1 to 7 is implemented.

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