Signal parameter generation method, apparatus and system, and sensing device

Abstract

Provided in the present application are a signal parameter generation method, apparatus and system, and a sensing device. The signal parameter generation method comprises the following steps: inputting an original signal, the original signal being an R-dimensional signal including M frequency components, wherein M and R are both greater than or equal to 1; extracting I sub-signals from the original signal, wherein I is greater than or equal to 1; and constructing a plurality of equations about the I sub-signals, and solving the equations, so as to obtain signal parameters of the original signal, wherein the signal parameters include one or more of amplitude parameter, phase parameter, frequency parameter and damping coefficient. The signal parameter generation method, apparatus and system and the sensing device in the present application can significantly improve the accuracy and reliability of signal parameter estimation.

Description

Signal parameter generation methods, devices, systems and sensing equipment Technical Field

[0001] This application relates primarily to the field of signal processing, and more particularly to a method, apparatus, system, and sensing device for generating signal parameters. Background Technology

[0002] In many practical engineering applications, the signals transmitted by sensors need to be processed by specific algorithms to obtain relevant useful information, such as distance, position, and velocity. This information is actually calculated using physical laws after estimating the signal parameters. Therefore, signal parameter estimation is a very important problem in many engineering applications.

[0003] Signal parameters include frequency, phase, amplitude, and damping coefficient. Different practical applications require different parameters. The parameters to be estimated may be the signal frequency, amplitude, frequency and phase, or all parameters, depending on the specific application scenario. For one-dimensional or multi-dimensional signals with multiple frequencies (discrete frequencies), especially when different frequencies are very close together in the spectrum, existing methods cannot accurately and robustly estimate the signal parameters. Summary of the Invention

[0004] The technical problem to be solved by this application is to provide a signal parameter generation method, apparatus, system and sensing device, which can significantly improve the accuracy and reliability of signal parameter estimation.

[0005] To address the aforementioned technical problems, this application provides a signal parameter generation method, comprising the following steps: inputting an original signal, wherein the original signal is an R-dimensional signal containing M frequency components, wherein M and R are both greater than or equal to 1; extracting I sub-signals from the original signal, wherein I is greater than or equal to 1; and constructing multiple equations concerning the I sub-signals, and solving the multiple equations to obtain the signal parameters of the original signal, wherein the signal parameters include one or more of amplitude parameters, phase parameters, frequency parameters, and damping coefficients.

[0006] In one embodiment of this application, the signal parameter generation method further includes: obtaining the frequency domain value and peak point coordinates corresponding to one or more peaks in the spectrum of each sub-signal; and including the frequency domain value and peak point coordinates in the equation.

[0007] In one embodiment of this application, obtaining the frequency domain value and peak coordinates corresponding to one or more peaks in the spectrum of each sub-signal includes: performing a Discrete Fourier Transform (DFT), zero-padding Fourier Transform, interpolated Fourier Transform, or CZT transform on the original signal, and obtaining the frequency domain value and peak coordinates corresponding to one or more peaks in the spectrum of the original signal; and calculating the frequency domain value and peak coordinates corresponding to one or more peaks in the spectrum of each sub-signal.

[0008] In one embodiment of this application, obtaining the frequency domain value and peak coordinates corresponding to one or more peaks in the spectrum of each sub-signal includes: performing a Discrete Fourier Transform, Zero-padding Fourier Transform, Interpolated Fourier Transform, or CZT Transform on a first portion of the I sub-signals, and obtaining the frequency domain value and peak coordinates corresponding to one or more peaks in the spectrum of the first portion of the sub-signals; and calculating the frequency domain value and peak coordinates corresponding to one or more peaks in the spectrum of the second portion of the I sub-signals.

[0009] In one embodiment of this application, the frequency domain value is a DFT value.

[0010] In one embodiment of this application, the sub-signal includes Where i=1,...,I, r=1,...,R, Let be the length of the i-th sub-signal in the r-th dimension.

[0011] In one embodiment of this application, the original signal includes s(n1,...,n R ):

[0012] and:

[0013] Where F r and N r These are the sampling frequency and signal length in the r-th dimension, respectively, A m and These are the amplitude parameters and initial phase of the original signal for the m-th frequency component of the original signal, respectively, f m,r and β m,r These are the frequency parameter and damping coefficient of the m-th frequency component of the original signal in the r-th dimension, respectively, and η i =1,2,... is the downsampling rate of the i-th sub-signal; and These are the amplitude parameter and initial phase of the m-th frequency component of the i-th sub-signal, respectively. Let be the index of the initial point of the i-th sub-signal; It is the discrete Fourier transform frequency of the m-th frequency component of the i-th sub-signal in the r-th dimension, where Defined as

[0014] In one embodiment of this application, it is assumed that the peak point of the p-th frequency component of the i-th sub-signal in the r-th dimension is at... The DFT of the i-th sub-signal is at point The value is written as in,

[0015] In one embodiment of this application, the signal parameter generation method further includes using the formula Applying this to all peak points of the spectrum corresponding to the I sub-signals, we obtain 2M*I equations as follows:

[0016] in, W = diag{W 1 W 2 ,…,W I}

[0017] in,

[0018] In one embodiment of this application, when the equation is a nonlinear equation, the method further includes: calculating the initial values ​​of the signal parameters.

[0019] In one embodiment of this application, the steps of solving the equation include using the Levenberg-Marquardt, Newton-Raphson, or Gaussian-Newton algorithm.

[0020] In one embodiment of this application, in the step of extracting I sub-signals from the original signal, the number I of the extracted sub-signals satisfies the following condition: I ≥ R + 1.

[0021] In one embodiment of this application, if the damping coefficient is not included in the signal parameters of the original signal, then in the step of extracting I sub-signals from the original signal, the number of sub-signals I extracted satisfies the following condition: I≥ceil(R / 2)+1.

[0022] In one embodiment of this application, if the original signal is a periodic signal with a known mathematical model, the method further includes setting the value of M to 1.

[0023] In one embodiment of this application, if some parameters of the original signal have interrelated calculation relationships, the method further includes, in the step of extracting I sub-signals from the original signal, setting the minimum value of the number I of the extracted sub-signals to 1 or the sub-signals to be equivalent to the original signal.

[0024] In one embodiment of this application, the frequency parameter and the phase parameter of the original signal have a mutually related calculation relationship, and the damping coefficient is 0 or less than the damping coefficient threshold.

[0025] In one embodiment of this application, the original signal includes an intermediate frequency signal generated by mixing an FMCW signal or a CTFM signal.

[0026] In one embodiment of this application, when the original signal is an intermediate frequency (IF) signal generated by mixing the FMCW or CTFM signal, the frequency-phase relationship of the IF signal is as follows:

[0027] Where κ = f0 / B, f0 and B are the initial frequency and effective bandwidth of the FMCW or CTFM signal, respectively, and T is the sampling time length of the intermediate frequency signal. The phase jump is caused by the reflection of the FMCW or CTFM signal on the object surface, and the equation includes:

[0028] in

[0029] This application also provides a signal parameter generation device, comprising:

[0030] The signal receiver is configured to receive the raw signal.

[0031] The processing module is configured to generate signal parameters of the original signal using the method described above, wherein the signal parameters include one or more of amplitude parameters, phase parameters, frequency parameters, and damping coefficients; and

[0032] The signal output terminal is configured to output the signal parameters of the original signal.

[0033] This application also provides a sensing device, including the signal parameter generation apparatus described above.

[0034] In one embodiment of this application, the sensing device includes a radar device or a sonar device.

[0035] In one embodiment of this application, the radar device includes a lidar device, a millimeter-wave radar device, or an ultrasonic radar device.

[0036] This application also provides a signal parameter generation system, comprising: a memory for storing instructions executable by a processor; and a processor for executing the instructions to implement the method described above.

[0037] This application also provides a computer-readable medium storing computer program code that, when executed by a processor, implements the method described above.

[0038] Compared with existing technologies, this application has the following advantages: By extracting sub-signals from the original signal and solving equations that are equal to or greater than the number of unknown parameters, the signal parameters of the original signal can be accurately reconstructed, significantly improving the accuracy and reliability of signal parameter estimation. Furthermore, by calculating the frequency domain value corresponding to the peak value in the spectrum of each sub-signal and including this value in the equation, the computational difficulty can be reduced and computational efficiency improved. In some embodiments, the computational process can be further optimized for original signals with different characteristics, thereby reducing computational difficulty and improving computational efficiency. This application can be widely used in specific application fields, such as radar and sonar equipment, to improve the accuracy of distance measurement. Attached Figure Description

[0039] The accompanying drawings are included to provide a further understanding of this application. They are incorporated into and constitute a part of this application. The drawings illustrate embodiments of this application and, together with this specification, serve to explain the principles of this application.

[0040] In the attached image:

[0041] Figure 1 is a schematic flowchart of a signal parameter generation method according to an embodiment of this application;

[0042] Figure 2 is a flowchart illustrating a signal parameter generation method according to another embodiment of this application;

[0043] Figures 3 and 4 are schematic diagrams of the sub-signal extraction methods of one-dimensional and two-dimensional original signals in a signal parameter generation method according to an embodiment of this application.

[0044] Figure 5 is a structural diagram of a signal parameter generation device according to an embodiment of this application; and

[0045] Figure 6 is a system block diagram of a signal parameter generation system according to an embodiment of this application. Detailed Implementation

[0046] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this application. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0047] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" are not specifically singular and may include plural forms. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0048] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following drawings denote similar items; therefore, once an item is defined in one drawing, it need not be further discussed in subsequent drawings.

[0049] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, these terms have no special meaning and therefore should not be construed as limiting the scope of protection of this application. In addition, although the terminology used in this application is selected from commonly known and used terms, some terms mentioned in this application's specification may have been chosen by the applicant according to his or her judgment, and their detailed meanings are explained in the relevant sections of this description. Moreover, this application should be understood not only through the actual terms used, but also through the meaning implied by each term.

[0050] One embodiment of this application, referring to FIG1, proposes a signal parameter generation method 10 (hereinafter referred to as "method 10"), which can significantly improve the accuracy and reliability of signal parameter estimation. The accompanying drawings, including FIG1, use flowcharts to illustrate the operations performed by the system according to an embodiment of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more steps may be removed from these processes.

[0051] According to Figure 1, method 10 includes the following steps: Step 11 is to input the original signal, which is an R-dimensional signal containing M frequency components, where M and R are both greater than or equal to 1. It should be noted that the original signal used in this application contains M frequency components, which can be understood by those skilled in the art as M discrete frequency components. Step 12 is to extract I sub-signals from the original signal, where I is greater than or equal to 1. Step 13 is to construct multiple equations about the I sub-signals and then solve these equations to obtain the signal parameters of the original signal. The signal parameters include one or more of the following: amplitude parameter, phase parameter, frequency parameter, and damping coefficient.

[0052] In the various embodiments of this application, including Figure 1, since the original signal is an R-dimensional signal containing M frequency components, the original signal can be represented as follows: the original signal includes s(n1,...,n R ), specifically

[0053] Where, n r =0,...,N r -1, F r and N r These are the sampling frequency and signal length in the r-th dimension, respectively, A m and These are the amplitude parameter and initial phase of the m-th frequency component of the original signal, respectively, f m,r and β m,r These are the frequency parameter and damping coefficient of the m-th frequency component of the original signal in the r-th dimension, respectively.

[0054] In step 12, each of the I sub-signals also contains an R-dimensional signal with M frequency components. For example, Figures 3 and 4 illustrate the extraction of I sub-signals from a one-dimensional signal and a two-dimensional signal, respectively. First, according to Figure 3, it shows a schematic diagram of extracting two sub-signals from a given one-dimensional original signal, where 31 and 32 represent the regions containing the first and second sub-signals, respectively. Correspondingly, referring to Figure 4, for a given two-dimensional sinusoidal signal as the original signal, the three rectangles in Figure 4 represent the three extracted sub-signals, with each sub-signal's rectangle corresponding to different position coordinates.

[0055] In step 13, since the signal parameters of each sub-signal are either the same or related to each other, and the signal parameters of each sub-signal are related to the signal parameters of the original signal, we can extract I sub-signals from the original signal, establish a set of equations about the signal parameters for each sub-signal, obtain equations that are equal to or greater than the number of unknown signal parameters (i.e., the number of equations is greater than or equal to the total number of unknown parameters), and solve them to obtain the signal parameters of the original signal.

[0056] In the above technical solution of this application, by extracting multiple sub-signals from the original signal, since the parameters of each sub-signal are either the same or related to each other, and the parameters of each sub-signal are related to the signal parameters of the original signal, the parameters of the original signal can be obtained by establishing and solving a system of equations about the signal parameters, and the solution result has very high accuracy and reliability.

[0057] Figure 2 is a schematic flowchart of a signal parameter generation method according to another embodiment of this application. Referring to Figure 2, steps 21 and 22 of the signal parameter generation method 20 are similar to steps 11 and 12 of the previous embodiment, and will not be elaborated here. Method 20 further includes step 23, obtaining the frequency domain value and peak coordinates corresponding to one or more peaks in the spectrum of each sub-signal. Here, the frequency domain value includes the amplitude and phase of the peak point. The specific process of step 23 will be described in detail below. In the following description, DFT values ​​are used as an example of frequency domain values.

[0058] For ease of subsequent calculations, assume that the discrete Fourier transform frequency of the m-th frequency component in the r-th dimension is:

[0059] definition:

[0060] The original signal can then be rewritten as:

[0061] Performing a Fourier transform on the original signal yields the original signal s(n1,...,n). RThe DFT values ​​of ) are as follows:

[0062] Based on this, assume that the peak point of the spectrum of the p-th frequency component in the r-th dimension is at k. p,r According to formula (4), the DFT of the signal at point (k) p,1 ,...,k p,R The value of ) can be written as

[0063] Here, (k) p,1 ,...,k p,R () represents the coordinates of the peak point.

[0064] Among them, W r (k) is a length of N r The k-th spectral line of the DFT of the rectangular window, W r The expression for (k) is

[0065] According to formula (6), we can obtain:

[0066] Where S p It can be calculated using formula (5). By observation, it can be seen that two equations can be obtained for each peak point, so a total of 2M equations can be obtained from M peak points. Since the original signal has a total of M amplitude parameters, M phase parameters, M*R frequency parameters and M*R damping coefficients, there are a total of 2M+2M*R unknown parameters to be solved. By extracting I sub-signals from the original signal (each sub-signal contains M peaks) to obtain equations that are equal to or greater than the number of unknown parameters (i.e., the number of equations is greater than or equal to the total number of unknown parameters), these unknowns can be further solved.

[0067] In several embodiments of this application, preferably, the number of segments I of the sub-signal satisfies the following condition: I ≥ R + 1. Specifically, since each sub-signal can provide 2M equations, this application proposes that in some embodiments, at least R + 1 sub-signals are required to facilitate equation solving, i.e., I ≥ R + 1. For example, if the original signal is a one-dimensional signal, i.e., R = 1, and assuming M = 1, then according to the above constraints, I is greater than or equal to 2 (i.e., two or more sub-signals are obtained). For such an original signal, the total number of original parameters (unknown parameters) to be solved is 2M + 2M * R = 4. Therefore, in step 14 shown in Figure 1, at least 4 equations need to be constructed to solve for all the original parameters. Therefore, when I is at least 2, the number of equations is at least 2M * I, i.e., 4 equations, which can satisfy the above requirement of solving for all the original parameters, and the solution result is more comprehensive and complete. Of course, this application is not limited to this. If some of the original parameters are solved or the original signal has specific properties, the above-mentioned I≥R+1 constraint condition may not be strictly enforced. This will be further explained below.

[0068] Based on this, for step 23 in method 20 as shown in Figure 2, if it is necessary to calculate the frequency domain value and peak point coordinates corresponding to one or more peaks of the sub-signal spectrum for each sub-signal, this step can be specifically implemented as follows:

[0069] Assuming the sub-signal has a length in the r-th dimension, and the initial point index and downsampling rate are respectively... and η i Downsampling rate is a metric for downsampling; specifically, it refers to the percentage of the original signal retained after downsampling with a spacing of η. i Sampling points. Definition The i-th sub-signal is defined as:

[0070] in,

[0071] Suppose that the peak point of the p-th frequency component of the i-th sub-signal in the r-th dimension is at... The DFT of the i-th sub-signal is at point The value is written as:

[0072] Here, These are the coordinates of the peak point.

[0073] in,

[0074] More preferably, step 24 further includes formula Applying this to all peak points of the spectrum corresponding to the I sub-signals, we obtain 2M*I equations as follows:

[0075] in,

[0076] in,

[0077] In the above formula (14), the diag function is used to create a block diagonal matrix.

[0078] Alternatively, instead of performing a complete original signal, one can perform a Discrete Fourier Transform (DFT), Zero-padding Fourier Transform (DFT), Interpolated Fourier Transform (IFT), CZT Transform (CZT), or other known transforms on the first portion of the I sub-signals. This yields the frequency domain values ​​(e.g., DFT values) and peak coordinates corresponding to one or more peaks in the spectrum of the first portion of the sub-signals. The first portion of the sub-signals can be one or more sub-signals. Then, since the frequency domain values ​​and peak coordinates of the first portion of the sub-signals have been calculated, it is only necessary to calculate the frequency domain values ​​and peak coordinates corresponding to one or more peaks in the spectrum of the second portion of the I sub-signals. The second portion of the sub-signals consists of all sub-signals except the first portion.

[0079] Although the preceding text uses DFT values ​​as an example, it is understood that the frequency domain values ​​calculated in step 23 can also be other types of values, such as CZT values.

[0080] It should be noted that, depending on the type of raw signal being processed, for some types of raw signals, the 2M*I equations constructed in step 24 as shown in Figure 2 are nonlinear equations. However, it is not excluded that for some specific signal types, only linear equations need to be constructed in step 24. In particular, based on the above calculation method, preferably, when the equations constructed in step 24 of method 20 as shown in Figure 2 are nonlinear equations, method 20 also includes calculating the initial values ​​of the signal parameters.

[0081] Specifically, in the calculation process shown in Figure 2, the original signal or the first sub-signal undergoes Discrete Fourier Transform (DFT), Zero-padding Fourier Transform (ZFT), Interpolation Fourier Transform (IFT), CZT Transform, or other known transformations, and the initial values ​​of the signal parameters are calculated. This involves two methods for calculating the initial values ​​of the signal parameters: performing DFT, ZFT, IFT, CZT Transform, or other known transformations on the original signal and the sub-signal, respectively. Since DFT, ZFT, IFT, or CZT Transform is also required when determining the frequency domain values ​​and peak coordinates corresponding to one or more peaks in step 23, the results of DFT, ZFT, IFT, or CZT Transform can be used simultaneously to determine the frequency domain values ​​and peak coordinates corresponding to one or more peaks and to calculate the initial values ​​of the signal parameters.

[0082] Specifically, if a Discrete Fourier Transform, Zero-padding Fourier Transform, Interpolated Fourier Transform, or CZT Transform is performed on the original signal in step 23 of Figure 2, then this result can be directly used when calculating the initial value afterwards. Conversely, if the initial value is calculated before calculating the frequency domain value and peak point coordinates in step 23, then this result can be used in step 23 to directly calculate the frequency domain value and peak point coordinates corresponding to one or more peaks of the sub-signal spectrum for each sub-signal.

[0083] Furthermore, if step 23 in Figure 2 employs Discrete Fourier Transform, Zero-padding Fourier Transform, Interpolated Fourier Transform, or CZT Transform on the sub-signals, and more than one sub-signal was extracted in the preceding steps, then in this step, only the initial value for the spectrum corresponding to one of the sub-signals needs to be calculated. Conversely, if the initial value for the spectrum corresponding to one sub-signal is calculated before step 23, this result can be directly used in step 23. That is, for sub-signals that have undergone Discrete Fourier Transform, Zero-padding Fourier Transform, Interpolated Fourier Transform, or CZT Transform, the value can be directly obtained, while for other sub-signals, the frequency domain value and peak coordinates corresponding to the peaks need to be calculated. Preferably, other sub-signals do not need to be calculated for the complete spectrum, but only for the peak points.

[0084] In some embodiments, zero-padded Fourier transform (i.e., zero-padded method), interpolated Fourier transform, CZT method, or other known methods are used to obtain more accurate peak point coordinates. And it is used to obtain the frequency domain value corresponding to one or more peaks in the spectrum of each sub-signal. Specifically, it uses... Replace the peak point coordinates in formulas (11)-(15) Calculations are performed to make the final calculated signal parameters more accurate.

[0085] In some embodiments, zero-padded Fourier transform (i.e., zero-padded method), interpolated Fourier transform, CZT method, or other known methods are used to obtain more accurate peak point coordinates. Using the more precise peak point coordinates (i.e., peak point frequency), more accurate initial values ​​of signal parameters can be calculated.

[0086] Preferably, in such embodiments, the steps of solving the equations include using algorithms such as Levenberg-Marquardt, Newton-Raphson, or Gaussian-Newton. It is understood that the above-described algorithms for solving the equations are merely illustrative examples, and this application is not limited to these algorithms.

[0087] As explained above, in the step of extracting I sub-signals from the original signal, it is preferable to ensure that I ≥ R + 1, thereby obtaining a more complete and comprehensive solution. In different application scenarios of this application, considering the different types of original signals being processed, the calculation method can be further optimized to improve calculation speed and accuracy.

[0088] First, if the original signal's signal parameters do not include the damping coefficient, then in the step of extracting I sub-signals from the original signal, the number of sub-signals I does not need to satisfy the constraint I ≥ R + 1, but only needs to satisfy the following condition: I ≥ ceil(R / 2) + 1. Here, the ceil function is the floor function. Specifically, for such signals, since the original signal's signal parameters do not include the damping coefficient (which in some cases can also be called the attenuation factor), such as signals whose amplitude does not significantly attenuate with time and space, the total number of signal parameters (i.e., unknown parameters) of such original signals is 2M + M*R. By simplifying the number of I as described above, the number of equations can be reduced, thereby reducing the pressure of solving the equations and improving computational accuracy while saving computational resources.

[0089] Furthermore, if the original signal is a periodic signal known from the mathematical model, the value of M can be set to 1. For example, such an original signal could be a square wave, a triangular wave, a sawtooth wave, etc. In this case, M = 1 can be directly set to reduce the number of equations and obtain the corresponding signal parameter solutions, making the calculation simple and convenient. For example, taking a square wave as an example, with a frequency of f1 and a phase of... The signal expression for the square wave is:

[0090] Its Fourier expansion is

[0091] After sampling

[0092] In this embodiment, although the original signal is a multi-frequency signal, since the frequency, amplitude, and phase of other frequency components are all related to the frequency, amplitude, and phase of the fundamental frequency, it is only necessary to calculate the peak value of the fundamental frequency or any one of the frequencies. Therefore, by setting the value of M to 1, the number of equations can be effectively reduced, thereby reducing the computational burden of solving the equations.

[0093] Building upon this, in some embodiments, if some parameters of the original signal have interrelated calculation relationships, then in the process of extracting I sub-signals from the original signal in step 12 of Figure 1 or step 22 of Figure 2, the minimum value of the number of sub-signals I can be set to 1, and the sub-signals can be equivalent to the original signal. In such embodiments, a more specific type is where the frequency parameter and phase parameter of the original signal have interrelated calculation relationships, and the damping coefficient is 0 or less than the damping coefficient threshold; that is, there are only M unknown amplitude parameters and M unknown frequency or phase parameters. Therefore, the number of unknowns in the original signal parameters is 2M. In such embodiments, to achieve the most accurate parameter estimation, the application scenario of this application can be extended to a more extreme case, that is, the entire original signal can be treated as the extracted sub-signals and subjected to the same analysis and calculation process described above, thereby obtaining more accurate signal parameter estimates. For example, such raw signals include intermediate frequency signals generated by mixing transmitted and received waves in FMCW (Frequency Modulated Continuous Wave) or CTFM (Continuous Transmission Frequency Modulation) radar or sonar.

[0094] More specifically, when the original signal is an intermediate frequency (IF) signal generated by FMCW, CTFM radar, or sonar, the frequency-phase relationship of this IF signal is as follows:

[0095] Where κ = f0 / B, f0 and B are the initial frequency and effective bandwidth of the FMCW or CTFM signal, respectively, and T is the sampling time length of the intermediate frequency signal. This is the phase jump caused by the reflection of the FMCW or CTFM signal on the object's surface. In this case, Equation 13 mentioned above can be further simplified to the following formula:

[0096] Another aspect of this application, referring to FIG5, also proposes a signal parameter generation device 40, which includes a signal receiving end 41, a processing module 42, and a signal output end 43. The signal receiving end 41 is configured to receive a raw signal; the processing module 42 is configured to generate signal parameters of the raw signal based on the raw signal using the signal parameter generation method proposed in any embodiment of this application, wherein the signal parameters include one or more of amplitude parameters, phase parameters, frequency parameters, and damping coefficients. The signal output end 43 is configured to output the signal parameters of the raw signal.

[0097] Another aspect of this application proposes a sensing device that may include radar and sonar devices. The radar / sonar device includes the signal parameter generation apparatus proposed in this application, such as the signal parameter generation apparatus 40 shown in Figure 5. Specifically, the radar device includes a lidar device, a millimeter-wave radar device, or an ultrasonic radar device. In such application scenarios, since it is usually necessary to estimate parameters such as frequency to obtain the estimated distance value, the more accurate the frequency estimation, the more accurate the estimated distance value. By adopting the solution of this application, the accuracy of the estimated signal parameters in the original signal can be significantly improved. Therefore, the distance estimation value for radar, sonar, and other devices can achieve micrometer-level accuracy, resulting in a significant performance improvement.

[0098] Another aspect of this application proposes a signal parameter generation system, comprising: a memory for storing instructions executable by a processor; and a processor for executing the instructions to implement the signal parameter generation method proposed in any embodiment of this application. Specifically, the signal parameter generation system is, for example, the signal parameter generation system 50 shown in FIG6. According to FIG6, the signal parameter generation system 50 may include an internal communication bus 51, a processor 52, a read-only memory (ROM) 53, a random access memory (RAM) 54, and a communication port 55. When applied to a personal computer, the signal parameter generation system 50 may also include a hard disk 56.

[0099] The internal communication bus 51 enables data communication between components of the signal parameter generation system 50. The processor 52 can perform calculations, make judgments, and issue prompts. In some embodiments, the processor 52 may consist of one or more processors. The communication port 55 enables data communication between the signal parameter generation system 50 and external systems. In some embodiments, the signal parameter generation system 50 can send and receive information and data from a network via the communication port 55.

[0100] The signal parameter generation system 50 may also include different types of program storage units and data storage units, such as a hard disk 56, a read-only memory (ROM) 53, and a random access memory (RAM) 54, capable of storing various data files used for computer processing and / or communication, as well as possible program instructions executed by the processor 52. The processor executes these instructions to implement the main part of the method. The results of the processor processing are transmitted to the user equipment through a communication port and displayed on the user interface.

[0101] In addition, this application also proposes a computer-readable medium storing computer program code that implements the above-described signal parameter generation method when executed by a processor.

[0102] The basic concepts have been described above. Obviously, for those skilled in the art, the above disclosure is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore remain within the spirit and scope of the exemplary embodiments of this application.

[0103] Furthermore, this application uses specific terms to describe embodiments of the application. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of the application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.

[0104] Some aspects of this application can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The aforementioned hardware or software may be referred to as a "data block," "module," "engine," "unit," "component," or "system." The processor may be one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. Furthermore, aspects of this application may manifest as computer products residing in one or more computer-readable media, including computer-readable program code. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic tapes, etc.), optical discs (e.g., compressed CDs, digital multifunction DVDs, etc.), smart cards, and flash memory devices (e.g., cards, sticks, key drives, etc.).

[0105] A computer-readable medium may contain a propagated data signal containing computer program code, for example, on baseband or as part of a carrier wave. This propagated signal may take various forms, including electromagnetic, optical, and so on, or suitable combinations thereof. A computer-readable medium can be any computer-readable medium other than a computer-readable storage medium, which can be connected to an instruction execution system, apparatus, or device to enable communication, propagation, or transmission of a program for use. The program code located on the computer-readable medium can be propagated through any suitable medium, including radio, cable, fiber optic cable, radio frequency signals, or similar media, or any combination of the above media.

[0106] Similarly, it should be noted that, in order to simplify the description of the present application and thus aid in the understanding of one or more embodiments, the foregoing description of the embodiments of the present application sometimes combines multiple features into a single embodiment, drawing, or description thereof. However, this disclosure method does not imply that the subject matter of the present application requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of the single embodiments disclosed above.

[0107] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of scope in some embodiments of this application are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0108] Although this application has been described with reference to specific embodiments, those skilled in the art should recognize that the above embodiments are only used to illustrate this application, and various equivalent changes or substitutions can be made without departing from the spirit of this application. Therefore, any changes or modifications to the above embodiments within the essential spirit of this application will fall within the scope of the claims of this application.

Claims

1. A method for generating signal parameters, characterized in that, Includes the following steps: Input the original signal, which is an R-dimensional signal containing M frequency components, where M and R are both greater than or equal to 1; I sub-signals are extracted from the original signal, where I is greater than or equal to 1; Construct multiple equations for the I sub-signals and solve the multiple equations to obtain the signal parameters of the original signal. The signal parameters include one or more of the amplitude parameter, phase parameter, frequency parameter, and damping coefficient.

2. The method as described in claim 1, characterized in that, Also includes: Obtain the frequency domain value and peak point coordinates corresponding to one or more peaks in the spectrum of each sub-signal; The frequency domain values ​​and peak point coordinates are included in the equation.

3. The method as described in claim 2, characterized in that, Obtaining the frequency domain value and peak coordinates corresponding to one or more peaks of the sub-signal spectrum for each sub-signal includes: Perform Fourier transform, zero-padding Fourier transform, interpolated Fourier transform, or CZT transform on the original signal, and obtain the frequency domain value and peak coordinates corresponding to one or more peaks in the spectrum of the original signal. Calculate the frequency domain value and peak coordinates corresponding to one or more peaks of the sub-signal spectrum for each sub-signal.

4. The method of claim 2, wherein, Obtaining the frequency domain value and peak coordinates corresponding to one or more peaks of the sub-signal spectrum for each sub-signal includes: Perform Discrete Fourier Transform, Zero-padding Fourier Transform, Interpolated Fourier Transform, or CZT Transform on the first part of the I sub-signals, and obtain the frequency domain value and peak point coordinates corresponding to one or more peaks in the spectrum of the sub-signal corresponding to the first part of the sub-signals. Calculate the frequency domain value and peak coordinates of one or more peaks in the spectrum of the second part of the sub-signals among the I sub-signals.

5. The method according to any one of claims 2 to 4, wherein, The frequency domain value is the DFT value.

6. The method as described in claim 1, characterized in that, The sub-signals comprise where i = 1,..., I, r = 1,..., R, is the length of the ith sub-signal in the rth dimension.

7. The method as described in claim 6, characterized in that: The original signal comprises s(n1,...,n R ) : And: where F r and N r are the sampling frequency and signal length in the rth dimension, respectively, A m and are the amplitude parameter and the initial phase of the original signal of the mth frequency component of the original signal, respectively, f m,r and β m,r are the frequency parameter and the damping coefficient of the mth frequency component of the original signal in the rth dimension, respectively, η i is the down-sampling rate of the i-th sub-signal; and These are the amplitude parameter and initial phase of the m-th frequency component of the i-th sub-signal, respectively. Let be the index of the initial point of the i-th sub-signal; It is the discrete Fourier transform frequency of the m-th frequency component of the i-th sub-signal in the r-th dimension, where Defined as 8. The method as described in claim 7, characterized in that, Suppose that the peak point of the p-th frequency component of the i-th sub-signal in the r-th dimension is at... The DFT of the i-th sub-signal is at point The value is written as in, 9. The method as described in claim 8, characterized in that, This also includes formulas Applying this to all peak points of the spectrum corresponding to the I sub-signals, we obtain 2M*I equations as follows: in, W=diag{W 1 ,IN 2 ,…,IN I } in, 10. The method according to any one of claims 1-4, characterized in that, When the equation is a nonlinear equation, the method further includes: Calculate the initial values ​​of the signal parameters.

11. The method as described in claim 10, characterized in that, The steps for solving the equation include using the Levenberg-Marquardt, Newton-Raphson, or Gaussian-Newton algorithms.

12. The method according to any one of claims 1-4, characterized in that, In the step of extracting I sub-signals from the original signal, the number I of the extracted sub-signals satisfies the following condition: I ≥ R + 1.

13. The method according to any one of claims 1 to 4, characterized in that, If the damping coefficient is not included in the signal parameters of the original signal, then in the step of extracting I sub-signals from the original signal, the number of sub-signals I extracted satisfies the following condition: I≥ceil(R / 2)+1.

14. The method according to any one of claims 1 to 4, characterized in that, If the original signal is a periodic signal known from a mathematical model, the method further includes setting the value of M to 1.

15. The method according to any one of claims 1 to 4, characterized in that, If some parameters of the original signal have interrelated calculation relationships, the method further includes the step of extracting I sub-signals from the original signal, wherein the minimum value of the number I of the extracted sub-signals is set to 1 or the sub-signals are equivalent to the original signal.

16. The method as described in claim 15, characterized in that, In the signal parameters of the original signal, the frequency parameter and the phase have a mutually related calculation relationship, and the damping coefficient is 0 or less than the damping coefficient threshold.

17. The method as described in claim 1 or 16, characterized in that, The original signal includes an intermediate frequency signal generated by mixing an FMCW signal or a CTFM signal.

18. The method as described in claim 17, characterized in that, When the original signal is an intermediate frequency (IF) signal generated by mixing the FMCW or CTFM signal, the frequency-phase relationship of the IF signal is as follows: Where κ = f0 / B, f0 and B are the initial frequency and effective bandwidth of the FMCW or CTFM signal, respectively, and T is the sampling time length of the intermediate frequency signal. The phase jump is caused by the reflection of the FMCW or CTFM signal on the object surface, and the equation includes: in 19. A signal parameter generation device, characterized in that, include: The signal receiver is configured to receive the raw signal. The processing module is configured to generate signal parameters of the original signal based on the original signal using the method described in any one of claims 1 to 18, wherein the signal parameters include one or more of amplitude parameters, phase parameters, frequency parameters, and damping coefficients; and The signal output terminal is configured to output the signal parameters of the original signal.

20. A sensing device, characterized in that, The sensing device includes the signal parameter generation apparatus as described in claim 19.

21. The sensing device as described in claim 20, characterized in that, The sensing devices include radar devices or sonar devices.

22. The sensing device as described in claim 21, characterized in that, The radar equipment includes lidar equipment, millimeter-wave radar equipment, or ultrasonic radar equipment.

23. A signal parameter generation system, comprising: Memory is used to store instructions that can be executed by the processor; and a processor for executing the instructions to implement the method as claimed in any one of claims 1-18.

24. A computer-readable medium storing computer program code that, when executed by a processor, implements the method as claimed in any one of claims 1-18.

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