Delay-Doppler dual-extended channel estimation method and device under ice source noise

Abstract

The present invention discloses a method, device, medium and equipment for estimating a delay-Doppler dual-extension channel under ice-source noise, and relates to the technical field of under-ice channel estimation, so as to solve the technical problem that the performance of estimating a delay-Doppler dual-extension channel is seriously degraded under impulse noise interference. The method comprises: constructing a delay-Doppler dual-extension channel model h, constructing an over-complete dictionary for a received signal y based on a transmitted signal x, reconstructing the over-complete dictionary using Doppler coefficients, and obtaining an over-complete dictionary A in the delay-Doppler domain; determining a received signal y=Ah; using an orthogonal matching pursuit method and using Lp norm correlation as correlation, performing multiple iterations on the equation y=Ah to obtain a sparse approximation value, and determining a delay-Doppler dual-extension channel estimation result h according to the sparse approximation value. The method provided by the present invention can effectively suppress impulse noise interference and realize delay-Doppler dual-extension channel estimation under ice-source noise.

Description

Technical Field

[0001] The present invention relates to the technical field of under-ice channel estimation, and in particular to a delay-Doppler dual-extended channel estimation method, device, medium and equipment under ice source noise. Background Art

[0002] Affected by global warming, the Arctic glaciers have begun to melt faster, and large tracts of navigable channels and sea areas have appeared in the Arctic Ocean. With the development of polar shipping routes, the strategic position of the Arctic has become more prominent. Most of the polar regions are covered with ice and snow all year round, so a series of activities under the ice in the waters of the Arctic Ocean require the support of hydroacoustic technology. Sound propagation under the ice in the Arctic Ocean is one of the key contents of polar acoustic research. Due to the relative movement between ice layers and the violent sea ice activities caused by ice melting and fracture, the ice source noise in the Arctic Ocean is different from the noise in the open sea. Its statistical characteristics no longer conform to the Gaussian distribution, but are more in line with the statistical characteristics of impulse noise, that is, it is random and does not have second-order moments and higher-order moments. Therefore, the traditional delay-Doppler dual-expansion channel estimation method, which is applicable in Gaussian noise environments, has a serious performance degradation in impulse noise environments.

[0003] The performance of the existing technology is seriously degraded when estimating the delay-Doppler dual extension channel under impulse noise interference, and it cannot be applied to polar sonar equipment. The statistical characteristics of ice source noise do not conform to the Gaussian distribution, but are more consistent with the statistical characteristics of impulse noise, that is, it is random and has no second-order moments and higher-order moments. The traditional orthogonal matching pursuit algorithm (Orthogonal Matching Pursuit, OMP) algorithm has poor impulse noise suppression ability in a Gaussian noise environment using the inner product correlation method. When there is impulse noise interference, the performance of the traditional OMP algorithm is greatly reduced.

[0004] In summary, the present application is aimed at solving the technical problem of serious degradation in the performance of delay-Doppler dual extended channel estimation under impulse noise interference. Summary of the invention

[0005] The purpose of the present invention is to address the technical problem that the performance of delay-Doppler dual-extension channel estimation under impulse noise interference is seriously degraded in existing channel estimation methods, and a delay-Doppler dual-extension channel estimation method under ice source noise is proposed, which is used to estimate the characteristic parameters of an underwater acoustic channel under ice, reconstruct a complete delay-Doppler domain dictionary of a received signal, and simultaneously adopt an orthogonal matching pursuit algorithm (OMP) to realize channel estimation. By improving the inner product correlation in OMP to Lp norm correlation, impulse noise interference can be effectively suppressed, and delay-Doppler dual-extension channel estimation under ice source noise can be realized.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A delay-Doppler dual-extended channel estimation method under ice source noise, comprising:

[0008] Construct a delay-Doppler dual-extended channel model h based on the number of multipaths and the Doppler coefficient, delay, and amplitude of the sparse multipath channel;

[0009] An overcomplete dictionary is constructed for the received signal y based on the transmitted signal x, and the overcomplete dictionary is reconstructed using the Doppler coefficient to obtain an overcomplete dictionary A in the delay-Doppler domain;

[0010] Determine the received signal y as the product Ah of the delay-Doppler domain overcomplete dictionary A and the delay-Doppler double extended channel h; the delay-Doppler double extended channel estimation problem is converted into a problem of solving the equation y=Ah;

[0011] The orthogonal matching pursuit method is used and the Lp norm correlation is used as the correlation. The equation y = Ah is solved multiple times by iteration to obtain the sparse approximation value.

[0012] According to the sparse approximation value Determine the delay-Doppler dual-extended channel estimation result h.

[0013] Compared with the prior art, the delay-Doppler dual-expansion channel estimation method under ice source noise provided by the present invention has the following beneficial effects compared with the prior art channel estimation technology:

[0014] (1) By designing a complete delay-Doppler domain dictionary for the received signal and using the orthogonal matching pursuit (OMP) algorithm to achieve channel estimation, the Doppler coefficient is used to reconstruct the dictionary matrix, which can simultaneously estimate the channel delay and Doppler coefficient, so that the Lp-OMP algorithm based on dictionary reconstruction can estimate the delay-Doppler dual-extended channel. The dictionary matrix of traditional technology does not consider the impact of the Doppler effect on the signal and cannot estimate the delay-Doppler dual-extended channel.

[0015] (2) The Lp norm correlation in OMP is used instead of the inner product to calculate the correlation, which effectively suppresses the interference of pulse noise and realizes the delay-Doppler dual extended channel estimation under ice source noise. The Lp norm constraint is introduced into the OMP algorithm, the Lp correlation is introduced to calculate the most relevant atoms, and the solution of the Lp norm minimization problem is introduced to update the residual. The Lp-OMP algorithm can effectively suppress the interference of pulse noise on the signal. The prior art uses the inner product to calculate the correlation and the least squares method to calculate the path amplitude. The ability to suppress pulse noise is limited. When the signal is interfered by pulse noise, the algorithm performance is severely degraded, and the performance is poor in the polar environment. The technical solution of the present application uses the Lp correlation to calculate the most relevant atoms and the method of solving the Lp norm minimization problem to update the residual, which can effectively suppress the interference of pulse noise on the signal.

[0016] The delay-Doppler dual-extended channel estimation method of the present application provides a detailed delay-Doppler dual-extended channel estimation, and more accurately estimates the delay-Doppler dual-extended channel under ice source noise. The obtained delay-Doppler dual-extended channel estimation result has high accuracy and good impulse noise suppression effect, and can be applied to fields such as polar sonar system communications.

[0017] The present invention also provides a delay-Doppler dual-extended channel estimation device under ice source noise, comprising:

[0018] The channel model unit is configured to construct a delay-Doppler dual-extended channel model h based on the number of multipaths and the Doppler coefficient, delay, and amplitude of the sparse multipath channel;

[0019] a dictionary unit configured to construct an overcomplete dictionary for a received signal y based on the transmitted signal x;

[0020] A dictionary reconstruction unit is configured to reconstruct the overcomplete dictionary using the Doppler coefficient to obtain an overcomplete dictionary A in the delay-Doppler domain;

[0021] The signal receiving unit is configured to determine that the received signal y is the product Ah of the delay-Doppler domain overcomplete dictionary A and the delay-Doppler double extended channel h, and the delay-Doppler double extended channel estimation problem is to solve the equation y=Ah;

[0022] The iterative solution unit is configured to adopt an orthogonal matching pursuit method and use the Lp norm correlation as the correlation to perform multiple iterations on the equation y=Ah to obtain a sparse approximation value

[0023] The output unit is configured to approximate the value according to the sparse Determine the delay-Doppler dual-extended channel estimation result h.

[0024] Compared with the prior art, the beneficial effects of the delay-Doppler dual extended channel estimation device under ice source noise provided by the present invention are the same as the beneficial effects of the delay-Doppler dual extended channel estimation method under ice source noise described in the above technical solution, and will not be repeated here.

[0025] The present invention also provides a computer storage medium, in which instructions are stored. When the instructions are executed, the delay-Doppler dual extension channel estimation method under ice source noise as described above is implemented.

[0026] The present invention also provides a computing device, including a processor and a communication interface coupled to the processor; the processor is used to run a computer program or instruction to implement the delay-Doppler dual extension channel estimation method under ice source noise as described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0028] Figure 1 Schematic diagram of a delay-Doppler dual-extended channel estimation method under ice source noise in an embodiment of the present invention.

[0029] Figure 2 Schematic diagram of a delay-Doppler dual-extended channel estimation device under ice source noise in an embodiment of the present invention.

[0030] Figure 3 Schematic diagram of the delay-Doppler dual extension channel estimation principle in an embodiment of the present invention.

[0031] Figure 4 4 is a flowchart of iterative execution of the Lp-OMP algorithm in an embodiment of the present invention.

[0032] Figure 5 Schematic diagram of the root mean square error curve of the Lp-OMP algorithm and the traditional OMP algorithm versus the signal-to-noise ratio in an embodiment of the present invention.

[0033] Figure 6 Schematic diagram of the true value of the delay-Doppler dual extension channel in an embodiment of the present invention.

[0034] Figure 7 This is a 3D estimation diagram of the delay-Doppler dual extended channel in an embodiment of the present invention.

[0035] Figure 8 3 is a comparison diagram between the true value and the estimated value of the channel when the Doppler coefficient is 0.95 in an embodiment of the present invention.

[0036] Fig. 9 3 is a comparison diagram of the true channel value and the estimated channel value when the Doppler coefficient is 1.05 in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to clearly describe the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, words such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and effects. For example, the first threshold and the second threshold are only used to distinguish different thresholds, and their order is not limited. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit them to be different.

[0038] It should be noted that, in the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0039] In the present invention, "at least one" means one or more, and "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, the combination of a and b, the combination of a and c, the combination of b and c, or the combination of a, b and c, where a, b, c can be single or multiple.

[0040] like Figure 1 As shown, a flow chart of the delay-Doppler double extension channel estimation method under ice source noise is given, which includes the following steps:

[0041] Step S1, constructing a delay-Doppler dual extension channel model h based on the number of multipaths and the Doppler coefficient, delay, and amplitude of the sparse multipath channel;

[0042] Step S2, constructing an overcomplete dictionary for the received signal y based on the transmitted signal x, and reconstructing the overcomplete dictionary using the Doppler coefficient to obtain an overcomplete dictionary A in the delay-Doppler domain;

[0043] Step S3, determining that the received signal y is the product Ah of the delay-Doppler domain overcomplete dictionary A and the delay-Doppler double extended channel h, and the delay-Doppler double extended channel estimation problem is to solve the equation y=Ah;

[0044] Step S4: Using the orthogonal matching pursuit method and taking the Lp norm correlation as the correlation, the equation y=Ah is solved for multiple iterations to obtain a sparse approximation value.

[0045] Step S5: Based on the sparse approximation value Determine the delay-Doppler dual-extended channel estimation result h.

[0046] The delay-Doppler domain over-complete dictionary includes all delays and Doppler coefficients of the channel.

[0047] The reconstructing the overcomplete dictionary by using the Doppler coefficient is to introduce the Doppler coefficient into the original overcomplete dictionary, and expand the overcomplete dictionary to the delay-Doppler two-dimensional domain.

[0048] The orthogonal matching pursuit method is used and the Lp norm correlation is used as the correlation. The equation y=Ah is solved by multiple iterations to obtain the sparse approximation value. The following steps are involved:

[0049] Input delay-Doppler domain overcomplete dictionary A, received signal y, sparsity K;

[0050] Initialize the residual, index set, sparse approximation solution and number of iterations of the first iteration;

[0051] In each iteration process, the index corresponding to the maximum value of the Lp correlation between the residual and the column of the delay-Doppler domain overcomplete dictionary is found and expanded to the index set; the reconstructed atomic set in the delay-Doppler domain overcomplete dictionary is recorded, and the Lp norm minimization problem is solved for the reconstructed atomic set to obtain a sparse approximation solution; the residual is updated using the obtained sparse approximation solution; after the iteration end condition is met, the sparse approximation solution is output.

[0052] The iteration termination condition is that the number of iterations is greater than the sparsity K. The reconstructed atomic set includes the reconstructed atomic set of the previous iteration and the sparse approximation solution to be solved in this iteration. The residual is represented by the difference obtained by subtracting the product of the reconstructed atomic set and the sparse approximation solution from the received signal.

[0053] like Figure 2 As shown, a schematic diagram of a delay-Doppler dual-extended channel estimation device under ice source noise is given, including:

[0054] The channel model unit is configured to construct a delay-Doppler dual-extended channel model h based on the number of multipaths and the Doppler coefficient, delay, and amplitude of the sparse multipath channel;

[0055] a dictionary unit configured to construct an overcomplete dictionary for a received signal y based on the transmitted signal x;

[0056] A dictionary reconstruction unit is configured to reconstruct the overcomplete dictionary using the Doppler coefficient to obtain an overcomplete dictionary A in the delay-Doppler domain;

[0057] The signal receiving unit is configured to determine that the received signal y is the product Ah of the delay-Doppler domain overcomplete dictionary A and the delay-Doppler double extended channel h, and the delay-Doppler double extended channel estimation problem is to solve the equation y=Ah;

[0058] The iterative solution unit is configured to adopt an orthogonal matching pursuit method and use the Lp norm correlation as the correlation to perform multiple iterations on the equation y=Ah to obtain a sparse approximation value

[0059] The output unit is configured to approximate the value according to the sparse Determine the delay-Doppler dual-extended channel estimation result h.

[0060] like Figure 3 As shown in the figure, the principle diagram of the delay-Doppler double extension channel estimation method under ice source noise is given. The specific principle is as follows:

[0061] An overcomplete dictionary of the received signal is constructed, and the Doppler coefficient is used to reconstruct the dictionary to obtain an overcomplete dictionary in the delay-Doppler domain. The received signal is solved using the OMP algorithm and the overcomplete dictionary in the delay-Doppler domain. The Lp norm constraint is introduced in the solution process, that is, the Lp-OMP algorithm is formed to estimate the channel, and finally the delay-Doppler dual extended channel estimation result is output.

[0062] In step S1, a delay-Doppler dual extension channel model h is constructed based on the number of multipaths and the Doppler coefficient, delay, and amplitude of the sparse multipath channel.

[0063] Usually, the received signal y(t) of the receiver is expressed as:

[0064] y(t)=h(τ,t)*x(t)+n(t)

[0065] =∫h(τ,t)x(t-τ)dτ+n(t),

[0066] Among them, * represents linear convolution, x(t) is the transmission signal of the transmitter. n(t) is the impulse noise that conforms to the α-stable distribution, and the specific characteristic function is expressed as: Among them, 0<α<2 represents the characteristic index describing the tail of the distribution, σ α >0 represents the dispersion parameter of the dispersion diffusion degree, which is similar to the variance in Gaussian distribution. h(τ,t) is the impulse response of the time-varying channel, expressed as: Where K is the number of multipaths, a k (t) and τ k (t) are the time-varying amplitude and delay of path k respectively.

[0067] Assume that the transmitted signal x(t) is transmitted as a pulse signal with a duration of T. Within the duration T, the amplitude of the channel multipath is time-invariant, that is, a k (t) = a k For the delay-Doppler double extension channel, the Doppler expansion factor is: Among them, v kis the relative speed between the transmitter and the receiver, and c is the speed of sound.

[0068] Therefore, based on the number of multipaths and the Doppler coefficient, delay, and amplitude of the sparse multipath channel, a delay-Doppler double extension channel model is constructed. The delay-Doppler double extension channel h(τ, t) between the transmitted signal and the received signal is expressed as:

[0069]

[0070] Based on the delay-Doppler double-extended channel model, the receiver's received signal y(t) is expressed as:

[0071]

[0072] Define τ k =τ k ′ / (1+d k ′) and d k =1+d k ′, then the received signal y(t) is expressed as:

[0073]

[0074] Among them, x is the transmitted signal and n(t) is the noise signal.

[0075] According to the received signal y(t) expressed as It can be seen that the key to realizing delay-Doppler dual extension channel estimation is to estimate the Doppler coefficient d of the sparse multipath channel. k , delay τ k and amplitude a k , where K is the number of multipaths.

[0076] In step S2, an overcomplete dictionary is constructed for the received signal y based on the transmitted signal x, and the overcomplete dictionary is reconstructed using the Doppler coefficient to obtain a delay-Doppler domain overcomplete dictionary A having both delay and Doppler domains.

[0077] Assume that the transmitted signal x is: x = [x(0), x(1), L, x(M)] T , the signal length is M+1, and the overcomplete dictionary A of the received signal under different delays is constructed as:

[0078]

[0079] Consider the Doppler coefficient of the channel d∈A d ={d min ,d min +Δd,…,d max}, where d min is the minimum possible value of the Doppler expansion coefficient, dmax is the maximum possible value, Δd is the search accuracy of the Doppler expansion coefficient. The dimension N of the Doppler search dictionary matrix is d =(d max -d min ) / Δd+1.

[0080] When the Doppler coefficient is d i When , the dictionary is constructed as:

[0081]

[0082] Therefore, the overcomplete dictionary A in the delay-Doppler domain reconstructed and generated by considering the Doppler expansion coefficient is expressed as: The delay-Doppler domain overcomplete dictionary A is overcomplete and must include all delays and Doppler coefficients of the channel.

[0083] The original overcomplete dictionary only contains the delay domain, not the Doppler domain, and cannot effectively estimate the delay-Doppler dual extended channel. The original overcomplete dictionary is reconstructed by introducing the Doppler coefficient, and the overcomplete dictionary is expanded to the delay-Doppler two-dimensional domain, and the delay-Doppler domain overcomplete dictionary is reconstructed. The delay-Doppler domain overcomplete dictionary contains both the delay domain and the Doppler domain, which can effectively estimate the delay-Doppler dual extended channel.

[0084] In step S3, the received signal y is determined to be the product Ah of the delay-Doppler domain overcomplete dictionary A and the delay-Doppler double extended channel h. The delay-Doppler double extended channel estimation problem is to solve the equation: y=Ah, where y represents the received signal of the receiver and h represents the channel estimation result.

[0085] In step S4, the orthogonal matching pursuit method is used and the Lp norm correlation is used as the correlation to perform multiple iterations on the equation y = Ah to obtain the sparse approximation value

[0086] Based on the Lp norm and the existing OMP algorithm, the Lp-OMP algorithm is generated, and the equation y=Ah is solved using the Lp-OMP algorithm. The solution idea of ​​the Lp-OMP algorithm is similar to that of the OMP algorithm. The OMP algorithm selects the atom with the largest absolute value of the inner product of the received signal and the dictionary matrix as the atom with the largest correlation coefficient in each iteration to participate in subsequent calculations. However, the method of solving the correlation by the inner product has limited effect on suppressing impulse noise. When there is impulse noise interference, the performance of the OMP algorithm is seriously degraded.

[0087] In the Lp-OMP algorithm, the Lp norm correlation is used instead of the inner product to find the correlation. The Lp correlation is defined as The Lp-OMP algorithm uses Lp correlation to replace the traditional inner product correlation method, and combines it with the OMP algorithm to effectively suppress the impact of impulse noise on the signal.

[0088] like Figure 4 As shown, the Lp-OMP algorithm specifically includes the following steps:

[0089] Input: delay-Doppler domain overcomplete dictionary A, received signal y, sparsity K.

[0090] Initialization: residual r0 = y, index set Sparse approximation solution The number of iterations t=1.

[0091] Iteration: In the tth iteration, find the residual r and the column a of the dictionary matrix A j The index corresponding to the maximum Lp correlation value Expand the index set to Λ t =Λ t-1 ∪j t , records the set of reconstructed atoms found in the dictionary matrix Solving the Lp norm minimization problem yields

[0092] Update residual The above iterative process is repeated, with t=t+1 in each iteration, until t>K is satisfied.

[0093] Output: Sparse approximation of the delay-Doppler double-extended channel h

[0094] In step S5, according to the sparse approximation value obtained by solving Determine the delay-Doppler dual-extended channel estimation result h.

[0095] The traditional OMP algorithm uses the inner product to calculate the correlation. The Lp-OMP algorithm redefines the correlation and uses Lp correlation instead of the inner product to solve the maximum atomic correlation, which can effectively suppress the influence of ice source noise on the signal.

[0096] The traditional OMP algorithm uses the least squares method to solve the least squares solution of y=Ah in the iterative process to update the residual. The Lp-OMP algorithm uses the solution of the Lp norm minimization problem to update the residual, which can effectively suppress the influence of ice source noise.

[0097] like Figure 5As shown, a schematic diagram of the root mean square error of the delay-Doppler double extended channel estimated by the Lp-OMP algorithm and the traditional OMP algorithm under ice source noise and the signal-to-noise ratio is given. When the generalized signal-to-noise ratio (GSNR) is -3dB, the mean square error (MSE) of the Lp-OMP algorithm in estimating the delay-Doppler double extended channel under ice is reduced by up to 0.398 compared with the traditional OMP algorithm; when the GSNR is 0dB, the MSE of the channel estimated by the method proposed in the embodiment of the present application is reduced by 0.18 compared with the traditional OMP algorithm, and the algorithm performance is improved by more than 10%.

[0098] Figure 5 The results show that the Lp-OMP algorithm based on dictionary reconstruction in the embodiment of the present application has better estimation performance than the traditional OMP algorithm in estimating the delay-Doppler dual extension channel in a pulse noise interference environment, and the suppression effect is best when p=1. This is because the traditional OMP algorithm's inner product to find the maximum correlation atom has limited ability to suppress pulse noise.

[0099] like Figure 6 As shown, the true value of the delay-Doppler double-extended channel is given. Figure 6 The two Doppler expansion coefficients and four multipaths obtained by simulation are shown, corresponding to the Doppler coefficients d k =0.95, the delays are 10ms and 20ms respectively; and d k =1.05, the delays are 30ms and 45ms respectively.

[0100] like Figure 7 As shown, the delay-Doppler double-extended channel estimation value is given. Figure 7 The 3D estimation diagram of the delay-Doppler dual extended channel using the Lp-OMP algorithm based on dictionary reconstruction according to the embodiment of the present application is shown. Obviously, the proposed channel estimation method can well estimate the delay and Doppler coefficient of the delay-Doppler dual extended channel under impulse noise interference.

[0101] like Figure 8 As shown in Figure 1, the delay-Doppler double-extended channel amplitude estimation diagram using the Lp-OMP algorithm is given when the Doppler coefficient is 0.95. Fig. 9 As shown in Figure 1, the delay-Doppler double extended channel amplitude estimation diagram using the Lp-OMP algorithm with a Doppler coefficient of 1.05 is given. Obviously, the Lp-OMP algorithm can well estimate the amplitude of the delay-Doppler double extended channel multipath under impulse noise interference.

[0102] Compared with the prior art, the present application can accurately estimate the delay-Doppler dual extended channel and can effectively suppress impulse noise. The present application adopts a method different from the prior art that uses the Doppler coefficient to reconstruct the dictionary matrix, which can simultaneously estimate the delay and Doppler coefficient of the channel. At the same time, the present application adopts the Lp correlation different from the prior art to find the most relevant atoms and solve the Lp norm minimization problem to update the residual, which can effectively suppress the interference of impulse noise on the signal. Under impulse noise interference, the channel estimation error of the channel estimation method of the present application is significantly lower than that of the prior art, and can realize delay-Doppler dual extended channel estimation under ice source noise.

[0103] Compared with the prior art, the beneficial effects of the delay-Doppler dual extended channel estimation device under ice source noise are the same as the beneficial effects of the delay-Doppler dual extended channel estimation method under ice source noise described in the above technical solution, and will not be repeated here.

[0104] The present application also provides a computer storage medium, in which instructions are stored. When the instructions are executed, the delay-Doppler dual extension channel estimation method under ice source noise as described above is implemented.

[0105] The present application also provides a computing device, including a processor and a communication interface coupled to the processor; the processor is used to run a computer program or instruction to implement the delay-Doppler dual extension channel estimation method under ice source noise as described above.

[0106] It should be easily appreciated by those skilled in the art that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present invention can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is performed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0107] The embodiment of the present invention can divide the functional modules according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present invention is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0108] Although the present invention has been described in conjunction with specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present invention. Accordingly, this specification and the accompanying drawings are merely exemplary illustrations of the present invention as defined by the appended claims and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present invention. Obviously, those skilled in the art may make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, the present invention is intended to include such modifications and variations if they fall within the scope of the claims of the present invention and their equivalents.

Claims

1. A delay-Doppler dual-extended channel estimation method under ice source noise, characterized in that: include: Based on the number of multipaths K and the Doppler coefficient d of the sparse multipath channel k , delay τ k , amplitude α k Constructing a delay-Doppler dual-extended channel model in; The Doppler spread factor is v k is the relative speed between the transmitter and the receiver, c is the speed of sound, d k =1+d′ k ; An overcomplete dictionary is constructed for the received signal y based on the transmitted signal x, and the overcomplete dictionary is reconstructed using the Doppler coefficient to obtain an overcomplete dictionary in the delay-Doppler domain Transmitted signal x = [x(0), x(1), L, x(M)] T , the signal length is M+1, when the Doppler coefficient is d i When dictionary item A i Including delay domain elements and Doppler domain elements: Determine that the received signal y is the product of the delay-Doppler domain overcomplete dictionary A and the delay-Doppler double extended channel h y=Ah, and the delay-Doppler double extended channel estimation problem is to solve the equation y=Ah; Using the orthogonal matching pursuit method and taking the Lp norm correlation as the correlation, y = Ah is solved by multiple iterations. Until t>K is satisfied to obtain the sparse approximation value The following steps are involved: Input: delay-Doppler domain overcomplete dictionary A, received signal y, multipath number K; Initialization: residual r0 = y, index set Sparse approximation solution Iteration number t = 1; Iteration: In the tth iteration, find the residual r t-1 and column a of the delay-Doppler domain overcomplete dictionary A j The index corresponding to the maximum value of Lp correlation Expand the index set to Λ t =Λ t-1 ∪j t , records the set of reconstructed atoms found in the dictionary matrix Solving the Lp norm minimization problem yields Update residual Repeat the above iterative process, with t=t+1 for each iteration, until t>K is satisfied; Output: Sparse approximation of the delay-Doppler double-extended channel h According to the sparse approximation value Determine the delay-Doppler dual-extended channel estimation result h'.

2. A delay-Doppler dual-extended channel estimation device under ice source noise according to the method of claim 1, characterized in that: include: The channel model unit is configured to be based on the number of multipaths K and the Doppler coefficient d of the sparse multipath channel. k , delay τ k , amplitude α k Constructing a delay-Doppler dual-extended channel model in; The Doppler spread factor is v k is the relative speed between the transmitter and the receiver, c is the speed of sound, d k =1+d k ′; A dictionary unit is configured to construct an overcomplete dictionary for the received signal y based on the transmitted signal x, and reconstruct the overcomplete dictionary using the Doppler coefficient to obtain an overcomplete dictionary in the delay-Doppler domain Transmitted signal x = [x(0), x(1), L, x(M)] T , the signal length is M+1, when the Doppler coefficient is d i When dictionary item A i Including delay domain elements and Doppler domain elements: The signal receiving unit is configured to determine that the received signal y is the product y=Ah of the delay-Doppler domain overcomplete dictionary A and the delay-Doppler double extended channel h, and the delay-Doppler double extended channel estimation problem is to solve the equation y=Ah; The iterative solution unit is configured to use the orthogonal matching pursuit method and use the Lp norm correlation as the correlation to perform multiple iterations to solve y=Ah Until t>K is satisfied to obtain the sparse approximation value Perform the following steps: Input: delay-Doppler domain overcomplete dictionary A, received signal y, multipath number K; Initialization: residual r0 = y, index set Sparse approximation solution Iteration number t = 1; Iteration: In the tth iteration, find the residual r t-1 and column a of the delay-Doppler domain overcomplete dictionary A j The index corresponding to the maximum value of Lp correlation Expand the index set to Λ t =Λ t-1 ∪j t , records the set of reconstructed atoms found in the dictionary matrix Solving the Lp norm minimization problem yields Update residual Repeat the above iterative process, with t=t+1 for each iteration, until t>K is satisfied; Output: Sparse approximation of the delay-Doppler double-extended channel h The output unit is configured to approximate the value according to the sparse Determine the delay-Doppler dual-extended channel estimation result h'.

3. A computer storage medium, characterized in that: The computer storage medium stores instructions, and when the instructions are executed, the delay-Doppler dual extension channel estimation method under ice source noise according to claim 1 is implemented.

4. A computing device, characterized in that It includes a processor and a communication interface coupled to the processor; the processor is used to run a computer program or instruction to implement the delay-Doppler dual extension channel estimation method under ice source noise according to claim 1.

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