A frequency hopping signal parameter estimation method and device, electronic equipment and storage medium

Abstract

Embodiments of the present application disclose a frequency hopping signal parameter estimation method and device, electronic equipment and a storage medium. The method comprises: acquiring a frequency hopping signal, and performing compressed sensing sampling on the frequency hopping signal to obtain a compressed signal; constructing a redundant atom dictionary for sparse representation of the frequency hopping signal according to the frequency hopping signal; wherein each atom in the redundant atom dictionary comprises a frequency domain position, a time domain position and a duration of signal hopping; determining a target number of optimal atoms in the redundant atom dictionary according to the compressed signal, and performing frequency hopping signal parameter estimation according to each optimal atom to obtain a reconstructed signal of the frequency hopping signal. The compressed sensing sampling can reduce the pressure of signal sampling; the frequency hopping signal parameter estimation by the redundant atom dictionary can effectively complete the interfered and intercepted signal, and reduce the error of signal reconstruction.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a method, apparatus, electronic device, and storage medium for estimating frequency hopping signal parameters. Background Technology

[0002] With the development of communication technology, frequency hopping communication has become one of the important communication methods due to its advantages such as good concealment, complexity, anti-interference ability, anti-fading and anti-multipath.

[0003] Frequency-hopping communication technology improves the anti-interference capability of communication systems. However, for the interfering party, accurately and quickly detecting the time-frequency characteristics of the communication signal is a crucial prerequisite for tracking or repeating interference of the frequency-hopping signal. Current technologies typically rely on the Nyquist sampling theorem to acquire signal data and then identify the frequency-hopping signal parameters.

[0004] However, with the development of communication technology, frequency hopping communication, which hops carrier frequencies across a very wide frequency band, results in extremely high sampling rates, putting pressure on data storage. Traditional Nyquist sampling is no longer sufficient for sampling wideband data. Consequently, the identified frequency hopping signal parameters are not accurate enough. Summary of the Invention

[0005] This invention provides a method, apparatus, electronic device, and storage medium for estimating frequency hopping signal parameters, thereby reducing the pressure of signal sampling and lowering the reconstruction error of frequency hopping signals.

[0006] According to one aspect of the present invention, a method for estimating parameters of a frequency hopping signal is provided, the method comprising:

[0007] Acquire the frequency hopping signal and perform compressed sensing sampling on the frequency hopping signal to obtain a compressed signal;

[0008] Based on the frequency hopping signal, a redundant atom dictionary is constructed for sparse representation of the frequency hopping signal; wherein, each atom in the redundant atom dictionary includes the frequency domain position, time domain position, and duration of the signal transition;

[0009] Based on the compressed signal, the optimal number of atoms for the target quantity is determined in the redundant atom dictionary, and the frequency hopping signal parameters are estimated based on each optimal atom to obtain the reconstructed signal of the frequency hopping signal.

[0010] According to another aspect of the present invention, a frequency hopping signal parameter estimation apparatus is provided, the apparatus comprising:

[0011] A compressed signal determination module is used to acquire a frequency hopping signal and perform compressed sensing sampling on the frequency hopping signal to obtain a compressed signal;

[0012] A redundant atom dictionary construction module is used to construct a redundant atom dictionary for sparse representation of the frequency hopping signal based on the frequency hopping signal; wherein, each atom in the redundant atom dictionary includes the frequency domain position, time domain position, and duration of the signal transition;

[0013] The reconstructed signal determination module is used to determine the optimal number of atoms in the redundant atom dictionary based on the compressed signal, and to perform frequency hopping signal parameter estimation based on each optimal atom to obtain the reconstructed signal of the frequency hopping signal.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the frequency hopping signal parameter estimation method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the frequency hopping signal parameter estimation method according to any embodiment of the present invention.

[0019] The technical solution of this invention acquires a frequency-hopping signal and performs compressed sensing sampling on the signal to obtain a compressed signal. Based on the frequency-hopping signal, a redundant atom dictionary is constructed for sparse representation of the signal. Each atom in the redundant atom dictionary includes the frequency domain position, time domain position, and duration of the signal jump. Based on the compressed signal, the optimal number of atoms in the redundant atom dictionary is determined, and the frequency-hopping signal parameters are estimated based on each optimal atom to obtain a reconstructed signal. This solves the problem of parameter identification of the received frequency-hopping signal for reconstructing the signal. Compressed sensing sampling reduces the pressure of signal sampling. Estimating the frequency-hopping signal parameters using the redundant atom dictionary effectively completes the interfered and intercepted signals, reducing the error in signal reconstruction.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0022] Figure 1a This is a flowchart of a frequency hopping signal parameter estimation method provided in Embodiment 1 of the present invention;

[0023] Figure 1b This is a flowchart illustrating the construction of a frequency hopping signal according to Embodiment 1 of the present invention;

[0024] Figure 1c This is a flowchart of a redundant atom dictionary construction method provided in Embodiment 1 of the present invention;

[0025] Figure 2a This is a flowchart of a frequency hopping signal parameter estimation method provided in Embodiment 2 of the present invention;

[0026] Figure 2b This is a flowchart for determining the optimal atom according to Embodiment 2 of the present invention;

[0027] Figure 3 This is a schematic diagram of the structure of a frequency hopping signal parameter estimation device according to Embodiment 3 of the present invention;

[0028] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the frequency hopping signal parameter estimation method of the present invention. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0031] Example 1

[0032] Figure 1a This is a flowchart of a frequency hopping signal parameter estimation method according to Embodiment 1 of the present invention. This embodiment is applicable to situations where frequency hopping signals are received and signal parameters are identified to recover the original frequency hopping signal. This method can be executed by a frequency hopping signal parameter estimation device, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1a As shown, the method includes:

[0033] Step 110: Obtain the frequency hopping signal and perform compressed sensing sampling on the frequency hopping signal to obtain the compressed signal.

[0034] The frequency hopping signal can be a frequency command composed of a pseudo-random code sequence, controlling the generation of a random carrier frequency signal, causing the signal frequency to randomly jump within the frequency band. Simply put, the signal frequency is not fixed; it changes irregularly, sometimes high and sometimes low, changing once every cycle. If each transition cycle is the same, it is called a conventional frequency hopping signal, also known as a uniform frequency hopping signal; if each transition cycle is different, it is called an unconventional frequency hopping signal, i.e., a non-uniform frequency hopping signal. In this embodiment, the frequency hopping signal is a conventional frequency modulation signal.

[0035] For example, Figure 1b This is a flowchart illustrating the construction of a frequency-hopping signal according to Embodiment 1 of the present invention. It can be implemented using methods such as... Figure 1bFor the process shown, construct a time-domain diagram of a conventional frequency-hopping signal with a randomly varying carrier frequency. Specifically, an initialization operation can be performed, setting the loop variable i to 1; generating a random integer n; determining the carrier frequency f = 100 × n based on the random number; as time t changes, a frequency-hopping signal x = sin(2π × f × t) can be generated, and set i to increment by 1, and check if i is less than or equal to a preset threshold value (such as 10); if so, return to the operation of generating a random integer n to continue generating the frequency-hopping signal until i is greater than the preset threshold value. If not, output the generated frequency-hopping signal. This frequency-hopping signal can be sent by the sender to the receiver, and the receiver can receive this frequency-hopping signal for compressive sensing sampling and signal reconstruction processing.

[0036] Specifically, due to the good concealment and complexity of frequency-hopping signals, as long as the interceptor does not understand the law of carrier frequency change, it is very difficult to intercept the communication information of the sender. However, frequency-hopping signals hop the carrier frequency over a very wide frequency band, which will bring an extremely high sampling rate. And a high sampling rate will result in a large amount of data, which will bring huge pressure to the storage, processing, and transportation of data. In this embodiment, compressive sensing sampling can reduce the sampling pressure.

[0037] Among them, compressive sensing sampling can be understood as follows: first, receive the original frequency-hopping signal, then perform compressive sampling on this signal, and then obtain a small amount of useful data. These small amounts of data can be processed to obtain the entire information of the signal. To achieve the above process, there are two very important requirements: one is that the small amount of data collected must be useful and meaningful, and it can contain all the useful information in the original data; the other is to select an optimal reconstruction algorithm, and use this algorithm to recover the original frequency-hopping signal from the small amount of useful data, and ensure that the error is as small as possible.

[0038] [[ID=...]]具体的,对于具有稀疏性的信号可以将信号在稀疏基Ψ下稀疏性表示,将一个N维稀疏信号x∈R N 投影到压缩感知测量矩阵Φ M×N (M << N)上,并且要保证测量矩阵Φ M×N 与稀疏基Ψ不相关,投影后得到一个M维压缩测量值y∈R M ,这一过程实现了在采样的同时进行了压缩处理。因此,使用压缩感知技术能够降低信号采样速率。之后,可以采用一种最优的重构算法从压缩测量值y中以极小误差或较高概率重构原始信号。

[0039] It should be noted that the content in seems to be incomplete in the original Chinese text, but I have translated it as accurately as possible based on the existing content. If you can provide the complete text, it will be more conducive to a more accurate translation.In an optional embodiment of the present invention, compressed sensing sampling is performed on the frequency hopping signal to obtain a compressed signal, including: determining the compression ratio of the frequency hopping signal for compressed sensing sampling, and determining the target signal length of the compressed signal based on the original signal length of the frequency hopping signal and the compression ratio; constructing a compression measurement matrix based on the target signal length and the original signal length; and performing compressed sensing sampling on the frequency hopping signal based on the compression measurement matrix.

[0040] The compression ratio can be set according to requirements. Compression ratio = Original signal length / Target signal length. The target signal length and the original signal length can be used as the lengths of the row vector and column vector of the compression measurement matrix, respectively. Assuming the original signal length is N and the target signal length is M, the compression measurement matrix can be Φ. M×N Compressed sensing sampling of frequency-hopping signals can be achieved using the compressed measurement matrix.

[0041] In this embodiment of the invention, optionally, the compressed measurement matrix is ​​a Gaussian random matrix. Φ M×N =randn(M,N). The compressed signal can be y = Φ M×N ×x.

[0042] Step 120: Construct a redundant atom dictionary for sparse representation of the frequency hopping signal based on the frequency hopping signal.

[0043] The redundant atom dictionary includes the frequency domain position, time domain position, and duration of the signal transition.

[0044] Specifically, frequency-hopping signals exhibit sparsity and can be sparsely represented. The sparse representation of a frequency-hopping signal under a redundant dictionary is: x = Ψα. Here, x represents the frequency-hopping signal, Ψ is the redundant atom dictionary, and α is the sparse coefficient. The frequency-hopping signal is a non-stationary signal whose carrier wave varies with time under pseudo-random sequence control; therefore, it can be represented using... Indicated by: S is the signal power; T is the signal strength. H It's a periodic jump, t1 is the first jump time, f k If t1 is the center frequency of the k-th jump, then t1+(k-1)T H Let L be the transition time of the k-th hop, and L be the signal duration. <t≤L; It is a width of T H The rectangle function,

[0045] In this embodiment, each hop of the frequency-hopping signal corresponds to a best-matching atom. Each atom is determined by the following three parameters: frequency domain position T. k Time domain location f k and duration d kTherefore, a redundant atom dictionary can be constructed, where each atom in the dictionary represents one hop of the frequency hopping signal.

[0046] Figure 1c This is a flowchart illustrating the construction of a redundant atom dictionary according to Embodiment 1 of the present invention. Figure 1c As shown, the basic parameters of the frequency-hopping signal can be used as input to obtain the data length of the frequency-hopping signal; the total number of atoms in the redundant atom dictionary can be determined based on the data length. The initial atom position can be determined in the first hop, and the subsequent atom positions can be determined sequentially based on the starting position interval. Based on the data length, the initial atom position, and the set frequency, each atom in the redundant atom dictionary can be constructed. When the number of atoms reaches the determined total number of atoms, the generation of the redundant atom dictionary is complete.

[0047] Step 130: Based on the compressed signal, determine the optimal number of atoms in the redundant atom dictionary, and estimate the frequency hopping signal parameters based on each optimal atom to obtain the reconstructed signal of the frequency hopping signal.

[0048] In this scenario, a frequency-hopping signal of length N is compressed and measured into a signal with a measurement vector of length M and a value of y. The most matching atom and its position in the redundant atom dictionary corresponding to the frequency-hopping signal are found; this atom represents one hop of the frequency-hopping signal. Finally, the three parameters representing the optimal atom are obtained, allowing estimation of the hopping rate, hopping time, and hopping frequency of the original frequency-hopping signal.

[0049] Specifically, for an m-hop frequency-hopping signal, the signal is sparsely represented in a redundant atom dictionary. Then, the m largest sparse coefficients and their positions in the dictionary are found. The positions of these m sparse coefficients correspond to a matching atom in the dictionary. Finally, by obtaining the parameters of these m best-matching atoms, the parameters of the original frequency-hopping signal can be determined.

[0050] In an optional embodiment of the present invention, the reconstruction signal of the frequency hopping signal is obtained by estimating the parameters of the frequency hopping signal based on each optimal atom, including: sorting each optimal atom according to its corresponding time domain position, and determining the hopping period of the reconstruction signal according to the duration corresponding to each optimal atom; and determining the reconstruction signal of the frequency hopping signal based on the sorted optimal atom, the frequency domain position corresponding to each optimal atom, and the hopping period.

[0051] For example, the measurement vector y can be multiplied by each column of the redundant atom dictionary; the maximum value of the multiplication result is the optimal atom to be found. This method finds the M best-matching atoms. These atoms are then sorted according to their time center values ​​in the time domain. Averaging the durations yields an estimate of the hopping period. Based on the sorted optimal atoms, their corresponding frequency domain positions, and the hopping period, the parameter values ​​of the frequency-hopping signal can be deduced, thus obtaining the reconstructed signal. The reconstructed signal can be understood as the frequency-hopping signal recovered from the original frequency-hopping signal after parameter identification.

[0052] The technical solution of this embodiment acquires a frequency-hopping signal and performs compressed sensing sampling on the signal to obtain a compressed signal. Based on the frequency-hopping signal, a redundant atom dictionary is constructed for sparse representation of the signal. Each atom in the redundant atom dictionary includes the frequency domain position, time domain position, and duration of the signal jump. Based on the compressed signal, the optimal number of atoms in the redundant atom dictionary is determined, and the parameters of the frequency-hopping signal are estimated based on each optimal atom to obtain the reconstructed signal. This solves the problem of parameter estimation and reconstruction of the frequency-hopping signal. Compressed sensing sampling reduces the pressure of signal sampling. Parameter estimation of the frequency-hopping signal using the redundant atom dictionary can effectively supplement the interfered and intercepted signals, reducing the error in signal reconstruction.

[0053] Example 2

[0054] Figure 2a This is a flowchart of a frequency hopping signal parameter estimation method according to Embodiment 2 of the present invention. This embodiment is a further refinement of the above technical solution, and the technical solution in this embodiment can be combined with various optional solutions in one or more of the above embodiments. Figure 2a As shown, the method includes:

[0055] Step 210: Acquire the frequency hopping signal, determine the compression ratio of the frequency hopping signal for compressed sensing sampling, and determine the target signal length of the compressed signal based on the original signal length of the frequency hopping signal and the compression ratio.

[0056] Optionally, the frequency hopping signal can be a conventional frequency modulation signal.

[0057] Step 220: Construct a compressed measurement matrix based on the target signal length and the original signal length; and perform compressed sensing sampling on the frequency hopping signal based on the compressed measurement matrix to obtain the compressed signal.

[0058] Optionally, the compressed measurement matrix is ​​a Gaussian random matrix.

[0059] Step 230: Determine the signal expression of the frequency hopping signal under pseudo-random sequence control, and based on the signal expression and each hop of the frequency hopping signal, determine the frequency domain position, time domain position, and duration of each atom in the redundant atom dictionary.

[0060] Among them, frequency hopping signals can be used Each jump has a corresponding jump time, jump frequency, and duration, which can be used as the basis for determining the time domain position, frequency domain position, and duration of the corresponding atom, respectively.

[0061] Specifically, this can be achieved using the parameter vector r. i ={T i f i d i A windowed sine function with unit energy is used to represent atoms in the redundant atom dictionary Ψ. The mathematical expression is: Among them, T i It is the time center (time domain location), f i d is the frequency (frequency domain position) of the sine function. i The length of the rectangular window is the hopping period of the frequency-hopping signal. With these three parameters, we can estimate the transition time, frequency, and hopping period of each hop in the frequency-hopping signal.

[0062] Step 240: Determine the redundant atom dictionary for sparse representation of frequency hopping signals based on the correlation between frequency domain position, time domain position and duration, and the positional relationship between atoms in the redundant atom dictionary.

[0063] The aforementioned redundant atom dictionary contains a large number of atoms, posing challenges for subsequent data computation and storage. To further reduce the number of atoms in the redundant atom dictionary, the relationships between frequency domain positions, time domain positions, and durations, as well as the positional relationships between atoms in the redundant atom dictionary, can be used to establish connections between the atoms in the redundant atom dictionary, thus constructing a redundant atom dictionary.

[0064] Specifically, the duration of an atom's duration is not continuous, but rather varies exponentially, i.e., it skips periods. Frequency is related to the duration of the signal, i.e., f k =k×f s / 2 i+1 (k = 1, 2, ..., 2) i +1 Secondly, the atomic positions are not arbitrary; the spacing between the initial atomic positions is d. i / 2. By utilizing the relationship between these three factors, we can better construct a dictionary of redundant atoms and reduce the number of atoms in the dictionary.

[0065] Step 250: Based on the compressed signal, determine the optimal number of atoms in the redundant atom dictionary, and estimate the frequency hopping signal parameters based on each optimal atom to obtain the reconstructed signal of the frequency hopping signal.

[0066] In an optional embodiment of the present invention, determining the optimal number of atoms for a target quantity in a redundant atom dictionary based on a compressed signal includes: constructing a recovery matrix based on a measurement matrix and a redundant atom dictionary; performing inner product calculation based on the recovery matrix and the compressed signal to obtain multiple inner product values; determining the target inner product value for a target quantity that meets preset screening conditions among the multiple inner product values ​​based on the dimension of the recovery matrix; and determining the atom at the position corresponding to the target inner product value as the optimal atom.

[0067] The recovery matrix can be Θ = ΦΨ. The inner product of the recovery matrix and the compressed signal can be calculated using λ. m =argmax| <r m-1 ,Θ j The inner product calculation can be the target inner product value for the number of targets that meet the preset screening conditions; specifically, it can be the inner product of the measurement vector y with each column of the redundant atom dictionary, and the maximum value of the inner product is the best atom to be found; that is, to determine the most matching atom. The residuals calculated using least squares can have an initial value of r0 = y; Λ m =Λ m-1 ∪{λ m Let be the increment matrix, and its initial value can be the recovery matrix, which can be expanded in each iteration. The process of determining multiple optimal atoms can be a continuous iterative process. Iteration can stop when the stopping condition is met; otherwise, m can be incremented by 1 to continue iteration. After the iteration is complete, the reconstructed signal can be obtained. Where, Θ * Let Θ be the pseudo-inverse of the recovery matrix Θ. * =(Θ H Θ) -1 Θ. Θ H This represents the conjugate transpose of the recovery matrix.

[0068] In this embodiment, the number of iterations is related to the sparsity K of the signal. Generally, the larger the sparsity K, the more iterations are needed; the smaller the sparsity K, the fewer iterations are needed. Typically, choosing an iteration count m = K is optimal. In addition, an iteration stopping condition must be met to achieve convergence. This stopping condition can be that the residual vector is sufficiently convergent, i.e. Here, δ is generally a positive constant close to zero.

[0069] Figure 2bThis is a flowchart for determining the optimal atoms according to Embodiment 2 of the present invention. Figure 2b As shown, the process of determining the optimal atom in this embodiment of the invention can be explained more clearly. First, the increment matrix and residual vector are initialized; the iteration count m = K is set; within the iteration count, the inner product value and the position of the maximum inner product value are recorded; all column vectors of the recovery matrix and the sparse inner product values ​​of the residual projection are obtained, and the atom position corresponding to the maximum inner product value is found; the increment matrix is ​​expanded using the increment matrix and the residual vector; the least squares method is used to minimize the residual vector, and it is determined whether the residual vector satisfies the iteration stopping condition; if not, the process returns to recording the inner product value and the position of the maximum inner product value within the iteration count until the residual vector satisfies the iteration stopping condition; if the residual vector satisfies the iteration stopping condition, the iteration stops, the optimal atom is output, and the frequency hopping signal is reconstructed to obtain the reconstructed signal.

[0070] In an optional embodiment of the present invention, the reconstruction signal of the frequency hopping signal is obtained by estimating the parameters of the frequency hopping signal based on each optimal atom, including: sorting each optimal atom according to its corresponding time domain position, and determining the hopping period of the reconstruction signal according to the duration corresponding to each optimal atom; and determining the reconstruction signal of the frequency hopping signal based on the sorted optimal atom, the frequency domain position corresponding to each optimal atom, and the hopping period.

[0071] The technical solution of this embodiment involves acquiring a frequency-hopping signal, determining the compression ratio of the frequency-hopping signal for compressed sensing sampling, and determining the target signal length of the compressed signal based on the original signal length and compression ratio of the frequency-hopping signal; constructing a compression measurement matrix based on the target signal length and the original signal length; performing compressed sensing sampling on the frequency-hopping signal based on the compression measurement matrix to obtain the compressed signal; determining the signal expression of the frequency-hopping signal under pseudo-random sequence control, and determining the frequency domain position, time domain position, and duration of each atom in the redundant atom dictionary based on the signal expression and each hop of the frequency-hopping signal; and determining the frequency domain position, time domain position, and duration based on the frequency domain position, time domain position, and duration of the compressed signal. By analyzing the correlation between durations and the positional relationships between atoms in the redundant atom dictionary, a redundant atom dictionary is determined for sparse representation of the frequency-hopping signal. Based on the compressed signal, the optimal number of atoms for the target quantity is determined in the redundant atom dictionary, and the frequency-hopping signal parameters are estimated based on each optimal atom to obtain the reconstructed signal. This solves the problem of parameter estimation and reconstruction of the frequency-hopping signal. Compressed sensing sampling can reduce the pressure of signal sampling. By improving the redundant atom dictionary, the amount of data can be reduced. Using the redundant atom dictionary for frequency-hopping signal parameter estimation can effectively complete the interfered and intercepted signals and reduce the error of signal reconstruction.

[0072] The acquisition, storage, and application of various signals involved in the technical solutions of this invention comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0073] Example 3

[0074] Figure 3 This is a schematic diagram of a frequency hopping signal parameter estimation device according to Embodiment 3 of the present invention. Figure 3 As shown, the device includes: a compressed signal determination module 310, a redundant atom dictionary construction module 320, and a reconstructed signal determination module 330. Wherein:

[0075] The compressed signal determination module 310 is used to acquire the frequency hopping signal and perform compressed sensing sampling on the frequency hopping signal to obtain the compressed signal;

[0076] The redundant atom dictionary construction module 320 is used to construct a redundant atom dictionary for sparse representation of the frequency hopping signal based on the frequency hopping signal; wherein, each atom in the redundant atom dictionary includes the frequency domain position, time domain position and duration of the signal transition.

[0077] The reconstructed signal determination module 330 is used to determine the optimal number of atoms in the redundant atom dictionary based on the compressed signal, and to perform frequency hopping signal parameter estimation based on each optimal atom to obtain the reconstructed signal of the frequency hopping signal.

[0078] Optionally, the compression signal determination module 310 includes:

[0079] The target signal length determination unit is used to determine the compression ratio of the frequency hopping signal for compressed sensing sampling, and to determine the target signal length of the compressed signal based on the original signal length of the frequency hopping signal and the compression ratio.

[0080] The compressed sensing sampling unit is used to construct a compressed measurement matrix based on the target signal length and the original signal length, and to perform compressed sensing sampling on the frequency hopping signal based on the compressed measurement matrix.

[0081] Optional, redundant atomic dictionary construction module 320 includes:

[0082] The atom information determination unit is used to determine the signal expression of the frequency hopping signal under pseudo-random sequence control, and based on the signal expression and each hop of the frequency hopping signal, determine the frequency domain position, time domain position and duration of each atom in the redundant atom dictionary;

[0083] The redundant atom dictionary determination unit is used to determine the redundant atom dictionary when the frequency hopping signal is sparsely represented based on the correlation between the frequency domain position, the time domain position and the duration, as well as the positional relationship between the atoms in the redundant atom dictionary.

[0084] Optionally, the reconstructed signal determination module 330 includes:

[0085] The recovery matrix construction unit is used to construct the recovery matrix based on the measurement matrix and the dictionary of redundant atoms.

[0086] The inner product value determination unit is used to perform inner product calculation based on the recovery matrix and the compressed signal to obtain multiple inner product values;

[0087] The target inner product value filtering unit is used to determine the number of target inner product values ​​that meet the preset filtering conditions from multiple inner product values ​​based on the dimension of the recovery matrix.

[0088] The optimal atom determination unit is used to determine the atom at the position corresponding to the target inner product value as the optimal atom.

[0089] Optionally, the reconstructed signal determination module 330 includes:

[0090] The jump period determination unit is used to sort each best atom according to its corresponding time domain position and determine the jump period of the reconstructed signal based on the duration corresponding to each best atom.

[0091] The reconstructed signal determination unit is used to determine the reconstructed signal of the frequency hopping signal based on the sorted best atoms, the frequency domain position corresponding to each best atom, and the hopping period.

[0092] Optionally, the frequency hopping signal can be a conventional frequency modulation signal.

[0093] Optionally, the compressed measurement matrix is ​​a Gaussian random matrix.

[0094] The frequency hopping signal parameter estimation device provided in this embodiment of the invention can execute the frequency hopping signal parameter estimation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0095] Example 4

[0096] Figure 4 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0097] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0098] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0099] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as frequency hopping signal parameter estimation methods.

[0100] In some embodiments, the frequency hopping signal parameter estimation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the frequency hopping signal parameter estimation method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the frequency hopping signal parameter estimation method by any other suitable means (e.g., by means of firmware).

[0101] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0102] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0103] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0104] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0105] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0106] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0107] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0108] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for estimating parameters of a frequency-hopping signal, characterized in that, include: Acquire the frequency hopping signal and perform compressed sensing sampling on the frequency hopping signal to obtain a compressed signal; Based on the frequency hopping signal, a redundant atom dictionary is constructed for sparse representation of the frequency hopping signal; wherein, each atom in the redundant atom dictionary includes the frequency domain position, time domain position, and duration of the signal transition; Based on the compressed signal, the optimal number of atoms for the target quantity is determined in the redundant atom dictionary, and the frequency hopping signal parameters are estimated based on each optimal atom to obtain the reconstructed signal of the frequency hopping signal. The step of constructing a redundant atom dictionary for sparse representation of the frequency hopping signal based on the frequency hopping signal includes: Determine the signal expression of the frequency hopping signal under pseudo-random sequence control; and based on the signal expression and each hop of the frequency hopping signal, determine the frequency domain position, time domain position, and duration of each atom in the redundant atom dictionary. Based on the correlation between frequency domain position, time domain position and duration, and the positional relationship between each atom in the redundant atom dictionary, the redundant atom dictionary for sparse representation of the frequency hopping signal is determined. Wherein, the signal expression is Where S is the signal power; It's a cycle skipping. This is the first transition moment. If is the center frequency of the k-th jump, then Let L be the transition time of the k-th hop, and L be the signal duration. ; The width is The rectangle function, Redundant atomic dictionary atoms in The mathematical expression is: ; For time domain location, For frequency domain location, It is the cycle skipping of the frequency hopping signal.

2. The method according to claim 1, characterized in that, The frequency hopping signal is subjected to compressed sensing sampling to obtain a compressed signal, including: Determine the compression ratio of the frequency hopping signal for compressed sensing sampling, and determine the target signal length of the compressed signal based on the original signal length of the frequency hopping signal and the compression ratio; A compressed measurement matrix is ​​constructed based on the target signal length and the original signal length; and the frequency hopping signal is subjected to compressed sensing sampling based on the compressed measurement matrix.

3. The method of claim 2, wherein, Based on the compressed signal, determining the optimal number of atoms for the target quantity from the redundant atom dictionary includes: Construct a recovery matrix based on the measurement matrix and the redundant atom dictionary; Based on the recovery matrix and the compressed signal, an inner product calculation is performed to obtain multiple inner product values; Based on the dimension of the recovery matrix, determine the target number of inner product values ​​that satisfy the preset screening conditions among the multiple inner product values; The atom at the position corresponding to the target inner product value is determined as the optimal atom.

4. The method of claim 1, wherein, Based on the optimal atoms described above, frequency hopping signal parameters are estimated to obtain the reconstructed signal of the frequency hopping signal, including: The optimal atoms are sorted according to their corresponding time-domain positions, and the jump period of the reconstructed signal is determined based on the duration corresponding to each optimal atom. The reconstructed signal of the frequency hopping signal is determined based on the sorted optimal atoms, the frequency domain positions corresponding to the optimal atoms, and the hopping period.

5. The method of claim 1, wherein, The frequency hopping signal is a conventional frequency modulation signal.

6. The method of claim 2, wherein, The compressed measurement matrix is ​​a Gaussian random matrix.

7. A frequency hopping signal parameter estimation apparatus characterized by comprising: include: A compressed signal determination module is used to acquire a frequency hopping signal and perform compressed sensing sampling on the frequency hopping signal to obtain a compressed signal; A redundant atom dictionary construction module is used to construct a redundant atom dictionary for sparse representation of the frequency hopping signal based on the frequency hopping signal; wherein, each atom in the redundant atom dictionary includes the frequency domain position, time domain position, and duration of the signal transition; The reconstructed signal determination module is used to determine the optimal number of atoms in the redundant atom dictionary based on the compressed signal, and to perform frequency hopping signal parameter estimation based on each optimal atom to obtain the reconstructed signal of the frequency hopping signal; The redundant atom dictionary construction module includes: The atom information determination unit is used to determine the signal expression of the frequency hopping signal under pseudo-random sequence control; and based on the signal expression and each hop of the frequency hopping signal, to determine the frequency domain position, time domain position and duration of each atom in the redundant atom dictionary; The redundant atom dictionary determination unit is used to determine the redundant atom dictionary when the frequency hopping signal is sparsely represented based on the correlation between the frequency domain position, the time domain position and the duration, as well as the positional relationship between each atom in the redundant atom dictionary. Wherein, the signal expression is Where S is the signal power; It's a cycle skipping. This is the first transition moment. If is the center frequency of the k-th jump, then Let L be the transition time of the k-th hop, and L be the signal duration. ; The width is The rectangle function, Redundant atomic dictionary atoms in The mathematical expression is: ; For time domain location, For frequency domain location, It is the cycle skipping of the frequency hopping signal.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the frequency hopping signal parameter estimation method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the frequency hopping signal parameter estimation method according to any one of claims 1-6.

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