CN115208482B - Underwater acoustic communication method under polar impulse interference - Google Patents

Underwater acoustic communication method under polar impulse interference Download PDF

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CN115208482B
CN115208482B CN202210770505.0A CN202210770505A CN115208482B CN 115208482 B CN115208482 B CN 115208482B CN 202210770505 A CN202210770505 A CN 202210770505A CN 115208482 B CN115208482 B CN 115208482B
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CN115208482A (en
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葛威
贾亦真
殷敬伟
韩笑
郭龙祥
生雪莉
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Harbin Engineering University
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    • H—ELECTRICITY
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    • H04B13/02—Transmission systems in which the medium consists of the earth or a large mass of water thereon, e.g. earth telegraphy
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H04L25/0202—Channel estimation
    • H04L25/0212—Channel estimation of impulse response
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
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    • H04L25/03178—Arrangements involving sequence estimation techniques
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    • H04L25/0328—Arrangements for operating in conjunction with other apparatus with interference cancellation circuitry
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    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03178—Arrangements involving sequence estimation techniques
    • H04L25/03305—Joint sequence estimation and interference removal
    • H—ELECTRICITY
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    • H04L2025/0335—Arrangements for removing intersymbol interference characterised by the type of transmission
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Abstract

The invention provides an underwater acoustic communication method under polar region pulse interference, which belongs to the field of polar region underwater acoustic communication and is used for modulating communication information to a carrier phase based on a single carrier phase shift keying modulation system. The decoding process of the communication signal at the receiving end is as follows: firstly, pulse detection is carried out, and pulse interference in a received signal is reconstructed; the signal is processed in a block mode, interference reconstruction and elimination are carried out on the received signal under the least square criterion through a method of iterative interference estimation elimination and time domain equalization, and time domain equalization is carried out; and based on the equalized symbols, obtaining estimated values of channels, interference and symbols by adopting a joint estimation algorithm based on combination of sparse Bayesian learning and a least square method. The invention has the advantages that (1) the time domain is processed in a blocking way, the real-time performance of the system is ensured, and the method can be applied to an underwater sound time-varying channel; (2) good robustness in an impulse noise environment; (3) While ensuring the performance, the blocking process reduces the computational complexity of joint estimation.

Description

Underwater acoustic communication method under polar impulse interference
Technical Field
The invention relates to an underwater acoustic communication method with stable communication performance and acceptable calculation complexity under polar region pulse interference, and belongs to the field of polar region underwater acoustic communication.
Background
The arctic region is covered by ice and snow all the year round, and due to the fact that an ice layer is broken or extruded, a large amount of pulse noise exists, so that background noise does not only obey Gaussian distribution, and the performance of the underwater acoustic communication system is seriously reduced. The single carrier modulation system, as one of the preferred schemes for realizing high-speed underwater acoustic communication, has advantages over the OFDM system in terms of peak-to-average power ratio and carrier frequency offset resistance, but at present, research on impulse interference suppression is mainly focused on the OFDM system, and impulse interference suppression methods for the single carrier modulation system are few, so that a robust single carrier communication method under impulse interference is urgently needed to be designed.
The pulse interference belongs to full-frequency-band interference with short duration, the energy of the pulse interference is far higher than the average energy of signals, the time of occurrence of the pulse interference in the received signals is random, short-time distortion is caused to waveforms, and a filter cannot completely filter out the signals, so that the communication performance is seriously influenced. The duration of a data block of single carrier time domain communication is often much longer, except for the influence of random time pulse interference, the channel time-varying phenomenon cannot be avoided, and the conventional decision feedback equalizer ignores the phenomenon in the equalization process, so that the performance is sharply reduced, and the method is not suitable for the current scene any more.
Disclosure of Invention
The invention aims to improve the robustness of an underwater sound single carrier communication system under polar impulse interference, and provides an underwater sound communication method under polar impulse interference, which is a single carrier communication method for carrying out signal processing in a time domain. The method combines the block iterative time domain equalization and the joint estimation to eliminate the interference and the channel equalization, and then performs the joint estimation of the channel and the symbol on the output signal, and simultaneously estimates and eliminates the interference again, thereby improving the communication robustness under the pulse interference and being suitable for the time-varying channel, and reducing the calculation complexity of the joint estimation through the block processing.
The purpose of the invention is realized by the following steps:
an underwater acoustic communication method under polar impulse interference is based on a single carrier phase shift keying modulation system to modulate communication information to a carrier phase, and a receiving end signal decoding step is as follows:
step 1: preprocessing the signal and outputting a training part signal y tr And a block signal y b ；
And 2, step: training part signal y output in step 1 tr And a block signal y b Detecting and parameterizing pulse interference and outputting a parameter matrix Lambda tr Γ tr And Λ b Γ b ；
And step 3: based on the training part signal y in step 1 tr Ginseng in step 2Number matrix Λ tr Γ tr And the transmitted training sequence is used for channel estimation, and the channel estimation result is output
Figure BDA0003723792570000011
And 4, step 4: based on the channel estimation result output in step 3
Figure BDA0003723792570000021
Symbol obtained by iteration of i-1
Figure BDA0003723792570000022
Finishing the estimation and elimination of interference, outputting the signal z after the pulse interference elimination b ；
And 5: method for obtaining balanced symbols by time domain equalization
Figure BDA0003723792570000023
And 6: judging whether the maximum iteration times is reached, if not, repeating the steps 4 and 5 until the times are met, ending the iteration, and outputting the balanced symbol
Figure BDA0003723792570000024
And 7: based on the equalized symbols output in step 6
Figure BDA0003723792570000025
And the block signal y output in step 1 b Performing joint estimation on a channel and a symbol by adopting a sparse Bayesian learning method, estimating and eliminating pulse interference again by adopting a least square method, and outputting a final estimated symbol D of a current block;
and 8: combining the outputs of all blocks to obtain the final estimated symbol
Figure BDA0003723792570000026
And decoding is carried out.
The signal preprocessing in the step 1 specifically comprises the following steps: after construction of the pretreatmentReceiving a signal model comprising a training part signal y tr And information-transmitting signal, partitioning the information-transmitting signal, constructing information-signal block model, signal processing, and outputting training part signal y tr And a block signal y b ；
The step 2 specifically comprises the following steps: in the training part signal y tr And a block signal y b Detecting the existence of impulse interference and the start and end time, and respectively using the detection result to train partial signal y tr And a block signal y b In (a) randomly occurring impulse interference i tr 、i b Parameterized interference is Λ tr Γ tr u tr 、Λ b Γ b u b ，Λ tr Γ tr And Λ b Γ b For parameterizing the coefficients, u tr 、u b Are the interference samples.
The channel estimation in step 3 is divided into channel estimation in the presence and absence of interference, and when interference exists, the partial signal y is trained based on step 1 tr Step 2 parameterized interference Λ tr Γ tr u tr And the transmitted training symbol P carries out channel estimation; training the partial signal y based on step 1 only when no interference is present tr And the transmitted training symbol P carries out channel estimation, and the final output channel estimation result under the two conditions is
Figure BDA0003723792570000027
The step 4 specifically comprises the following steps: in the ith iteration, based on the channel estimation result output in step 3
Figure BDA0003723792570000028
Expected symbol output from the i-1 th iteration
Figure BDA0003723792570000029
Reconstructing the block signal and outputting the block signal y from step 1 b Subtracting, and obtaining the estimated value of the interference sample by a least square method
Figure BDA00037237925700000210
The estimate of the interference sample is then used
Figure BDA00037237925700000211
Corresponding parameterized coefficient Λ output from step 2 b Γ b Multiplying, from the block signal y b Middle reduction, interference elimination, output of eliminated signal z b 。
The step 4 and the step 5 form an iterative pulse interference estimation elimination and time domain equalization structure, the iterative pulse interference estimation elimination and time domain equalization structure is used for carrying out independent processing on each block of signal, in the processing process, the equalization symbol output by the i-1 iteration is used for reconstructing the block signal in the ith iteration of the current block, interference estimation and elimination are carried out, then the signal is output to a time domain equalization part, the time domain equalization is carried out on the block signal by a method of connecting a decision feedback equalizer after a time reversal mirror until the iteration times are met, and the equalization result of the current block is output
Figure BDA0003723792570000031
The step 7 specifically comprises the following steps: based on the equalized symbols output in step 6
Figure BDA0003723792570000032
Equalized symbol to be output per block
Figure BDA0003723792570000033
Composition matrix
Figure BDA0003723792570000034
The structure is as follows:
Figure BDA0003723792570000035
wherein, N b Is the subblock length, L is the channel length;
performing joint estimation on a channel and a symbol by using a sparse Bayesian learning method, and estimating and eliminating pulse interference again by using a least square method;
firstly, by using the sparsity of the channel, assuming that the sparsity obeys a Gaussian distribution with a mean value of 0 and a variance of α, the estimation result of the channel is as follows:
Figure BDA0003723792570000036
wherein, Σ is the variance of the posterior distribution,
Figure BDA0003723792570000037
is the variance of Gaussian noise, B b ＝Λ b Γ b ，，
Figure BDA0003723792570000038
Symbol output by iterative interference estimation cancellation and time domain equalization
Figure BDA0003723792570000039
Formed matrix, the channel estimation result is
Figure BDA00037237925700000310
Estimating interference by using a least square idea to obtain estimation of the interference:
Figure BDA00037237925700000311
finally, let symbol vector D be
Figure BDA00037237925700000312
By calculating
Figure BDA00037237925700000313
To obtain
Figure BDA00037237925700000314
To obtain the value of the symbol vector D.
The invention provides an underwater acoustic communication method under polar impulse interference, which is creatively realized by carrying out iterative interference elimination and time domain equalization in blocks aiming at impulse interference occurring in a time-varying channel and random time, adding a joint estimation step after an iterative structure, carrying out joint estimation on a channel and a symbol, estimating and eliminating the interference again, effectively realizing impulse interference suppression and symbol estimation, improving the robustness of communication, further eliminating the interference in real time, reducing the complexity and realizing high-performance decoding on single carrier communication data under the impulse interference.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides an underwater acoustic communication method under polar impulse interference, which is based on a single carrier system, performs preliminary interference elimination through the steps of blocking iterative interference elimination and time domain equalization, performs residual interference elimination again through the step of joint estimation based on symbols output by iterative processing, and outputs final estimated symbols.
(1) Improving reliability of communications
The reliability of communication is highly correlated with the performance of the data processing method. Under the condition that the channel is time-varying or impulse interference exists in the environment, the conventional time domain equalizer processes the whole frame signal, interference elimination is not performed in the processing process, the equalization effect is extremely poor, and the communication reliability is seriously reduced. The invention adopts the method of blocking iterative interference elimination and time domain equalization, the duration time of each block of signals is less than the coherence time of a channel, the time-varying phenomenon of the channel is effectively dealt with through blocking processing, and simultaneously, the pulse interference occurring in random time is eliminated. And then, based on the result of iterative output, joint estimation is carried out again, and the reliability of communication is effectively improved.
(2) Improve the real-time performance of the system and reduce the calculation amount
The time domain block can be processed after the receiving end receives a single block signal, but the processing step is carried out only when the receiving end receives a whole frame signal, so that the real-time performance of the system is improved. Meanwhile, in the joint estimation, the signal dimension is reduced, and the calculation complexity of the system is effectively reduced, so that the calculation amount is reduced.
Drawings
In order to more clearly illustrate the technical solution in the embodiments of the present invention, the drawings used in the description of the embodiments are briefly introduced below. The drawings described below are for some embodiments of the invention and others will occur to those skilled in the art without the use of the innovative teachings herein, in which:
FIG. 1 is a flow chart of a method of underwater acoustic communication under polar impulse interference;
FIG. 2 is a signal block diagram;
FIG. 3 (a) is a time domain plot of impulse noise collected at the north pole;
FIG. 3 (b) is a time-frequency diagram of impulse noise collected at the north pole;
fig. 4 shows the error performance of different methods in arctic-icy impulse interference environments, with interference present, signal-to-interference ratio-20 dB, and no interference present.
Detailed Description
The invention is described in further detail below, by way of example, with reference to the accompanying drawings.
The underwater acoustic communication method under polar impulse interference provided by the invention has the working flow as shown in fig. 1, and the specific implementation mode is as follows:
step 1: inputting a receiving signal of a passband, preprocessing the signal, constructing a preprocessed receiving signal model, wherein the model comprises a training part signal and a signal for transmitting information, blocking the signal for transmitting the information, constructing a block model of the information signal, processing the signal, and outputting the training part signal and the block signal;
the received signal preprocessing in step 1 requires doppler estimation and compensation of the received signal, demodulation of the received signal to baseband, and division of the information signal into N bl The block and signal block are schematically shown in fig. 2, the overlapping part between blocks is the same as the channel length, and the estimated symbol output in the previous block is used in the iterative time domain equalization step of step 5. Output training part signal y tr And the signal y after the block b For further processing.
And 2, step: detecting the existence of pulse interference and the starting time and the ending time of the pulse interference in the training part signal and the blocking signal output in the step 1 respectively, carrying out interference parameterization and outputting parameterized interference;
the pulse interference parameterization in the step 2 is to simultaneously detect pulse interference, interference starting and receiving time in the training part signals and the block signals, and respectively detect the pulse interference i randomly appearing in the training part signals and the block signals by using the detection results tr 、i b Parameterization of Λ tr Γ tr u tr 、Λ b Γ b u b ，Λ tr Γ tr And Λ b Γ b For parameterized coefficients, u tr 、u b For disturbing sample values, output Λ tr Γ tr And Λ b Γ b 。
And 3, step 3: performing channel estimation based on the training part signals in the step 1, the parameterized interference in the step 2 and the transmitted training sequence, and outputting a channel estimation result;
the channel estimation process described in step 3 can be subdivided into channel estimation in the presence and absence of interference, and in the presence of interference, the partial signal y is trained based on step 1 tr Step 2, parameterization interference model Lambda tr Γ tr u tr And the transmitted training symbol P carries out channel estimation; training partial signal y based on step 1 only when interference is not present tr And the transmitted training symbols P are used for channel estimation. The final output channel estimation results in both cases
Figure BDA0003723792570000051
And 4, step 4: and 5, forming an iterative impulse interference estimation elimination and time domain equalization structure together. Finishing the estimation and elimination of interference based on the channel estimation result output in the step 3 and the symbol obtained by the previous iteration, and outputting a signal after pulse interference elimination;
the pulse interference estimation and elimination in the step 4 and the step 5 jointly form an iterative structure, and in the ith iteration, the channel estimation result output in the step 3 is based on
Figure BDA0003723792570000052
Expected symbol output from the i-1 st iteration
Figure BDA0003723792570000053
Reconstructing the block signal and outputting the block signal y from step 1 b And (4) subtracting. Obtaining an estimate of an interference sample by a least squares method
Figure BDA0003723792570000054
Then the estimated interference and the corresponding parameterized coefficient Lambda output in step 2 are carried out b Γ b Multiplication, from block signal y b Middle reduction, interference elimination, output of the eliminated signal z b 。
And 5: based on the signal obtained in the step 4 after the pulse interference is eliminated, obtaining an equilibrium symbol by a time domain equilibrium method;
step 5, the time domain equalization step is to eliminate the interference of the signal z in step 4 b And (6) carrying out equalization. The difference between the step and the traditional method is that the interference is eliminated before equalization, an iterative structure is selected in the process, and the symbol is continuously updated after equalization, so that the performance of the method is greatly improved. Outputting the equalized symbol in the ith iteration
Figure BDA0003723792570000055
And 6: judging whether the maximum iteration times is reached, if not, repeating the steps 4 and 5 until the times are met, ending the iteration, and outputting the balanced symbols;
the judgment step in the step 6 is iteration frequency judgment of iterative interference elimination and time domain equalization, the maximum iteration frequency Iter is not reached, the steps 4 and 5 are repeated until the symbol after the current block equalization is output after the iteration frequency is reached
Figure BDA0003723792570000056
And 7: based on the equalized symbol output in the step 6 and the block signal output in the step 1, performing joint estimation on a channel and a symbol in the step, estimating and eliminating residual impulse interference again, and outputting a final estimated symbol of a current block;
the iterative structure formed by the joint estimation part in the step 7 and the steps 4, 5 and 6 is the core of the invention. Joint estimation of output symbols based on an iterative structure
Figure BDA0003723792570000061
Forming the symbols output in each block into a matrix
Figure BDA0003723792570000062
The structure is as follows:
Figure BDA0003723792570000063
wherein, N b Is the subblock length and L is the channel length. And (3) performing joint estimation on the channel and the symbol by using a sparse Bayesian learning method, and estimating and eliminating the interference again.
Firstly, the channel obeys Gaussian distribution with variance alpha, and the channel is estimated again by estimating posterior distribution thereof to obtain an estimation result:
Figure BDA0003723792570000064
Figure BDA0003723792570000065
wherein Σ is the variance of the posterior distribution,
Figure BDA0003723792570000066
is the variance of Gaussian noise, B b ＝Λ b Γ b The channel is estimated as
Figure BDA0003723792570000067
Then, the estimated channel result is used to estimate the interference again
Figure BDA0003723792570000068
Obtaining the above estimateAfter a value, the estimation of the symbol can be considered to satisfy the following expression:
Figure BDA0003723792570000069
solving the formula to obtain a symbol vector D estimated by the current block, wherein D is a matrix
Figure BDA00037237925700000610
In the first column, the step of joint estimation is completed, and D is output.
And step 8: and combining the output symbols of all the blocks, outputting the final estimated symbol and decoding.
Combining the output symbols of all blocks as described in step 8 means combining N bl All the symbols output after the block is processed by the steps 2-7 to obtain the final estimated symbol
Figure BDA00037237925700000611
And decoding is carried out.
The advantages of the present invention will be further explained in conjunction with the results of the test data processing. It is to be understood that the experimental results described are a part of the examples of the present invention, and not all of the examples, and are intended only to illustrate and explain the present invention, and not to limit the present invention. All other embodiments, which can be obtained by a person skilled in the art without inventive effort based on the results of the processing of the test data in the present invention, shall fall within the scope of protection of the present invention.
Test data verification:
the test conditions are as follows: the method provided by the invention is used for processing test data and verifying the performance of the method provided by the invention. The impulse noise collected during the ninth arctic scientific investigation period shown in fig. 3 (a) and (b) is added to the communication data collected in the data form test, fig. 3 (a) is a time domain diagram of the impulse noise, and fig. 3 (b) is a time-frequency diagram of the impulse noise. In the processing process, gaussian noise is artificially added to change the signal-to-noise ratio of a received signal, and the error code performance of several methods under different signal-to-noise ratios is observed. The communication parameters in the experiment were as follows: the length of each frame of single carrier signal is 1000 symbols, 500 symbols are used as training sequence, and data is channel coded by 1/2 convolutional code. The carrier center frequency was 6kHz, the bandwidth was 2kHz, and the passband sampling rate was 48kHz. QPSK mapping is used.
And (3) analysis of test results: when there is arctic under-ice impulse interference in the received signal, the experimental data processing results are shown in fig. 4. Fig. 4 shows the bit error rate of the proposed method compared to the conventional method in the presence of interference, signal to interference ratio of-20 dB and in the absence of interference. The closer the curve to the x-axis indicates that the lower the bit error rate at the same signal-to-noise ratio, the more reliable the communication. In fig. 4, the first three curves show that when there is interference and the signal-to-interference ratio is-25 dB, the error rate results obtained by processing test data with the conventional method, the method of iterative interference cancellation and time domain equalization only proposed in the present invention, and the complete communication receiving end signal processing method proposed in the present invention (which refers to a method of iterative interference cancellation, time domain equalization and joint estimation step existing at the same time) are compared, and the results show that the method proposed in the present invention performs the interference cancellation step in the processing process, and simultaneously performs the interference cancellation and symbol updating continuously, so that the decoding error rate of data under all signal-to-noise ratios is significantly reduced, the performance is superior to that of the conventional method, and the joint estimation step is added, so that the method further cancels the interference on the basis of iteration, and the performance is optimal.
The two curves at the bottom are the comparison of the error rate results of data processing by using a traditional method and the complete communication receiving end signal processing method provided by the invention when no interference exists, the figure shows that when no interference exists, the signal distortion is small, the performance of the two methods is the performance when the interference exists, and the complete communication receiving end signal processing method provided by the invention has the optimal performance compared with the traditional method when the interference does not exist.
The analysis of the test results can obtain that the data processing performance of the method provided by the invention under the pulse interference and in the non-interference state is completely superior to that of the traditional method, and the method can be suitable for the scene of the pulse interference in the polar region.
The invention relates to an underwater acoustic communication method with stable communication performance and acceptable calculation complexity under polar region pulse interference, and belongs to the field of polar region underwater acoustic communication. The invention is realized by the following technical scheme: considering a single-carrier transmission system, communication information is modulated to a carrier phase based on a single-carrier phase shift keying modulation system. The decoding process of the communication signal at the receiving end is as follows: firstly, pulse detection is carried out, and pulse interference in a received signal is reconstructed. The randomness of the occurrence time of the impulse interference and the time-varying characteristic of a channel are considered, the signal is processed in a blocking mode, interference reconstruction and elimination are carried out on the received signal under the least square criterion through the method of iterative interference estimation elimination and time domain equalization, and the time domain equalization is carried out. Due to channel estimation errors and noise, the effects of impulse interference cannot be completely eliminated. And then, based on the equalized symbols, obtaining estimated values of the channel, the interference and the symbols by adopting a joint estimation algorithm based on combination of sparse Bayesian learning and a least square method. The invention has the advantages that (1) the time domain is processed in a block mode, the real-time performance of the system is ensured, and the method can be applied to an underwater acoustic time-varying channel; (2) the robustness is good in the impulse noise environment; (3) While ensuring the performance, the blocking process reduces the computational complexity of joint estimation.

Claims (5)

1. An underwater acoustic communication method under polar impulse interference is characterized in that: based on a single carrier phase shift keying modulation system, the communication information is modulated to a carrier phase, and the decoding steps of the signals at the receiving end are as follows:
step 1: preprocessing the signal and outputting a training part signal y tr And a block signal y b ；
And 2, step: training part signal y output in step 1 tr And a block signal y b Carrying out pulse interference detection and parameterization and outputting a parameterization coefficient lambda tr Γ tr And Λ b Γ b ；
And 3, step 3: based on the training part signal y in step 1 tr Parameterized coefficient Λ in step 2 tr Γ tr And the transmitted training symbol P carries out channel estimation and outputs the channel estimation result
Figure FDA0003962133890000011
And 4, step 4: based on the channel estimation result output in step 3
Figure FDA0003962133890000012
Expected symbol output from the i-1 th iteration
Figure FDA0003962133890000013
Reconstructing the block signal and outputting the block signal y from step 1 b Subtracting, and obtaining the estimated value of the interference sample by a least square method
Figure FDA0003962133890000014
Then estimating the interference sample
Figure FDA0003962133890000015
Corresponding parameterized coefficient Lambda output in step 2 b Γ b Multiplication, from block signal y b Middle reduction, interference elimination, output of signal z after pulse interference elimination b ；
And 5: for the signal z after the impulse interference elimination in the step 4 b Performing time domain equalization, and outputting equalized symbol in the ith iteration
Figure FDA0003962133890000016
And 6: judging whether the maximum iteration times is reached, if not, repeating the steps 4 and 5 until the times are met, ending the iteration, and outputting the balanced symbol
Figure FDA0003962133890000017
And 7: based on the equalized symbols output in step 6
Figure FDA0003962133890000018
And the block signal y output in step 1 b Performing joint estimation on a channel and a symbol by adopting a sparse Bayesian learning method, estimating and eliminating pulse interference again by adopting a least square method, and outputting a final estimated symbol D of a current block;
the method comprises the following specific steps: equalized symbol based on step 6 output
Figure FDA0003962133890000019
Equalized symbol to be output per block
Figure FDA00039621338900000110
Composition matrix
Figure FDA00039621338900000111
The structure is as follows:
Figure FDA00039621338900000112
wherein N is b Is the subblock length, L is the channel length;
performing joint estimation on a channel and a symbol by using a sparse Bayesian learning method, and estimating and eliminating pulse interference again by using a least square method;
firstly, by using the sparsity of the channel, assuming that the sparsity obeys a Gaussian distribution with a mean value of 0 and a variance of α, the estimation result of the channel is as follows:
Figure FDA0003962133890000021
wherein, Σ is the variance of the posterior distribution, u b In order to disturb the samples,
Figure FDA0003962133890000022
is the variance of Gaussian noise, B b ＝Λ b Γ b ，
Figure FDA0003962133890000023
Symbol output by iterative interference estimation cancellation and time domain equalization
Figure FDA0003962133890000024
Formed matrix, the channel estimation result is
Figure FDA0003962133890000025
Estimating interference by using a least square idea to obtain estimation of the interference:
Figure FDA0003962133890000026
finally, let symbol vector D be
Figure FDA0003962133890000027
By calculating
Figure FDA0003962133890000028
To obtain
Figure FDA0003962133890000029
Thereby obtaining the value of the symbol vector D;
and 8: combining the outputs of all blocks to obtain the final estimated symbol
Figure FDA00039621338900000210
And decoding is carried out.
2. The method of claim 1, wherein the method comprises: the step 4 and the step 5 form an iterative impulse interference estimation elimination and time domain equalization structure, the iterative impulse interference estimation elimination and time domain equalization structure carries out independent processing on each block of signals, in the processing process, in the ith iteration of the current block, the equalization symbol output by the (i-1) th iteration is used for reconstructing the block signals, interference estimation and elimination are carried out, then the signals are output to a time domain equalization part, a time reversal mirror is used and then a judgment reversal mirror is connectedThe method of the feed equalizer carries out time domain equalization on the block signals until the iteration times are met, and outputs the equalization result of the current block
Figure FDA00039621338900000211
3. The underwater acoustic communication method under polar impulse interference according to claim 1, wherein: the signal preprocessing in the step 1 specifically comprises the following steps: constructing a preprocessed received signal model, wherein the model comprises a training part signal y tr And information-transmitting signal, partitioning the information-transmitting signal, constructing information-signal block model, signal processing, and outputting training part signal y tr And a block signal y b 。
4. The method of claim 3, wherein the underwater acoustic communication under polar impulse interference comprises: the step 2 specifically comprises the following steps: in the training part signal y tr And a block signal y b Detecting the existence of impulse interference and the start and end time, and respectively using the detection result to train part signals y tr And a block signal y b In (a) randomly occurring impulse interference i tr 、i b Parameterized interference of Λ tr Γ tr u tr 、Λ b Γ b u b ，Λ tr Γ tr And Λ b Γ b For parameterized coefficients, u tr 、u b Are the interference samples.
5. The method of claim 4 for underwater acoustic communication under polar impulse interference, wherein: the channel estimation in step 3 is divided into channel estimation in the presence and absence of interference, and when interference exists, the partial signal y is trained based on step 1 tr Step 2 parameterized interference Λ tr Γ tr u tr And the transmitted training symbol P carries out channel estimation; training the partial signal y based on step 1 only when no interference is present tr And the transmitted training symbol P for channel estimation, in both casesThe final output channel estimation results are all
Figure FDA0003962133890000031
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