A frequency domain array processing method for underwater acoustic single-carrier communication based on ultra-short baseline array

Abstract

This invention discloses a frequency domain array processing method for underwater acoustic single-carrier communication based on an ultra-short baseline array, belonging to the field of underwater acoustic communication. This invention solves the problem of poor reliability in existing communication systems based on ultra-short baseline receiver arrays. The invention employs a high-precision delay estimation method from underwater acoustic positioning to refine the propagation delay of M receiving channels, eliminating the influence of different fractional delays on the channel estimation results of each channel. The signal-to-noise ratio (SNR) after multi-channel merging is compared with the SNR of a single channel to obtain the conditions required for equal-gain selective merging of multiple channels. Based on the channel merging conditions, it determines whether the standard channel and candidate channels should be merged, thereby continuously improving the received signal-to-noise ratio, obtaining spatial diversity gain, improving the reliability of the communication system, and effectively avoiding inter-channel interference in traditional methods. This invention can be applied to frequency domain array processing of underwater acoustic single-carrier communication using ultra-short baseline arrays.

Description

Technical Field

[0001] This invention belongs to the field of underwater acoustic communication, specifically relating to a frequency domain array processing method for underwater acoustic single-carrier communication based on an ultra-short baseline array. Background Technology

[0002] Underwater acoustic communication, which uses sound waves as a carrier, is an important technology for information transmission between different underwater nodes. However, underwater acoustic channels are among the most complex wireless channels, exhibiting significant fading characteristics. To address inter-symbol interference caused by multipath channels, equalization techniques are often used at the receiver to compensate for this effect. Furthermore, to improve the equalization performance of communication systems, existing underwater acoustic communication technologies have evolved to include multi-channel reception.

[0003] The characteristics of ultra-short baseline (USBR) receiver arrays are their small size, typically ranging from a few centimeters to tens of centimeters. Their transducers are closely spaced, resulting in strong consistency across all receiving channels. Unlike traditional multi-channel receiving technologies in underwater acoustic communication, the strong consistency of USBR array channels is primarily reflected in two aspects: channel consistency and received signal power consistency. Strong channel consistency means that the channel structure between channels has only a time delay deviation, typically not exceeding one symbol length, which significantly impacts traditional multi-channel equalization. Strong received signal power consistency means that the signal power is the same across all receiving channels, although there is a problem of inconsistent noise levels. Therefore, the reliability of existing communication systems based on USBR receiver arrays remains relatively poor, requiring targeted design to fully leverage the processing advantages of USBR arrays and further improve the reliability of communication systems. Summary of the Invention

[0004] The purpose of this invention is to solve the problem of poor reliability in existing communication systems based on ultra-short baseline receiving arrays, and to propose a frequency domain array processing method for underwater acoustic single-carrier communication based on ultra-short baseline arrays.

[0005] The technical solution adopted by the present invention to solve the above-mentioned technical problems is: a frequency domain array processing method for underwater acoustic single-carrier communication based on ultra-short baseline array, the method specifically includes the following steps:

[0006] Step 1: Each element in the ultra-short baseline array simultaneously receives a single-carrier underwater acoustic transmission signal and preprocesses the received single-carrier underwater acoustic signal to obtain the preprocessed signal for each channel.

[0007] Step 2: Each channel performs frame synchronization on the preprocessed signal and extracts the speed measurement signal of each channel based on the frame synchronization result;

[0008] For any given channel, the signal-to-noise ratio of that channel is estimated based on the frame synchronization result of that channel, the velocity within that channel is estimated based on the velocity measurement signal of that channel, and Doppler compensation is performed on the frame synchronization result of that channel based on the velocity estimation result within that channel, to obtain the Doppler-compensated signal of that channel.

[0009] Similarly, the signal-to-noise ratio estimation results for each channel and the signal after Doppler compensation are obtained separately.

[0010] Step 3: Perform symbol synchronization on the Doppler-compensated signal of each channel and extract the information sequence within each channel;

[0011] Step 4: Estimate the fractional delay based on the frame synchronization results for each channel;

[0012] For any channel, after processing the information sequence within that channel, the fractional delay estimation result of that channel is used to compensate for the fractional delay of the processing result, thus obtaining the fractional delay compensated signal of that channel.

[0013] Similarly, the fractional delay compensated signals for each channel are obtained separately.

[0014] Step 5: Based on the signal-to-noise ratio (SNR) estimation results of each channel obtained in Step 2, select the channel with the highest SNR as the standard channel and the other channels as alternative channels.

[0015] The signals after fractional delay compensation for the standard channel and each alternative channel are downsampled to obtain the downsampled signals of each channel. Then, channel estimation is performed based on the downsampled signal of the standard channel, and the channel estimation results are used as equalization coefficients.

[0016] Step 6: Select the candidate channels that meet the merging conditions based on the signal-to-noise ratio of the standard channel and each candidate channel;

[0017] Step 7: Process the downsampled signals from the standard channel and each of the candidate channels selected in Step 6, specifically as follows:

[0018] For any candidate channel selected in step six, perform FFT transformation on the downsampled signal of the candidate channel, and then use the equalization coefficients calculated in step five to perform frequency domain equalization on the FFT transformed signal to obtain the frequency domain equalized signal of the candidate channel.

[0019] Similarly, the frequency-equalized signals of the standard channel and each candidate channel selected in step six are obtained separately.

[0020] Step 8: Combine the frequency domain equalized signals of the standard channel and each candidate channel selected in Step 6, and then perform IFFT transformation on the combined signal to obtain the restored signal.

[0021] Furthermore, the preprocessing method in step one is bandpass filtering.

[0022] Furthermore, the specific process of processing the information sequence within the channel in step four is as follows:

[0023] The information sequence is then down-converted and low-pass filtered sequentially.

[0024] Furthermore, the estimation of fractional delay based on the frame synchronization results of each channel uses a three-point interpolation method.

[0025] Furthermore, the specific process of the fractional delay estimation is as follows:

[0026] For any channel, the peak region waveform of the frame synchronization result for that channel is fitted, and the fitted waveform function is:

[0027] r(t) = Acos(wt) + Bsin(wt)

[0028] Where t represents time, w represents the oscillation angular frequency, and A and B represent the coefficients of the fitted waveform function;

[0029] Let the peak point in the frame synchronization result be denoted as r2, where r2 = r(t2), and t2 is the time corresponding to the peak point. Select a sampling point t1 before the peak point and a sampling point t3 after the peak point, then we have:

[0030] r1=Acoswt1+Bsinwt1

[0031] r2=Acoswt2+Bsinwt2

[0032] r3=Acoswt3+Bsinwt3

[0033] Where r1 represents the waveform value corresponding to sampling point t1, and r3 represents the waveform value corresponding to sampling point t3, we can deduce:

[0034] 0 < wt s <π

[0035] r3 sinwt s =r2 sin2wt s -r1 sinwt s

[0036] Among them, t s Indicates the sampling interval, t s =1 / fs The value of the oscillation angular frequency is then:

[0037]

[0038] The fitted waveform function is then rearranged as follows:

[0039]

[0040] in:

[0041]

[0042] When wt = kπ + ψ, |r(t)| reaches its maximum value; where k is a positive integer and satisfies:

[0043]

[0044] Then, estimate the relevant peak time t0 based on the calculated k value:

[0045]

[0046] The fractional delay estimate τ for this channel is:

[0047] τ = t0 - t2.

[0048] Furthermore, the sampling points t1 and t3 satisfy t3-t2=t2-t1=1 / f s f s Indicates the sampling frequency, and f s >f0, where f0 represents the oscillation frequency of the frame synchronization result.

[0049] Furthermore, the channel estimation based on the downsampled signal of the standard channel adopts an RLS-based time-domain adaptive estimation algorithm.

[0050] Furthermore, the specific process of step six is ​​as follows:

[0051] Step 61: Sort the candidate channels in descending order of signal-to-noise ratio to obtain the sorting results;

[0052] Step 6.2: Denote the signal-to-noise ratio (SNR) of the first candidate channel in the sorting results as SNR1, and the SNR of the standard channel as SNR0. Determine whether SNR1 > SNR0 - 10lg3 is satisfied.

[0053] If SNR1 > SNR0 - 10lg3 is satisfied, then the first candidate channel in the sorting result is a candidate channel that meets the merging condition, and step six-three continues.

[0054] Otherwise, the first candidate channel in the sorting results is a candidate channel that does not meet the merging conditions, and there are no candidate channels that meet the merging conditions among the candidate channels;

[0055] Step 63: Initialize m = 2;

[0056] Step 64: Denote the signal-to-noise ratio (SNR) of the m-th candidate channel in the sorting results as SNR. m The signal-to-noise ratio (SNR) of the standard channel and the 1st, 2nd, ..., m-1th candidate channels in the sorting results is denoted as SNR. 012…m-1 , Determine if the following conditions are met:

[0057]

[0058] Among them, P s It is signal power. This is the noise power of the standard channel. This is the noise power of the first alternative channel. It is the noise power of the (m-1)th alternative channel. It is the noise power of the m-th alternative channel, SNR 12...m This represents the signal-to-noise ratio after merging the standard channel and the 1st, 2nd, ..., mth candidate channels in the sorting results;

[0059] Step 65: If SNR is satisfied 012...m >SNR 012...m-1 Then let m = m + 1, and return to step six four;

[0060] If SNR is not met 012...m >SNR 012...m-1 If the first, second, ..., m-1th candidate channels in the sorting results are the channels that meet the merging conditions.

[0061] Furthermore, the frequency domain equalization method employed is zero-forcing equalization or minimum mean square error equalization.

[0062] The beneficial effects of this invention are:

[0063] 1) This invention performs channel estimation only on one receiving channel and uses a high-precision time delay estimation method in underwater acoustic positioning to refine the propagation time delay of M receiving channels, eliminating the influence of different fractional time delays on the channel estimation results of each channel. This reduces the complexity of the system and improves the computational efficiency when performing multi-channel merging and equalization.

[0064] 2) This invention compares the signal-to-noise ratio of the multi-channel combined signal with that of the single channel to obtain the condition constraints required for the equal gain selection and combining of multiple channels. Based on the channel combining conditions, it determines whether the standard channel and the alternative channel should be combined, so as to continuously improve the signal-to-noise ratio of the received signal, obtain spatial diversity gain, improve the reliability of the communication system, and effectively avoid inter-channel interference of traditional methods. Attached Figure Description

[0065] Figure 1 This is a diagram of the transmitted signal frame structure of the present invention;

[0066] Figure 2 This is a flowchart of the receiving end of a frequency domain array processing method for underwater acoustic single-carrier communication based on an ultra-short baseline array according to the present invention.

[0067] Figure 3 This is a flowchart of the fractional delay compensation in this invention;

[0068] Figure 4 This is a flowchart illustrating the merging process between the standard channel and the candidate channel with the highest signal-to-noise ratio in this invention.

[0069] Figure 5 Simulation diagram of BER analysis for combined channels under AWGN channel;

[0070] Figure 6 This is a simulation diagram of the combined channel BER analysis under underwater acoustic channel. Detailed Implementation

[0071] Specific implementation method one: Combining Figure 2 and Figure 3 This embodiment describes a frequency domain array processing method for underwater acoustic single-carrier communication based on an ultra-short baseline array. The method specifically includes the following steps:

[0072] Step 1: Each element in the ultra-short baseline array simultaneously receives a single-carrier underwater acoustic transmission signal. The transmission signal frame structure is as follows: Figure 1 As shown, the received single-carrier underwater acoustic signal is preprocessed to obtain the preprocessed signal for each channel;

[0073] Step 2: Each channel performs frame synchronization on the preprocessed signal (that is, cross-correlates the preprocessed signal of each channel with the local known signal respectively), and extracts the speed measurement signal of each channel based on the frame synchronization result;

[0074] For any given channel, the signal-to-noise ratio of that channel is estimated based on the frame synchronization result of that channel, the velocity within that channel is estimated based on the velocity measurement signal of that channel, and Doppler compensation is performed on the frame synchronization result of that channel based on the velocity estimation result within that channel, to obtain the Doppler-compensated signal of that channel.

[0075] Similarly, the signal-to-noise ratio estimation results for each channel and the signal after Doppler compensation are obtained separately.

[0076] Step 3: Perform symbol synchronization on the Doppler-compensated signal of each channel and extract the information sequence in each channel (the cross-correlation peak position in each channel is the trailing edge of the synchronization signal, and then extract the information sequence part of the received signal from the cross-correlation peak position).

[0077] Step 4: Estimate the fractional delay based on the frame synchronization results for each channel;

[0078] For any channel, after processing the information sequence within that channel, the fractional delay estimation result of that channel is used to compensate for the fractional delay of the processing result, thus obtaining the fractional delay compensated signal of that channel.

[0079] Similarly, the fractional delay compensated signals for each channel are obtained separately.

[0080] Step 5: Based on the signal-to-noise ratio (SNR) estimation results of each channel obtained in Step 2, select the channel with the highest SNR as the standard channel and the other channels as alternative channels.

[0081] The signals after fractional delay compensation for the standard channel and each alternative channel are downsampled to obtain the downsampled signals of each channel. Then, channel estimation is performed based on the downsampled signal of the standard channel, and the channel estimation results are used as equalization coefficients.

[0082] Step 6: Select the candidate channels that meet the merging conditions based on the signal-to-noise ratio of the standard channel and each candidate channel;

[0083] Step 7: Process the downsampled signals from the standard channel and each of the candidate channels selected in Step 6, specifically as follows:

[0084] For any candidate channel selected in step six, perform FFT transformation on the downsampled signal of the candidate channel, and then use the equalization coefficients calculated in step five to perform frequency domain equalization on the FFT transformed signal to obtain the frequency domain equalized signal of the candidate channel.

[0085] Similarly, the frequency-equalized signals of the standard channel and each candidate channel selected in step six are obtained separately.

[0086] Step 8: Combine the frequency domain equalized signals of the standard channel and each candidate channel selected in Step 6, and then perform IFFT transformation on the combined signal to obtain the restored signal.

[0087] Each frame of signal received by the ultra-short baseline array is processed using the method of this invention.

[0088] Specific Implementation Method Two: This implementation method differs from Specific Implementation Method One in that the preprocessing method in step one is bandpass filtering.

[0089] The other steps and parameters are the same as in Specific Implementation Method 1.

[0090] Specific Implementation Method Three: This implementation method differs from Specific Implementation Method One or Two in that the specific process of processing the information sequence within the channel in step four is as follows:

[0091] The information sequence is then down-converted and low-pass filtered sequentially.

[0092] Other steps and parameters are the same as in specific implementation method one or two.

[0093] Specific Implementation Method Four: This implementation method differs from Specific Implementation Methods One to Three in that the estimation of fractional delay based on the frame synchronization results of each channel uses a three-point interpolation method.

[0094] The other steps and parameters are the same as those in one of the specific implementation methods one to three.

[0095] Specific Implementation Method Five: This implementation method differs from Specific Implementation Methods One to Four in that the specific process of fractional time delay estimation is as follows:

[0096] For any channel, the peak region waveform of the frame synchronization result for that channel is fitted, and the fitted waveform function is:

[0097] r(t) = Acos(wt) + Bsin(wt)

[0098] Where t represents time, w represents the oscillation angular frequency, w≈2πf0, f0 represents the oscillation frequency of the frame synchronization result, and A and B represent the coefficients of the fitted waveform function.

[0099] Let the peak point in the frame synchronization result be denoted as r2, where r2 = r(t2), and t2 is the time corresponding to the peak point. Select a sampling point t1 before the peak point and a sampling point t3 after the peak point, then we have:

[0100] r1=Acoswt1+Bsinwt1

[0101] r2=Acoswt2+Bsinwt2

[0102] r3=Acoswt3+Bsinwt3

[0103] Where r1 represents the waveform value corresponding to sampling point t1, and r3 represents the waveform value corresponding to sampling point t3, we can deduce:

[0104] 0 < wt s <π

[0105] r3 sinwt s =r2 sin2wt s -r1 sinwt s

[0106] Among them, t s Indicates the sampling interval, t s =1 / f s The value of the oscillation angular frequency is then:

[0107]

[0108] The fitted waveform function is then rearranged as follows:

[0109]

[0110] in:

[0111]

[0112] tg represents the tangent function, where |r(t)| reaches its maximum value when wt = kπ + ψ (k is a non-negative integer); where k is a positive integer and satisfies:

[0113]

[0114] Then, estimate the relevant peak time t0 based on the calculated k value:

[0115]

[0116] The fractional delay estimate τ for this channel is:

[0117] τ=t0-t2

[0118] The other steps and parameters are the same as those in one of the specific implementation methods one to four.

[0119] Specific Implementation Method Six: This implementation method differs from Specific Implementation Methods One to Five in that the sampling points t1 and t3 satisfy t3-t2=t2-t1=1 / f s f s Indicates the sampling frequency, and f s >f0, where f0 represents the oscillation frequency of the frame synchronization result.

[0120] The other steps and parameters are the same as those in one of the specific implementation methods one to five.

[0121] Specific Implementation Method Seven: This implementation method differs from Specific Implementation Methods One to Six in that the channel estimation based on the downsampled signal of the standard channel uses an RLS-based time-domain adaptive estimation algorithm.

[0122] The other steps and parameters are the same as those in one of the specific implementation methods one to six.

[0123] Specific implementation method eight: Combination Figure 4 This embodiment is described below. The difference between this embodiment and any one of specific embodiments one through seven is that the specific process of step six is ​​as follows:

[0124] Step 61: Sort the candidate channels in descending order of signal-to-noise ratio to obtain the sorting results;

[0125] Step 6.2: Denote the signal-to-noise ratio (SNR) of the first candidate channel in the sorting results as SNR1, and the SNR of the standard channel as SNR0. Determine whether SNR1 > SNR0 - 10lg3 is satisfied.

[0126] If SNR1 > SNR0 - 10lg3 is satisfied, then the first candidate channel in the sorting result is a candidate channel that meets the merging condition, and step six-three continues.

[0127] Where lg represents the logarithm to the base 10;

[0128] Otherwise, the first candidate channel in the sorting result is a candidate channel that does not meet the merging condition, and there is no candidate channel that meets the merging condition among the candidate channels (when the candidate channel with a large signal-to-noise ratio does not meet the merging condition, it is no longer necessary to judge the candidate channel with a small signal-to-noise ratio).

[0129] Step 63: Initialize m = 2;

[0130] Step 64: Denote the signal-to-noise ratio (SNR) of the m-th candidate channel in the sorting results as SNR. m The signal-to-noise ratio (SNR) of the standard channel and the 1st, 2nd, ..., m-1th candidate channels in the sorting results is denoted as SNR. 012...m-1 , Determine if the following conditions are met:

[0131]

[0132] Among them, P s It is signal power. This is the noise power of the standard channel. This is the noise power of the first alternative channel. It is the noise power of the (m-1)th alternative channel. It is the noise power of the m-th alternative channel, SNR 12...mThis represents the signal-to-noise ratio after merging the standard channel and the 1st, 2nd, ..., mth candidate channels in the sorting results;

[0133] Step 65: If SNR is satisfied 012...m >SNR 012...m-1 Then let m = m + 1, and return to step six four;

[0134] If SNR is not met 012...m >SNR 012...m-1 If the first, second, ..., m-1th candidate channels in the sorting results are the channels that meet the merging conditions.

[0135] The other steps and parameters are the same as those in any of the specific implementation methods one to seven.

[0136] The derivation process of the channel merging condition is as follows:

[0137] Assume the in-band signal-to-noise ratio of the signal from the m-th candidate channel after passing through the bandpass filter is:

[0138]

[0139] This leads to the relationship between noise power and signal power:

[0140]

[0141] When the signals from the standard channel and the first alternative channel are combined, since the signal power of the receiving array is consistent and the noise is independent, the signal-to-noise ratio (SNR) after equal gain combining can be obtained. 01 have:

[0142]

[0143] To achieve a signal-to-noise ratio (SNR) gain by combining the two paths, the SNR must be satisfied. 01 Since SNR is greater than 0, we can conclude that:

[0144]

[0145] Therefore, the channel merging condition can be obtained as follows:

[0146] SNR1 > SNR0 - 10lg3

[0147] The channels that meet this condition are included in the signal-to-noise ratio calculation. Then, it is determined whether the third channel (i.e., the second candidate channel) meets the condition, which should be:

[0148]

[0149] And so on, determine whether the m-th candidate channel satisfies:

[0150]

[0151] Specific Implementation Method Nine: This implementation method differs from Specific Implementation Methods One to Eight in that the frequency domain equalization method used is zero-forcing equalization or minimum mean square error equalization.

[0152] The other steps and parameters are the same as those in one of the specific implementation methods one to eight.

[0153] Experimental Section

[0154] This invention studies multi-channel refined delay estimation techniques in equalization, discusses the impact of delay estimation accuracy on communication performance, and develops multi-path delay compensation techniques. It compares the signal-to-noise ratio (SNR) of the combined multi-channel array with that of the single-channel array, derives the conditions required for equal-gain selective combining of multiple channels, and proposes a multi-channel selective combining criterion. Compared to traditional multi-channel equalization techniques, the ultra-short baseline array processing method of this invention has advantages such as reduced system complexity and improved communication system reliability. The following simulation verification of the proposed underwater acoustic single-carrier communication frequency domain array processing method for ultra-short baseline arrays is presented. The simulation analysis process of this invention is based on the parameters set in Table 1, and the basic simulation parameter settings are shown in Table 1:

[0155] Table 1 Simulation Parameter Description

[0156] Parameter name Parameter Description carrier frequency 25kHz Sampling frequency 100kHz System bandwidth 20-30kHz Symbol rate 5kbps Modulation method BPSK Information sequence length 1000 bits Training sequence length 255 bits

[0157] In the simulation analysis, three channels were set up to ensure accurate timing synchronization of each channel. The signal-to-noise ratios of the three signals are shown in Table 2 (assuming that the signal-to-noise ratio of each channel remains constant within the same frame of received signal):

[0158] Table 2 Signal-to-noise ratio parameter settings

[0159]

[0160]

[0161] In this simulation, channel 1 serves as the standard channel, with a signal-to-noise ratio (SNR) range of 0dB to 10dB in 1dB increments. Channel 2's SNR ranges from -10dB to 0dB in 1dB increments. Channel 3's SNR is the same as channel 1. Case 1 involves merging channel 1 and channel 2, while case 2 involves merging channel 1 and channel 3. During each merge, the SNR difference between channel 1 and channel 2 is 10dB, while the SNRs of channel 1 and channel 3 are the same. Based on the above theory, case 1 will decrease the SNR of the standard channel, increasing the system's BER; case 2 will increase the SNR of the standard channel, decreasing the system's BER. Simulations were performed using AWGN and underwater acoustic channels, with the SNR of the standard channel as the horizontal axis. The results are as follows: Figure 5 and Figure 6 As shown, the BER curves for both channels illustrate that, assuming consistent signal power but inconsistent noise power, channel combining does not necessarily lead to an increase in signal-to-noise ratio (SNR). When the SNR of the candidate channel is below the combining threshold, it may cause a decrease in the SNR of the standard channel, thereby affecting the reliability of the communication system. When the SNR of the candidate channel is above the combining threshold, spatial diversity gain can be obtained through combining equalization, thereby improving the signal SNR and reducing the bit error rate.

[0162] The frequency domain array processing method for underwater acoustic single-carrier communication proposed in this invention was verified through field data processing. The field test and simulation used the same signal parameters and receiver array type. The field test consisted of five array element channels. Channel selection, merging, and equalization processing were performed according to the method proposed in this invention. The results are shown in Table 3.

[0163] Table 3. Results of Field Test Data Processing

[0164] ZF Equalized Average Bit Error Rate MMSE (Medium Bit Error Rate) Average gain of combined signal-to-noise ratio / dB High signal-to-noise ratio 10-frame signal 0 0 2.10 Low signal-to-noise ratio 20-frame signal <![CDATA[4.5×10 -5 ]]> <![CDATA[4.5×10 -5 ]]> 2.45

[0165] The results show that the present invention, through fractional delay estimation and compensation, performs channel estimation on only one channel, and then selects and merges channels for frequency domain equalization, not only reduces computational complexity but also obtains spatial diversity gain, greatly reduces the bit error rate, improves the signal-to-noise ratio of the received signal, and effectively enhances the reliability of the communication system. It has significant technical advantages and broad application prospects.

[0166] The above examples of the present invention are merely illustrative of the computational model and process of the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is impossible to exhaustively list all possible implementations here. Any obvious variations or modifications derived from the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A frequency domain array processing method for underwater acoustic single-carrier communication based on an ultra-short baseline array, characterized in that, The method specifically includes the following steps: Step 1: Each element in the ultra-short baseline array simultaneously receives a single-carrier underwater acoustic transmission signal and preprocesses the received single-carrier underwater acoustic signal to obtain the preprocessed signal for each channel. Step 2: Each channel performs frame synchronization on the preprocessed signal and extracts the speed measurement signal of each channel based on the frame synchronization result; For any given channel, the signal-to-noise ratio of that channel is estimated based on the frame synchronization result of that channel, the velocity within that channel is estimated based on the velocity measurement signal of that channel, and Doppler compensation is performed on the frame synchronization result of that channel based on the velocity estimation result within that channel, to obtain the Doppler-compensated signal of that channel. Similarly, the signal-to-noise ratio estimation results for each channel and the signal after Doppler compensation are obtained separately. Step 3: Perform symbol synchronization on the Doppler-compensated signal of each channel and extract the information sequence within each channel; Step 4: Estimate the fractional delay based on the frame synchronization results for each channel; For any channel, after processing the information sequence within that channel, the fractional delay estimation result of that channel is used to compensate for the fractional delay of the processing result, thus obtaining the fractional delay compensated signal of that channel. Similarly, the fractional delay compensated signals for each channel are obtained separately. Step 5: Based on the signal-to-noise ratio (SNR) estimation results of each channel obtained in Step 2, select the channel with the highest SNR as the standard channel and the other channels as alternative channels. The signals after fractional delay compensation for the standard channel and each alternative channel are downsampled to obtain the downsampled signals of each channel. Then, channel estimation is performed based on the downsampled signal of the standard channel, and the channel estimation results are used as equalization coefficients. Step 6: Select the candidate channels that meet the merging conditions based on the signal-to-noise ratio of the standard channel and each candidate channel; Step 7: Process the downsampled signals from the standard channel and each of the candidate channels selected in Step 6, specifically as follows: For any candidate channel selected in step six, perform FFT transformation on the downsampled signal of the candidate channel, and then use the equalization coefficients calculated in step five to perform frequency domain equalization on the FFT transformed signal to obtain the frequency domain equalized signal of the candidate channel. Similarly, the frequency-equalized signals of the standard channel and each candidate channel selected in step six are obtained separately. Step 8: Combine the frequency domain equalized signals of the standard channel and each candidate channel selected in Step 6, and then perform IFFT transformation on the combined signal to obtain the restored signal.

2. The method for frequency domain array processing of underwater acoustic single-carrier communication based on an ultra-short baseline array according to claim 1, characterized in that, The preprocessing method in step one is bandpass filtering.

3. The method for frequency domain array processing of underwater acoustic single-carrier communication based on an ultra-short baseline array according to claim 1, characterized in that, In step four, the specific process of processing the information sequence within the channel is as follows: The information sequence is then down-converted and low-pass filtered sequentially.

4. The method for frequency domain array processing of underwater acoustic single-carrier communication based on an ultra-short baseline array according to claim 1, characterized in that, The method for estimating fractional delay based on the frame synchronization results of each channel is a three-point interpolation method.

5. The method for frequency domain array processing of underwater acoustic single-carrier communication based on an ultra-short baseline array according to claim 4, characterized in that, The specific process of fractional time delay estimation is as follows: For any channel, the peak region waveform of the frame synchronization result for that channel is fitted, and the fitted waveform function is: r(t) = Acos(wt) + Bsin(wt) Where t represents time, w represents the oscillation angular frequency, and A and B represent the coefficients of the fitted waveform function; Let the peak point in the frame synchronization result be denoted as r2, where r2 = r(t2), and t2 is the time corresponding to the peak point. Select a sampling point t1 before the peak point and a sampling point t3 after the peak point, then we have: r1=Acoswt1+Bsinwt1 r2=Acoswt2+Bsinwt2 r3=Acoswt3+Bsinwt3 Where r1 represents the waveform value corresponding to sampling point t1, and r3 represents the waveform value corresponding to sampling point t3, we can deduce: 0<wt s <p r3 sinwt s =r2 sin2wt s -r1 sinwt s Among them, t s Indicates the sampling interval, t s =1 / f s The value of the oscillation angular frequency is then: The fitted waveform function is then rearranged as follows: in: When wt = kπ + ψ, |r(t)| reaches its maximum value; where k is a positive integer and satisfies: Then, estimate the relevant peak time t0 based on the calculated k value: The fractional delay estimate τ for this channel is:

6. The method for frequency domain array processing of underwater acoustic single-carrier communication based on an ultra-short baseline array according to claim 5, characterized in that, The sampling points t1 and t3 satisfy t3-t2=t2-t1=1 / f s f s Indicates the sampling frequency, and f s >f0, where f0 represents the oscillation frequency of the frame synchronization result.

7. The method for frequency domain array processing of underwater acoustic single-carrier communication based on an ultra-short baseline array according to claim 1, characterized in that, The channel estimation based on the downsampled signal of the standard channel uses a time-domain adaptive estimation algorithm based on RLS.

8. The method for frequency domain array processing of underwater acoustic single-carrier communication based on an ultra-short baseline array according to claim 1, characterized in that, The specific process of step six is ​​as follows: Step 61: Sort the candidate channels in descending order of signal-to-noise ratio to obtain the sorting results; Step 6.2: Denote the signal-to-noise ratio (SNR) of the first candidate channel in the sorting results as SNR1, and the SNR of the standard channel as SNR0. Determine whether SNR1 > SNR0 - 10lg3 is satisfied. If SNR1 > SNR0 - 10lg3 is satisfied, then the first candidate channel in the sorting result is a candidate channel that meets the merging condition, and step six-three continues. Otherwise, the first candidate channel in the sorting results is a candidate channel that does not meet the merging conditions, and there are no candidate channels that meet the merging conditions among the candidate channels; Step 63: Initialize m = 2; Step 64: Denote the signal-to-noise ratio (SNR) of the m-th candidate channel in the sorting results as SNR. m The signal-to-noise ratio (SNR) of the standard channel and the 1st, 2nd, ..., m-1th candidate channels in the sorting results is denoted as SNR. 012...m-1 , Determine if the following conditions are met: Among them, P s It is signal power. This is the noise power of the standard channel. This is the noise power of the first alternative channel. It is the noise power of the (m-1)th alternative channel. It is the noise power of the m-th alternative channel, SNR 12...m This represents the signal-to-noise ratio after merging the standard channel and the 1st, 2nd, ..., mth candidate channels in the sorting results; Step 65: If SNR is satisfied 012...m >SNR 012...m-1 Then let m = m + 1, and return to step six four; If SNR is not satisfied 012...m >SNR 012...m-1 If the first, second, ..., m-1th candidate channels in the sorting results are the channels that meet the merging conditions.

9. The method for frequency domain array processing of underwater acoustic single-carrier communication based on an ultra-short baseline array according to claim 1, characterized in that, The frequency domain equalization method used is zero-forcing equalization or minimum mean square error equalization.

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