A method and system for estimating signal modulation parameters

Abstract

The application provides a signal modulation parameter estimation method, comprising: dividing a modulation signal into two equivalent to-be-detected signals, and inputting the two to-be-detected signals into a main sampling channel and a feedback sampling channel respectively; performing main channel sampling on the to-be-detected signal input into the main sampling channel to obtain a sample group, performing main channel parameter estimation based on the sample group to obtain an estimation value of an interrupt point position and an estimation value of an amplitude factor of the to-be-detected signal, and obtaining an amplitude estimation value of the to-be-detected signal based on the amplitude factor estimation value; constructing a feedback signal based on the interrupt point position estimation value and the amplitude estimation value, and inputting the feedback signal into the feedback sampling channel; performing frequency mixing on the to-be-detected signal input into the feedback sampling channel and the feedback signal to obtain a carrier signal of the to-be-detected signal, performing direct sampling and delay sampling on the carrier signal to obtain an undelayed sample group and a delayed sample group respectively, and performing feedback channel parameter estimation based on the undelayed sample group and the delayed sample group to obtain a frequency modulation rate estimation value and an initial carrier frequency estimation value of the to-be-detected signal.

Description

Technical Field

[0001] This invention belongs to the field of signal processing technology, and more specifically relates to a method and system for estimating signal modulation parameters. Background Technology

[0002] In the field of communications, signal modulation typically involves adjusting and setting parameters such as waveform, frequency, phase, and amplitude. Different adjustment methods can be used to achieve various communication objectives, and the widespread application of modulation technology has brought convenience to people's lives. The development of modulated signals has mainly gone through four stages: from frequency modulation to amplitude modulation, then to phase modulation, and finally to digital modulation. With the continuous development of communication technology, composite modulation signals have also been widely used in the field. These signals combine two or more different modulation methods to form a new modulation scheme. The change in modulation methods is mainly aimed at improving communication efficiency and ensuring signal quality. Composite modulation signals have brought faster and more reliable transmission methods to the communication field, increasing data transmission rates and spectrum utilization, effectively promoting the development of communication technology.

[0003] Determining the modulation parameters of a signal is crucial for improving the transmission efficiency, anti-interference capability, and resistance to multipath fading in communication systems. Signal sampling plays a vital role in estimating these modulation parameters. Sampling requires converting continuous-time signals into discrete-time signals, which necessitates converting the signal into a digital signal. This process can introduce quantization errors, which may cause deviations or increase the overall estimation error of the modulation parameters. The sampling results directly impact the estimation of modulation parameters. For example, insufficient sampling rate can lead to aliasing, resulting in incorrect estimations. Jitter and noise during sampling can also affect the accuracy of the estimation results. Therefore, when estimating modulation parameters, it is essential to fully consider the influence of sampling techniques and adopt appropriate sampling methods to minimize errors.

[0004] ASK-LFM composite modulation signal is a novel composite modulation method that combines amplitude modulation (ASK) and linear frequency modulation (LFM). It boasts advantages such as high precision, strong resistance to multipath interference, and high bandwidth utilization, making it widely used in radar and communication fields. The main sampling methods for ASK-LFM composite modulation signals are Nyquist sampling and under-Nyquist sampling. ASK-LFM composite modulation signals have a relatively large bandwidth. If traditional Nyquist sampling is applied directly to the original signal, the sampling rate needs to be greater than or equal to twice the original bandwidth to ensure accurate parameter estimation. This method generates a considerable amount of data, placing a heavy burden on the processor and storage devices. If under-Nyquist sampling is applied directly to the original signal, the periodicity of the trigonometric function can cause frequency ambiguity in the samples, affecting the estimation of the modulation parameters of the signal under test. Even if the original signal is pre-processed and a low signal-to-noise ratio is maintained before performing under-Nyquist sampling, problems of low sampling efficiency and low estimation accuracy still exist.

[0005] This shows that there are still problems in the estimation methods and system settings for signal modulation parameters, such as low sampling and detection efficiency, low parameter estimation accuracy, and the need to optimize the parameter estimation strategy. Summary of the Invention

[0006] Based on the aforementioned shortcomings and deficiencies in the prior art, one of the objectives of this invention is to at least solve one or more of the aforementioned problems in the prior art. In other words, one of the objectives of this invention is to provide a method and system for estimating signal modulation parameters that meets one or more of the aforementioned requirements.

[0007] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0008] In a first aspect, the present invention provides a method for estimating signal modulation parameters, comprising the steps of:

[0009] S1. Divide the modulated signal into two equivalent signals to be tested, and input the two equivalent signals to be tested into the main sampling channel and the feedback sampling channel respectively.

[0010] S2. The signal to be tested input to the main sampling channel is sampled by the main channel to obtain a sample group. The main channel parameters are estimated based on the sample group to obtain the estimated value of the discontinuity position and the estimated value of the amplitude factor of the signal to be tested. The amplitude estimated value of the signal to be tested is obtained based on the estimated value of the amplitude factor.

[0011] S3. Construct a feedback signal based on the estimated location and amplitude of the discontinuity point, and input the feedback signal into the feedback sampling channel;

[0012] S4. Mix the signal under test and the feedback signal in the input feedback sampling channel to obtain the carrier signal of the signal under test. Perform direct sampling and delayed sampling on the carrier signal to obtain the undelayed sample group and the delayed sample group, respectively. Based on the undelayed sample group and the delayed sample group, perform feedback channel parameter estimation to obtain the frequency modulation estimate and the initial carrier frequency estimate of the signal under test.

[0013] The above technical solution includes a main sampling channel and a feedback sampling channel for estimating signal modulation parameters. First, the signal under test is sampled in the main sampling channel to obtain a sample set containing multiple discrete samples. Based on this sample set, some parameters of the signal under test are estimated, and a feedback signal is constructed based on these estimates. Sampling is then performed again in the feedback signal channel, with time-interleaved sampling to obtain both undelayed and delayed sample sets. Finally, other parameters of the signal under test are estimated based on these undelayed and delayed sample sets. The feedback channel enhances signal strength and improves signal capture rate.

[0014] As a preferred embodiment, step S2 includes the following steps before sampling the signal under test in the input main sampling channel:

[0015] S21. Take the conjugate of the signal to be tested to obtain the complex conjugate signal of the signal to be tested, and demodulate the signal to be tested and the complex conjugate signal to obtain the baseband signal of the signal to be tested.

[0016] The above technical solution allows for the extraction of the conjugate of the signal under test, and the recovery of the original baseband signal, i.e., the DC component and the frequency component with zero center, based on the signal under test itself and its conjugate signal. This enables better signal processing and demodulation.

[0017] As a preferred embodiment, step S2, following step S21, further includes the following step:

[0018] S22. Filter the baseband signal, wherein the filtering bandwidth setting satisfies... Where BLPF represents the filter bandwidth, K represents the number of amplitude step segments of the baseband signal, and T represents the duration of the baseband signal.

[0019] By using the above technical solutions, filtering the baseband signal before sampling can suppress anti-aliasing in-band noise and aliasing errors, and can also help reduce high-frequency noise and interference in the sampled signal, improve the accuracy of the sampled signal, and thus ensure the accuracy of parameter estimation.

[0020] As a preferred embodiment, the number of samples in the sample group in step S2 satisfies Where T represents the duration of the baseband signal. This indicates the number of samples in the sample group. Indicates the sampling interval of the main channel. This indicates the sampling frequency of the main channel.

[0021] By using the above technical solutions, setting a reasonable number of samples can ensure the accuracy of signal reconstruction and reduce the computational complexity of the system.

[0022] As a preferred embodiment, the sampling rates of both the undelayed sample group and the delayed sample group in step S4 satisfy the following conditions: Where B represents the bandwidth of the carrier signal, Te represents the duration of the delayed carrier signal, T represents the duration of the undelayed carrier signal, and fs represents the sampling frequency of the feedback channel.

[0023] By using the above technical solutions, setting a reasonable sampling rate can reduce the occurrence of frequency ambiguity.

[0024] As a preferred embodiment, the delay setting for delay sampling of the carrier signal in step S4 satisfies... Where Te represents the duration of the delayed carrier signal, T represents the duration of the undelayed carrier signal, fs represents the sampling frequency of the feedback channel, and B represents the bandwidth of the carrier signal.

[0025] By using the above technical solutions, setting a reasonable delay can reduce the occurrence of frequency ambiguity.

[0026] As a preferred embodiment, the number of sample groups in both the undelayed sample group and the delayed sample group in step S4 satisfies T = NT. s Where T represents the duration of the undelayed carrier signal, N represents the number of sample groups in the undelayed sample group and the delayed sample group, and Ts represents the duration of the delayed carrier signal.

[0027] By using the above technical solutions, setting a reasonable number of samples can ensure the accuracy of signal reconstruction and reduce the computational complexity of the system.

[0028] In a second aspect, the present invention also provides a signal modulation parameter estimation system, based on a modulation signal parameter estimation method of any of the above schemes, comprising a processing module, a signal transmission module, a sampling module, and a parameter estimation module connected in sequence;

[0029] The processing module is used to divide the modulated signal into two equivalent signals to be tested.

[0030] The signal transmission module is used to input two equivalent signals to be tested into the main sampling channel and the feedback sampling channel, respectively.

[0031] The sampling module is used to sample the signal to be tested from the input main sampling channel to obtain a sample group.

[0032] The parameter estimation module performs main channel parameter estimation based on the sample group to obtain the estimated values ​​of the discontinuity positions and amplitude factors of the signal under test, and obtains the amplitude estimate of the signal under test based on the amplitude factor estimate.

[0033] The processing module constructs a feedback signal based on the estimated location and amplitude of the discontinuity point;

[0034] The signal transmission module is also used to input the feedback signal into the feedback sampling channel;

[0035] The processing module is also used to mix the signal under test and the feedback signal in the input feedback sampling channel to obtain the carrier signal of the signal under test;

[0036] The sampling module is also used to perform direct sampling and delayed sampling on the carrier signal to obtain an undelayed sample group and a delayed sample group, respectively.

[0037] The parameter estimation module also performs feedback channel parameter estimation based on the undelayed sample group and the delayed sample group to obtain the frequency modulation estimate and the initial carrier frequency estimate of the signal under test.

[0038] As a preferred embodiment, the processing module is used to take the conjugate of the signal under test to obtain the complex conjugate signal of the signal under test, and to demodulate the signal under test and the complex conjugate signal to obtain the baseband signal of the signal under test.

[0039] As a preferred embodiment, the processing module is used to filter the baseband signal.

[0040] Compared with the prior art, the present invention has the following advantages:

[0041] The estimation method and system of the present invention achieve accurate estimation of ASK-LFM composite modulation signal parameters with a small number of samples. The filtering of the signal and the setting of a reasonable sampling rate reduce the occurrence of frequency ambiguity, and the setting of a reasonable sample size reduces the pressure on the processing equipment and data storage equipment.

[0042] Further or more detailed beneficial effects will be described in conjunction with specific embodiments in the detailed implementation. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart of a signal modulation parameter estimation method according to the present invention.

[0045] Figure 2 This is a schematic diagram illustrating a specific implementation of the signal modulation parameter estimation method described in this invention.

[0046] Figure 3 This is a performance diagram of the estimated location of discontinuities under experimental noise conditions according to an embodiment of the present invention.

[0047] Figure 4 This is a graph showing the estimated amplitude value under experimental noise conditions according to an embodiment of the present invention.

[0048] Figure 5 This is an estimated performance diagram of the modulated frequency under experimental noise conditions according to an embodiment of the present invention.

[0049] Figure 6 This is a performance diagram of the estimated initial carrier frequency under experimental noise conditions according to an embodiment of the present invention.

[0050] Figure 7 This is a schematic diagram of a signal modulation parameter estimation system according to the present invention. Detailed Implementation

[0051] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0052] In the following description, several embodiments of this application are provided. Different embodiments can be substituted or combined. Therefore, this application can also be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then this application should also be considered to include embodiments containing one or more other possible combinations of A, B, C, and D, even if such embodiments are not explicitly described in the following text.

[0053] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of this application. Various processes or components may be appropriately omitted, substituted, or added to the examples. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.

[0054] To facilitate a better understanding of the embodiments of this application, the application scenarios will be explained before providing a detailed explanation of the specific implementation methods.

[0055] Example 1:

[0056] like Figure 1-2 As shown in the figure, this embodiment provides a method for estimating signal modulation parameters. The specific implementation of this method is as follows:

[0057] The modulated signal is input to the power divider, which divides it into two equivalent test signals x(t). The two equivalent test signals are then input to the main sampling channel and the feedback sampling channel, respectively.

[0058] The signal to be measured, x(t):

[0059]

[0060] Where the time variable of x(t) is t∈[0,T);T(T>0, Let x(t) be the time length; the number of amplitude step segments of the signal is K (K≥1, );t k (k=1,…,K+1) are the locations of discontinuities, satisfying 0≤t1<t2<…<t K+1 <T; u(t) is the unit step function, ξ k (t)=u(tt k )-u(tt k+1 () represents a unit rectangle in the time domain; the initial carrier frequency is f. c (f c >0, ); Frequency modulation μ (μ>0, ), and the bandwidth B of x(t) (B>0, The relationship between ) and time length T satisfies A k ∈{±1, ±3, …, ±(P-1)} represents the amplitude value of ASK modulation, and P The modulation order of ASK is given by P=4, i.e., when the modulation mode is 4ASK, A... k ∈{±1,±3}; Let x(t) be the initial phase.

[0061] To obtain the complex conjugate signal x(t) of the signal to be measured, take the conjugate of x(t). * (t), and combine x(t) with x * Multiplying (t) yields the baseband signal y(t) after removing the modulated carrier.

[0062] The specific calculations are as follows:

[0063]

[0064] Where t∈[0,T) are the time variables of the signal to be measured x(t) and the baseband signal y(t); T(T>0, ) represents the duration of the signal to be measured, x(t), and the baseband signal, y(t); K (K≥1, ) represents the number of amplitude step segments; t k (k=1,…,K+1) are the locations of discontinuities, satisfying 0≤t1<t2<…<t K+1 <T; u(t) is the unit step function, ξ k (t)=u(tt k )-u(tt k+1 () represents a unit rectangle in the time domain; P is the square of the amplitude value of the ASK modulation. Let P be the modulation order of ASK. When P = 4, i.e., the modulation mode is selected as 4ASK, Let x(t) be the initial phase.

[0065] The baseband signal is fed into an LPF for filtering to obtain the signal y(t). The filtering bandwidth is set to satisfy... Among them, B LPF The filter bandwidth is represented by K, the amplitude step number of the baseband signal is represented by T, and the duration of the baseband signal is represented by T.

[0066] The signal after LPF filtering Sampling is performed, but undersampling can cause spectral aliasing. To avoid this problem, the sampling rate is... Need to meet After undersampling, a set of discrete under-Nyquist sampled samples is obtained.

[0067]

[0068] Among them, the Nyquist sample Number of samples satisfy T represents the duration of the baseband signal. This indicates the number of samples in the sample group. Indicates the sampling interval of the main channel. This indicates the sampling frequency of the main channel.

[0069] Perform a DFT on the sampled data to obtain the sample. Fourier coefficients Y[m]:

[0070]

[0071] Among them, through m pairs Fourier coefficients Indexing is performed, where M is the maximum absolute value of the index value m, so the sample Fourier coefficients The total number is 2M+1.

[0072] sample Fourier coefficients Baseband signal before under-Nyquist sampling and after LPF filtering The following relationship exists between them:

[0073]

[0074] To simplify and transform the above expression, we need to define a first-order polynomial:

[0075]

[0076] Here, m is used to index the first-order polynomial Q[m], M is the maximum absolute value of the index value m, and the T parameter in the polynomial is consistent with the T of the signal x(t) to be measured in this invention, that is, it is consistent with the sample. Fourier coefficients The T in the text is consistent.

[0077] Multinomial factors and Multiplying them together, we get the following product:

[0078]

[0079] in, The final expression is obtained by summing K+1 components. For each component, there is an amplitude factor D. k and a complex exponential factor Multiplying them together yields the amplitude factor D. k satisfy:

[0080]

[0081] and

[0082] according to The final expression is used to construct a null filter and solve for the estimated location of the discontinuity of the measured signal x(t). and the estimated value of the amplitude factor

[0083] Furthermore, having already obtained the amplitude factor estimate... Based on this, solve for the amplitude factor D. k The expression yields the amplitude estimate of the signal x(t) to be measured.

[0084] Based on the estimated location of the discontinuity obtained from the above steps and magnitude estimate A feedback signal p(t) is constructed via a feedback signal controller. Furthermore, due to the low distortion and high accuracy of the parameter estimation method in this approach, the estimated location of the discontinuity of the measured signal x(t) is assumed to be... and magnitude estimate The original values ​​of the discontinuity locations of the signal x(t) to be measured are respectively... and amplitude original value If they are approximately equal, then a feedback signal p(t) can be constructed via a feedback signal controller:

[0085]

[0086] The constructed feedback signal p(t) is multiplied by the signal to be measured x(t) that enters the feedback sampling channel via the power divider to obtain the carrier signal z(t) of the signal to be measured x(t):

[0087]

[0088] Time-interleaved sampling is performed on the carrier signal z(t) of the signal to be measured x(t), that is, the carrier signal z(t) is undersampled at a rate of 10 ... Undersampling and undersampling rate Delay is T e Delayed under-Nyquist sampling yields undelayed under-Nyquist sample z[n] and delayed under-Nyquist sample z[n]. e [n]

[0089]

[0090]

[0091] Undelayed sample z[n] and delayed sample z e [n] has the same sampling rate, both equal to The sample sizes are the same, and both satisfy T = NT. s Where T represents the duration of the undelayed carrier signal, N represents the number of sample groups in the undelayed sample group and the delayed sample group, and Ts represents the duration of the delayed carrier signal.

[0092] Taking the conjugate of the undelayed sample z[n], we obtain the conjugate z of the undelayed sample. * [n], and the delayed sample z e [n] and the conjugate z of the undelayed sample * Multiplying [n] together yields the discrete sample z1[n], which is then further simplified and combined into the following form:

[0093]

[0094] in,

[0095] z1[n] is solved using the ESPRIT algorithm. This allows us to further solve for the estimated frequency modulation value of the measured signal x(t).

[0096]

[0097] Because trigonometric functions have periodic properties, discrete sample z1[n] is solved using the ESPRIT algorithm. The u obtained from this spectral estimation process is uncertain; its value is equal to the principal argument of u plus an integer multiple of 2π, thus introducing frequency ambiguity. To avoid frequency ambiguity, it is necessary to ensure that the undersampling rate meets the required standard. Delayed gratification Where B represents the bandwidth of the carrier signal, Te represents the duration of the delayed carrier signal, T represents the duration of the undelayed carrier signal, and fs represents the sampling frequency of the feedback channel.

[0098] The obtained frequency modulation estimate of the measured signal x(t) Define two discrete signals as d[n] and d[n] e [n]:

[0099]

[0100] Wherein, the discrete signal d[n] does not contain a delay component, d e [n] includes the delay T e Discrete signals d[n] and d e [n] is related to z[n] and z respectively. e Multiplying [n] together yields two new discrete signals z2[n] and z2[n]. 2e[n]. Similarly, the discrete signal z2[n] does not contain a delay component, z 2e [n] includes the delay T e .

[0101] Given discrete signals z2[n] and z 2e [n] Construct two sets of vectors of length N: z2 = [z[0], z[1], ..., z[N-1]] and z 2e =[z 2e [0],z 2e [1],…,z 2e [N-1]

[0102]

[0103] Taking the conjugate of vector z2 yields With vector z 2e Multiplying by their conjugates, we get Z:

[0104]

[0105] Furthermore, the initial carrier frequency estimate of the signal to be measured, x(t), is obtained by solving Z.

[0106]

[0107] To verify this method, the following experiment was set up:

[0108] Experiment 1 was specifically set up as follows:

[0109] Signal duration T = 25 μs, discontinuity location Amplitude value Initial carrier frequency f c =40MHz, signal modulation frequency μ = 1e14Hz / s. In the main sampling channel, the filter bandwidth B LPF =20MHz, sampling rate In the feedback sampling channel, the sampling rate f s =2MHz, delay T e =10ns. The parameter estimation results of the ASK-LFM composite modulation signal under noise-free conditions are shown in Table 1.

[0110] Table 1

[0111]

[0112] By comparing the true and estimated values ​​of each parameter, it can be seen that this method can accurately recover the parameters of the signal under test when there is no noise.

[0113] Experiment 2 is specifically set up as follows:

[0114] Signal duration T = 25 μs, discontinuity location parameters Amplitude parameter of the modulated signal to be measured The initial carrier frequency is f c =40MHz, modulation frequency μ = 1e14Hz / s. In the main sampling channel, the filter bandwidth B LPF =20MHz, sampling rate In the feedback sampling channel, the sampling rate f s =2MHz, delay T e =10ns. The noise environment is set to Gaussian white noise, and the signal under test is superimposed with Gaussian white noise. We define the expression for signal-to-noise ratio (SNR) as:

[0115]

[0116] Among them, P signal P represents the average power of the signal under test. noise This represents the average power of the environmental noise. The signal-to-noise ratio (SNR) is taken as [-10:5:70] dB. The normalized mean square error is chosen as the performance metric for estimation. If the experiment is repeated num times, then regarding t... k The NMSE is defined as follows:

[0117]

[0118] Where K (K≥1, ) represents the number of amplitude step segments; t k (k = 1, ..., K+1) represents the original values ​​of the discontinuity locations. This is an estimate of the location of discontinuities obtained by the sampling system in a noisy environment. The system is set to run num = 1000 times.

[0119] Figure 3 This study demonstrates the system's ability to estimate discontinuity locations under Gaussian white noise conditions. Analysis of the experimental results shows that at low signal-to-noise ratios (SNR) of -10 dB, the normalized mean square error (MSE) of the discontinuity location estimate is less than -20 dB. This error decreases as the SNR increases, eventually leveling off and stabilizing around -90 dB. As the first parameter of the undersampling and parameter estimation system designed in this invention is estimated, and subsequent parameter estimates are influenced by it, the performance of the discontinuity location parameter estimation has a significant impact on the overall system estimation performance.

[0120] from Figure 3 The results show that the undersampling and parameter estimation system designed in this invention has superior performance in estimating the discontinuity location parameter, with extremely high accuracy and anti-interference ability, which is beneficial to the performance improvement of subsequent parameter estimation.

[0121] Figure 4 The experiment demonstrates the system's ability to estimate amplitude under Gaussian white noise conditions. Analysis of the experimental results shows that at low signal-to-noise ratios (SNR) of -10 dB, the normalized mean square error (MSE) of the amplitude estimate is around -30 dB, decreasing as the SNR increases. At SNR of 70 dB, the MSE of the amplitude estimate is below -110 dB.

[0122] Figure 5 This demonstrates the system's ability to estimate frequency modulation (FM) under Gaussian white noise conditions. Analysis of the experimental results shows that at low signal-to-noise ratios (SNR) of -10 dB, the normalized mean square error (MSE) of the FM estimate is around 20 dB. Within the SNR range of [-10:10] dB, the MSE of the FM estimate decreases rapidly. After 10 dB, the MSE decreases further with increasing SNR, eventually dropping below -120 dB.

[0123] Figure 6 This study demonstrates the system's ability to estimate the initial carrier frequency under Gaussian white noise conditions. Since the invention employs a process of using the estimated modulation frequency (MFM) to demodulate the linear frequency modulation (LFM) to estimate the initial carrier frequency, the estimation performance of the initial carrier frequency is affected by the MFM estimation performance. Analysis of the experimental results shows that at low signal-to-noise ratios (SNR), when SNR = -10 dB, the normalized mean square error (MSE) of the initial carrier frequency estimate is around 0 dB. Within the SNR range of [-10:10] dB, the MSE of the initial carrier frequency estimate decreases rapidly. After 10 dB, the MSE of the initial carrier frequency estimate decreases with increasing SNR, eventually dropping below -90 dB.

[0124] The experimental results above show that, under noise-free conditions, the method of the present invention can accurately recover the parameters of the signal under test; under noisy conditions, the method of the present invention improves the parameter estimation performance of the signal under test and enhances the robustness of the system.

[0125] Example 2:

[0126] like Figure 7 As shown, this embodiment provides a signal modulation parameter estimation system based on any of the above-mentioned modulation signal parameter estimation methods, including a processing module, a signal transmission module, a sampling module, and a parameter estimation module connected in sequence;

[0127] The processing module is used to divide the modulated signal into two equivalent signals to be tested.

[0128] The signal transmission module is used to input two equivalent signals to be tested into the main sampling channel and the feedback sampling channel, respectively.

[0129] The sampling module is used to sample the signal to be tested from the input main sampling channel to obtain a sample group.

[0130] The parameter estimation module performs main channel parameter estimation based on the sample group to obtain the estimated values ​​of the discontinuity positions and amplitude factors of the signal under test, and obtains the amplitude estimate of the signal under test based on the amplitude factor estimate.

[0131] The processing module constructs a feedback signal based on the estimated location and amplitude of the discontinuity point;

[0132] The signal transmission module is also used to input the feedback signal into the feedback sampling channel;

[0133] The processing module is also used to mix the signal under test and the feedback signal in the input feedback sampling channel to obtain the carrier signal of the signal under test;

[0134] The sampling module is also used to perform direct sampling and delayed sampling on the carrier signal to obtain an undelayed sample group and a delayed sample group, respectively.

[0135] The parameter estimation module also performs feedback channel parameter estimation based on the undelayed sample group and the delayed sample group to obtain the frequency modulation estimate and the initial carrier frequency estimate of the signal under test.

[0136] Specifically, this embodiment provides a preferred implementation, wherein the processing module is used to take the conjugate of the signal under test to obtain the complex conjugate signal of the signal under test, and to demodulate the signal under test and the complex conjugate signal to obtain the baseband signal of the signal under test.

[0137] Specifically, this embodiment provides a preferred implementation, wherein the processing module is used to filter the baseband signal.

[0138] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0139] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0140] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of embodiments of this disclosure upon considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method of estimating a signal modulation parameter, characterized by, The method comprises the steps of: S1, dividing the modulated signal into two equivalent to-be-measured signals, and inputting the two equivalent to-be-measured signals into a main sampling channel and a feedback sampling channel respectively; S2, performing main channel sampling on the to-be-measured signal input into the main sampling channel to obtain a sample group, performing main channel parameter estimation based on the sample group to obtain an estimated value of the discontinuity position of the to-be-measured signal and an estimated value of the amplitude factor, and obtaining an estimated value of the amplitude of the to-be-measured signal based on the estimated value of the amplitude factor; S3, constructing a feedback signal based on the estimated value of the discontinuity position and the estimated value of the amplitude, and inputting the feedback signal into the feedback sampling channel; S4, mixing the to-be-tested signal and the feedback signal of the input feedback sampling channel to obtain a carrier signal of the to-be-tested signal, directly sampling and delay sampling the carrier signal to obtain an undelayed sample group Z[n] and a delay sample group Z e [n], respectively, performing feedback channel parameter estimation based on the undelayed sample group and the delay sample group to obtain a frequency modulation rate estimation value and an initial carrier frequency estimation value of the to-be-tested signal; The feedback channel parameter estimation is performed based on the non-delayed sample set Z[n] and the delayed sample set Z e [n] to obtain the frequency modulation rate estimate and the initial carrier frequency estimate of the signal under test includes: The conjugate of the non-delayed sample set Z[n] is taken to obtain the conjugate of the non-delayed sample Z*[n], and the delayed sample set Z e [n] is multiplied by the conjugate of the delayed sample Z*[n] to obtain the discrete sample Z1[n]. The discrete sample Z1[n] is solved by the ESPRIT algorithm, so that the estimated value of the frequency modulation of the to-be-measured signal can be further solved; two discrete signals d[n] and d e [n] are defined on the basis of the frequency modulation estimate value of the signal to be measured, wherein the discrete signal d[n] does not contain a delay portion, d e [n] contains a delay; The above two discrete signals are multiplied with the non-delayed sample set Z[n] and the delayed sample set Z[n] respectively, to obtain two new discrete signals Z2[n] and Z e [n], wherein Z2[n] does not contain the delay part, and Z 2e [n] contains the delay. 2e [n] contains the delay. from the discrete signals Z2[n] and Z 2e [n] two sets of vectors Z2 = [Z[0], Z[1],..., Z[N-1]] and Z 2e = [Z 2e [0], Z 2e [1],..., Z 2e [N-1]] of length N are constructed. Taking the conjugate of vector Z2 gives Z2 * Conjugate multiplication with vector Z 2e gives Z; Finally, the initial carrier frequency estimated value of the to-be-measured signal is solved by Z.

2. A method of estimating a signal modulation parameter according to claim 1, characterized by, Before performing main channel sampling on the to-be-measured signal input into the main sampling channel in step S2, the method comprises the step of: S21, taking a conjugate of the to-be-measured signal to obtain a complex conjugate signal of the to-be-measured signal, and demodulating the to-be-measured signal based on the to-be-measured signal and the complex conjugate signal to obtain a baseband signal of the to-be-measured signal.

3. A method of estimating a signal modulation parameter according to claim 2, wherein, After step S21 in step S2, the method further comprises the step of: S22, filtering processing is performed on the baseband signal, and a filtering bandwidth is set to satisfy wherein B LPF represents a filtering bandwidth, K represents a number of amplitude step sections of the baseband signal, and T represents a duration of the baseband signal.

4. The method of claim 1, wherein: The number of samples of the sample group in step S2 satisfies where T represents the duration of the baseband signal, represents the number of samples of the sample group, represents the sampling interval of the primary channel samples, represents the sampling frequency of the primary channel samples.

5. The method of claim 1, wherein: The sampling rates of the non-delayed sample group and the delayed sample group in step S4 both satisfy where B represents the bandwidth of the carrier signal, T e represents the duration of the delayed carrier signal, T represents the duration of the non-delayed carrier signal, f s represents the sampling frequency of the feedback channel samples.

6. The method of claim 1, wherein: The delay setting of the delay sampling on the carrier signal in step S4 satisfies where T e denotes the duration of the delayed carrier signal, T denotes the duration of the undelayed carrier signal, f s denotes the sampling frequency of the feedback channel sampling, B denotes the bandwidth of the carrier signal.

7. The method of claim 1, wherein: The number of sample groups of the non-delayed sample group and the delayed sample group in step S4 both satisfy T = NT s wherein T represents the duration of the non-delayed carrier signal, N represents the number of sample groups of the non-delayed sample group and the delayed sample group, T s represents the duration of the delayed carrier signal.

8. A system for estimating signal modulation parameters, the system being based on any one of the methods of claims 1-7, and the system comprising: a processing module, a signal transmission module, a sampling module, and a parameter estimation module connected in sequence. The processing module is configured to divide the modulated signal into two equivalent to-be-measured signals. The signal transmission module is configured to input the two equivalent to-be-measured signals into a main sampling channel and a feedback sampling channel respectively. The sampling module is configured to perform main channel sampling on the to-be-measured signal input into the main sampling channel to obtain a sample group. The parameter estimation module is configured to perform main channel parameter estimation based on the sample group to obtain an estimated value of the discontinuity position of the to-be-measured signal and an estimated value of the amplitude factor, and obtain an estimated value of the amplitude of the to-be-measured signal based on the estimated value of the amplitude factor. The processing module is configured to construct a feedback signal based on the estimated value of the discontinuity position and the estimated value of the amplitude. The signal transmission module is further configured to input the feedback signal into the feedback sampling channel. The processing module is further configured to perform frequency mixing on the to-be-measured signal and the feedback signal input into the feedback sampling channel to obtain a carrier signal of the to-be-measured signal. The sampling module is further configured to perform direct sampling and delay sampling on the carrier signal to obtain an undelayed sample group and a delayed sample group respectively. The parameter estimation module is further configured to perform feedback channel parameter estimation based on the undelayed sample group and the delayed sample group to obtain an estimated value of the frequency modulation of the to-be-measured signal and an initial carrier frequency estimated value of the to-be-measured signal. ​ 9. The system of claim 8, wherein the processing module is configured to: take a conjugate of the signal under test to obtain a complex conjugate signal of the signal under test; and demodulate the signal under test and the complex conjugate signal to obtain a baseband signal of the signal under test.

10. The system of claim 9, wherein the processing module is configured to: filter the baseband signal. ​ ​

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