Underwater sound single carrier communication frequency domain array processing method based on ultra-short baseline array

Abstract

The invention discloses an underwater acoustic single carrier communication frequency domain array processing method based on an ultra-short baseline array, and belongs to the field of underwater acoustic communication. The problem that an existing communication system based on an ultra-short baseline receiving array is poor in reliability is solved. According to the method, a high-precision time delay estimation method in underwater acoustic positioning is adopted to carry out refined estimation on propagation time delays of M receiving channels, and the influence of different decimal time delays on channel estimation results of all the channels is eliminated. And comparing the signal-to-noise ratio after multi-channel combination with the signal-to-noise ratio of a single channel to obtain condition limitation required during equal gain selection combination of the multiple channels, and judging whether a standard channel and an alternative channel are combined or not according to the condition of channel combination so as to continuously improve the signal-to-noise ratio of a received signal and obtain a space diversity gain. The reliability of a communication system is improved, and the inter-channel interference of a traditional method is effectively avoided. The method can be applied to underwater acoustic single carrier communication frequency domain array processing of an ultra-short baseline array.

Description

Technical Field

[0001] The present invention belongs to the field of underwater acoustic communication, and in particular relates to an underwater acoustic single-carrier communication frequency domain array processing method based on an ultra-short baseline array. Background Art

[0002] Underwater acoustic communication technology, which uses sound waves as carriers, is an important technology for transmitting information between different nodes underwater. Underwater acoustic channels are one of the most complex wireless channels, with obvious fading characteristics. In order to solve the inter-symbol interference caused by multipath channels, equalization technology is often used at the receiving end to compensate for this effect. In order to improve the equalization effect of the communication system, the existing underwater acoustic communication technology has developed into multi-channel reception.

[0003] The characteristics of the ultra-short baseline receiving array are its small size, usually on the order of a few centimeters to tens of centimeters, its receiving transducers are closely spaced, and the consistency of each receiving channel is strong. Different from the traditional multi-channel receiving technology in the field of underwater acoustic communication, the strong consistency of each receiving channel of the ultra-short baseline array is mainly 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, which usually does not exceed one symbol length, which has a greater impact on traditional multi-channel equalization; strong received signal power consistency means that the signal power between each receiving channel is the same, but there is a problem of inconsistent noise in each receiving channel. Therefore, the reliability of existing communication systems based on ultra-short baseline receiving arrays is still poor, and targeted design is needed to give full play to the processing advantages of ultra-short baseline arrays and further improve the reliability of communication systems. Summary of the invention

[0004] The purpose of the present invention is to solve the problem of poor reliability of existing communication systems based on ultra-short baseline receiving arrays, and proposes 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 technical problems is: a frequency domain array processing method for underwater acoustic single-carrier communication based on an ultra-short baseline array, the method specifically comprising the following steps:

[0006] Step 1: Each oscillator in the ultra-short baseline array simultaneously receives a single-carrier underwater acoustic emission signal, and pre-processes the received single-carrier underwater acoustic signal to obtain a pre-processed signal of each channel;

[0007] Step 2: Each channel performs frame synchronization on the pre-processed signal, and extracts the speed measurement signal of each channel according to the frame synchronization result;

[0008] For any channel, the signal-to-noise ratio of the channel is estimated according to the frame synchronization result of the channel, the speed in the channel is estimated according to the speed measurement signal of the channel, and the frame synchronization result of the channel is Doppler compensated according to the speed estimation result in the channel to obtain the Doppler compensated signal of the channel;

[0009] Similarly, the signal-to-noise ratio estimation results of each channel and the Doppler compensated signal are obtained respectively;

[0010] Step 3: symbol synchronization is performed on the Doppler compensated signal of each channel respectively, and the information sequence in each channel is extracted;

[0011] Step 4: Estimate the fractional delay according to the frame synchronization result of each channel;

[0012] For any channel, after processing the information sequence in the channel, the fractional delay estimation result of the channel is used to perform fractional delay compensation on the processing result to obtain the fractional delay compensated signal of the channel;

[0013] Similarly, the fractional delay compensated signals of each channel are obtained respectively;

[0014] Step 5: According to the signal-to-noise ratio estimation results of each channel obtained in step 2, the channel with the highest signal-to-noise ratio is selected as the standard channel, and the other channels are selected as candidate channels;

[0015] Downsampling the fractional delay compensated signals of the standard channel and each candidate channel respectively to obtain the downsampled signals of each channel, and then performing channel estimation based on the downsampled signals of the standard channel, and using the channel estimation results as equalization coefficients;

[0016] Step 6: Select the candidate channel that meets the merging condition according to the signal-to-noise ratio of the standard channel and each candidate channel;

[0017] Step 7: Process the downsampled signals of the standard channel and each candidate channel selected in step 6 respectively, specifically:

[0018] For any candidate channel selected in step 6, perform FFT transformation on the downsampled signal of the candidate channel, and then perform frequency domain equalization on the signal after FFT transformation using the equalization coefficient calculated in step 5 to obtain the frequency domain equalized signal of the candidate channel;

[0019] Similarly, the frequency domain equalized signals of the standard channel and each candidate channel selected in step 6 are obtained respectively;

[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 a restored signal.

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

[0022] Furthermore, in step 4, the specific process of processing the information sequence in the channel is:

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

[0024] Furthermore, the estimation of the fractional delay according to the frame synchronization result of each channel adopts a three-point interpolation method.

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

[0026] For any channel, the peak area waveform of the frame synchronization result of the channel is fitted, and the fitting 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] The peak point in the frame synchronization result is recorded as r2, r2=r(t2), t2 is the time corresponding to the peak point, a sampling point t1 is selected before the peak point, and a sampling point t3 is selected after the peak point, then:

[0030] r1=Acoswt1+Bsinwt1

[0031] r2=Acoswt2+Bsinwt2

[0032] r3=Acoswt3+Bsinwt3

[0033] Among them, r1 represents the waveform value corresponding to the sampling point t1, and r3 represents the waveform value corresponding to the sampling point t3, and the result is:

[0034] 0<wt s <π

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

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

[0037]

[0038] Then the fitting waveform function is organized as:

[0039]

[0040] in:

[0041]

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

[0043]

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

[0045]

[0046] Then the fractional delay estimation result τ of the channel is:

[0047] τ=t0-t2.

[0048] Furthermore, the sampling point t1 and the sampling point t3 satisfy t3-t2=t2-t1=1 / f s , f s represents the sampling frequency, and f s >f0, 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 a time domain adaptive estimation algorithm based on RLS.

[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 a sorting result;

[0052] Step 62: record the signal-to-noise ratio of the first candidate channel in the sorting result as SNR1, record the signal-to-noise ratio of the standard channel as SNR0, and determine whether SNR1>SNR0-10lg3 is satisfied:

[0053] If SNR1>SNR0-10lg3 is satisfied, the first candidate channel in the sorting result is the candidate channel that meets the merging condition, and step 63 is continued;

[0054] 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;

[0055] Step 63: Initialize m=2;

[0056] Step 64: The signal-to-noise ratio of the mth candidate channel in the sorting result is recorded as SNR m , the signal-to-noise ratio of the standard channel, the first, second, ..., m-1th candidate channels in the sorting result is recorded as SNR 012…m-1 , Determine whether it meets the following requirements:

[0057]

[0058] Among them, P s is the signal power, is the noise power of the standard channel, is the noise power of the first candidate channel, is the noise power of the m-1th candidate channel, is the noise power of the mth candidate channel, SNR 12...m It represents the signal-to-noise ratio after combining the standard channel and the first, second, ..., mth candidate channels in the sorting result;

[0059] Step 65: If SNR is satisfied 012...m >SNR 012...m-1 , then set m=m+1 and return to step 64;

[0060] If the SNR is not met 012...m >SNR 012...m-1 , then the 1st, 2nd, ..., m-1th candidate channels in the sorting result are the channels that meet the merging conditions.

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

[0062] The beneficial effects of the present invention are:

[0063] 1) The present invention only performs channel estimation on one receiving channel, and uses a high-precision delay estimation method in underwater acoustic positioning to perform refined estimation of the propagation delays of M receiving channels, thereby eliminating the influence of different fractional delays on the channel estimation results of each channel, thereby reducing the complexity of the system and improving the computational efficiency when performing multi-channel merging and equalization;

[0064] 2) The present invention compares the signal-to-noise ratio after merging multiple channels with the signal-to-noise ratio of a single channel, obtains the conditional restrictions required for equal-gain selective merging of multiple channels, and determines whether to merge the standard channel and the alternative channel according to the channel merging conditions, 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 the interference between channels in the traditional method. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0066] Figure 2 It is a receiving end working flow chart of a frequency domain array processing method for underwater acoustic single-carrier communication based on an ultra-short baseline array of the present invention;

[0067] Figure 3 This is a flow chart of fractional delay compensation in the present invention;

[0068] Figure 4 This is a flow chart of merging the standard channel and the candidate channel with the largest signal-to-noise ratio in the present invention;

[0069] Figure 5 This is the simulation diagram of the combined channel BER analysis under the AWGN channel;

[0070] Figure 6 This is the simulation diagram of the merged channel BER analysis in the underwater acoustic channel. DETAILED DESCRIPTION

[0071] Specific implementation method 1: Combination 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, and the method specifically includes the following steps:

[0072] Step 1: Each oscillator in the ultra-short baseline array simultaneously receives a single-carrier underwater acoustic emission 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 of each channel;

[0073] Step 2: Each channel performs frame synchronization on the pre-processed signal (i.e., the pre-processed signal of each channel is cross-correlated with the local known signal), and extracts the speed measurement signal of each channel according to the frame synchronization result;

[0074] For any channel, the signal-to-noise ratio of the channel is estimated according to the frame synchronization result of the channel, the speed in the channel is estimated according to the speed measurement signal of the channel, and the frame synchronization result of the channel is Doppler compensated according to the speed estimation result in the channel to obtain the Doppler compensated signal of the channel;

[0075] Similarly, the signal-to-noise ratio estimation results of each channel and the Doppler compensated signal are obtained respectively;

[0076] Step 3: symbol synchronization is performed on the Doppler compensated signal of each channel respectively, and the information sequence in each channel is extracted (the peak position of the mutual correlation in each channel is the trailing edge of the synchronization signal, and then the information sequence part in the received signal is extracted from the peak position of the mutual correlation);

[0077] Step 4: Estimate the fractional delay according to the frame synchronization result of each channel;

[0078] For any channel, after processing the information sequence in the channel, the fractional delay estimation result of the channel is used to perform fractional delay compensation on the processing result to obtain the fractional delay compensated signal of the channel;

[0079] Similarly, the fractional delay compensated signals of each channel are obtained respectively;

[0080] Step 5: According to the signal-to-noise ratio estimation results of each channel obtained in step 2, the channel with the highest signal-to-noise ratio is selected as the standard channel, and the other channels are selected as candidate channels;

[0081] Downsampling the fractional delay compensated signals of the standard channel and each candidate channel respectively to obtain the downsampled signals of each channel, and then performing channel estimation based on the downsampled signals of the standard channel, and using the channel estimation results as equalization coefficients;

[0082] Step 6: Select the candidate channel that meets the merging condition according to the signal-to-noise ratio of the standard channel and each candidate channel;

[0083] Step 7: Process the downsampled signals of the standard channel and each candidate channel selected in step 6 respectively, specifically:

[0084] For any candidate channel selected in step 6, perform FFT transformation on the downsampled signal of the candidate channel, and then perform frequency domain equalization on the signal after FFT transformation using the equalization coefficient calculated in step 5 to obtain the frequency domain equalized signal of the candidate channel;

[0085] Similarly, the frequency domain equalized signals of the standard channel and each candidate channel selected in step 6 are obtained respectively;

[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 a restored signal.

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

[0088] Specific implementation method 2: This implementation method is different from specific implementation method 1 in that the preprocessing method in step 1 is bandpass filtering.

[0089] The other steps and parameters are the same as those in the first embodiment.

[0090] Specific implementation method three: This implementation method is different from specific implementation methods one or two in that, in step four, the specific process of processing the information sequence in the channel is as follows:

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

[0092] The other steps and parameters are the same as those in the first or second embodiment.

[0093] Specific implementation method 4: This implementation method is different from any one of specific implementation methods 1 to 3 in that the fractional delay is estimated based on the frame synchronization result of each channel using a three-point interpolation method.

[0094] The other steps and parameters are the same as those in Specific Embodiments 1 to 3.

[0095] Specific implementation mode 5: This implementation mode is different from the specific implementation modes 1 to 4 in that the specific process of fractional delay estimation is as follows:

[0096] For any channel, the peak area waveform of the frame synchronization result of the channel is fitted, and the fitting waveform function is:

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

[0098] Wherein, t represents time, w represents oscillation angular frequency, oscillation angular frequency w≈2πf0, f0 represents oscillation frequency of frame synchronization result, A and B represent coefficients of fitting waveform function;

[0099] The peak point in the frame synchronization result is recorded as r2, r2=r(t2), t2 is the time corresponding to the peak point, a sampling point t1 is selected before the peak point, and a sampling point t3 is selected after the peak point, then:

[0100] r1=Acoswt1+Bsinwt1

[0101] r2=Acoswt2+Bsinwt2

[0102] r3=Acoswt3+Bsinwt3

[0103] Among them, r1 represents the waveform value corresponding to the sampling point t1, and r3 represents the waveform value corresponding to the sampling point t3, and the result is:

[0104] 0<wt s <π

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

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

[0107]

[0108] Then the fitting waveform function is organized as:

[0109]

[0110] in:

[0111]

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

[0113]

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

[0115]

[0116] Then the fractional delay estimation result τ of the channel is:

[0117] τ=t0-t2

[0118] The other steps and parameters are the same as those in Specific Embodiments 1 to 4.

[0119] Specific implementation method 6: This implementation method is different from any one of the specific implementation methods 1 to 5 in that the sampling point t1 and the sampling point t3 satisfy t3-t2=t2-t1=1 / f s , f s represents the sampling frequency, and f s >f0, f0 represents the oscillation frequency of the frame synchronization result.

[0120] The other steps and parameters are the same as those in Specific Implementation Methods 1 to 5.

[0121] Specific implementation example 7: This implementation example is different from any one of specific implementation examples 1 to 6 in that the channel estimation based on the downsampled signal of the standard channel adopts a time domain adaptive estimation algorithm based on RLS.

[0122] The other steps and parameters are the same as those in Specific Embodiments 1 to 6.

[0123] Specific implementation method eight: Combination Figure 4 This embodiment is different from the first to seventh embodiments in 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 a sorting result;

[0125] Step 62: record the signal-to-noise ratio of the first candidate channel in the sorting result as SNR1, record the signal-to-noise ratio of the standard channel as SNR0, and determine whether SNR1>SNR0-10lg3 is satisfied:

[0126] If SNR1>SNR0-10lg3 is satisfied, the first candidate channel in the sorting result is the candidate channel that meets the merging condition, and step 63 is continued;

[0127] Where lg represents the logarithm with 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 in the front does not meet the merging condition, it is no longer necessary to judge the candidate channel with a small signal-to-noise ratio in the back);

[0129] Step 63: Initialize m=2;

[0130] Step 64: The signal-to-noise ratio of the mth candidate channel in the sorting result is recorded as SNR m , the signal-to-noise ratio of the standard channel, the first, second, ..., m-1th candidate channels in the sorting result is recorded as SNR 012...m-1 , Determine whether it meets the following requirements:

[0131]

[0132] Among them, P s is the signal power, is the noise power of the standard channel, is the noise power of the first candidate channel, is the noise power of the m-1th candidate channel, is the noise power of the mth candidate channel, SNR 12...mIt represents the signal-to-noise ratio after combining the standard channel and the first, second, ..., mth candidate channels in the sorting result;

[0133] Step 65: If SNR is satisfied 012...m >SNR 012...m-1 , then set m=m+1 and return to step 64;

[0134] If the SNR is not met 012...m >SNR 012...m-1 , then the 1st, 2nd, ..., m-1th candidate channels in the sorting result are the channels that meet the merging conditions.

[0135] The other steps and parameters are the same as those in Specific Embodiments 1 to 7.

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

[0137] Assume that the signal-to-noise ratio of the mth candidate channel after passing through the bandpass filter is:

[0138]

[0139] Then we can get the relationship between noise power and signal power:

[0140]

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

[0142]

[0143] If the two channels are to be combined to obtain a signal-to-noise ratio gain, the SNR must be 01 >SNR0, so we know:

[0144]

[0145] Then the channel merging condition is obtained as follows:

[0146] SNR1>SNR0-10lg3

[0147] The channels that meet the condition are included in the signal-to-noise ratio calculation, and then the third channel (i.e., the second candidate channel) is judged to see whether it meets the condition. It should meet the following conditions:

[0148]

[0149] Similarly, determine whether the mth candidate channel satisfies:

[0150]

[0151] Specific implementation method 9: This implementation method is different from any one of specific implementation methods 1 to 8 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 Specific Embodiments 1 to 8.

[0153] Experimental Section

[0154] The present invention studies the multi-channel refined delay estimation technology in merging equalization, discusses the impact of delay estimation accuracy on communication performance and develops multi-channel delay compensation technology, compares the signal-to-noise ratio after multi-channel merging with the signal-to-noise ratio of a single channel, obtains the conditional restrictions required for equal-gain selective merging of multiple channels, and proposes a multi-channel selective merging criterion. Compared with traditional multi-channel equalization technology, the ultra-short baseline array processing method of the present invention has the advantages of reducing system complexity and improving communication system reliability. The frequency domain array processing method for underwater acoustic single-carrier communication for ultra-short baseline arrays proposed in the present invention is simulated and verified below. The simulation and analysis process of the present invention is simulated and set according to the parameters in Table 1. The basic simulation parameter settings are shown in Table 1:

[0155] Table 1 Description of simulation parameters

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

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

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

[0159]

[0160]

[0161] Among them, channel one is used as the standard channel, and the signal-to-noise ratio ranges from 0dB to 10dB with a step size of 1dB. The signal-to-noise ratio range of channel two is from -10dB to 0dB with a step size of 1dB. The signal-to-noise ratio setting of channel three is the same as that of channel one. Case one is the merger of channel one and channel two, and case two is the merger of channel one and channel three. The signal-to-noise ratio of channel one and channel two differs by 10dB each time they are merged, and the signal-to-noise ratio of channel one and channel three is the same. From the above theory, it can be seen that case one will reduce the signal-to-noise ratio of the standard channel and increase the BER of the system; case two will increase the signal-to-noise ratio of the standard channel and reduce the BER of the system. Simulations were performed using the AWGN channel and the underwater acoustic channel respectively, with the signal-to-noise ratio of the standard channel as the horizontal axis. The results are as follows Figure 5 and Figure 6 As shown in the figure, the BER curves under the two channels show that, when the signal power is consistent but the noise power is inconsistent, channel merging does not necessarily bring about a gain in the signal-to-noise ratio. When the signal-to-noise ratio of the candidate channel is lower than the merging threshold, it may cause a decrease in the signal-to-noise ratio of the standard channel, thereby affecting the reliability of the communication system; when the signal-to-noise ratio of the candidate channel is higher than the merging threshold, spatial diversity gain can be obtained through merging and equalization, thereby improving the signal-to-noise ratio and reducing the bit error rate.

[0162] The proposed method for underwater acoustic single-carrier communication frequency domain array processing for ultra-short baseline arrays was verified by field data processing. The field test and the simulation had the same signal parameters and receiving array type. The field test had a total of five array element channels. The method proposed in the present invention was used to select and merge channel equalization processing. The results are shown in Table 3:

[0163] Table 3 Field test data processing results

[0164] ZF equalization average bit error rate MMSE equalization average bit error rate Average signal-to-noise ratio gain after merging / 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 not only reduces the 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 improves the reliability of the communication system through fractional delay estimation and compensation, channel estimation for only one channel, and then selects the combined channel for frequency domain equalization. It has significant technical advantages and broad application prospects.

[0166] The above calculation examples of the present invention are only used to explain the calculation model and calculation process of the present invention in detail, and are not intended to limit the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution 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 ultra-short baseline array, characterized in that: The method specifically comprises the following steps: Step 1: Each oscillator in the ultra-short baseline array simultaneously receives a single-carrier underwater acoustic emission signal, and pre-processes the received single-carrier underwater acoustic signal to obtain a pre-processed signal of each channel; Step 2: Each channel performs frame synchronization on the pre-processed signal, and extracts the speed measurement signal of each channel according to the frame synchronization result; For any channel, the signal-to-noise ratio of the channel is estimated according to the frame synchronization result of the channel, the speed in the channel is estimated according to the speed measurement signal of the channel, and the frame synchronization result of the channel is Doppler compensated according to the speed estimation result in the channel to obtain the Doppler compensated signal of the channel; Similarly, the signal-to-noise ratio estimation results of each channel and the Doppler compensated signal are obtained respectively; Step 3: symbol synchronization is performed on the Doppler compensated signal of each channel respectively, and the information sequence in each channel is extracted; Step 4: Estimate the fractional delay according to the frame synchronization result of each channel; For any channel, after processing the information sequence in the channel, the fractional delay estimation result of the channel is used to perform fractional delay compensation on the processing result to obtain the fractional delay compensated signal of the channel; Similarly, the fractional delay compensated signals of each channel are obtained respectively; Step 5: According to the signal-to-noise ratio estimation results of each channel obtained in step 2, the channel with the highest signal-to-noise ratio is selected as the standard channel, and the other channels are selected as candidate channels; Downsampling the fractional delay compensated signals of the standard channel and each candidate channel respectively to obtain the downsampled signals of each channel, and then performing channel estimation based on the downsampled signals of the standard channel, and using the channel estimation results as equalization coefficients; Step 6: Select the candidate channel that meets the merging condition according to the signal-to-noise ratio of the standard channel and each candidate channel; Step 7: Process the downsampled signals of the standard channel and each candidate channel selected in step 6 respectively, specifically: For any candidate channel selected in step 6, perform FFT transformation on the downsampled signal of the candidate channel, and then perform frequency domain equalization on the signal after FFT transformation using the equalization coefficient calculated in step 5 to obtain the frequency domain equalized signal of the candidate channel; Similarly, the frequency domain equalized signals of the standard channel and each candidate channel selected in step 6 are obtained respectively; 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 a restored signal.

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

3. According to the method for processing frequency domain array of underwater acoustic single carrier communication based on ultra-short baseline array in claim 1, it is characterized in that: In step 4, the specific process of processing the information sequence in the channel is: The information sequence is down-converted and low-pass filtered in sequence.

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

5. According to claim 4, a method for processing frequency domain array of underwater acoustic single carrier communication based on ultra-short baseline array is characterized in that: The specific process of fractional delay estimation is as follows: For any channel, the peak area waveform of the frame synchronization result of the channel is fitted, and the fitting 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; The peak point in the frame synchronization result is recorded as r2, r2=r(t2), t2 is the time corresponding to the peak point, a sampling point t1 is selected before the peak point, and a sampling point t3 is selected after the peak point, then: r1=Acoswt1+Bsinwt1 r2=Acoswt2+Bsinwt2 r3=Acoswt3+Bsinwt3 Among them, r1 represents the waveform value corresponding to the sampling point t1, and r3 represents the waveform value corresponding to the sampling point t3, and the result is: 0<wt s <p r3 sinwt s =r2 sin2wt s -r1 sinwt s Among them, t s represents the sampling interval, t s =1 / f s ; then the value of the oscillation angular frequency is: Then the fitting waveform function is organized as: in: When wt=kπ+ψ, |r(t)| reaches the maximum value; where k is a positive integer and satisfies: Then estimate the correlation peak time t0 based on the calculated k value: Then the fractional delay estimation result τ of the channel is:

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

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

8. The method for processing frequency domain array of underwater acoustic single carrier communication based on ultra-short baseline array according to claim 1 is 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 a sorting result; Step 62: record the signal-to-noise ratio of the first candidate channel in the sorting result as SNR1, record the signal-to-noise ratio of the standard channel as SNR0, and determine whether SNR1>SNR0-10lg3 is satisfied: If SNR1>SNR0-10lg3 is satisfied, the first candidate channel in the sorting result is the candidate channel that meets the merging condition, and step 63 is continued; 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; Step 63: Initialize m=2; Step 64: The signal-to-noise ratio of the mth candidate channel in the sorting result is recorded as SNR m , the signal-to-noise ratio of the standard channel, the first, second, ..., m-1th candidate channels in the sorting result is recorded as SNR 012...m-1 , Determine whether it meets the following requirements: Among them, P s is the signal power, is the noise power of the standard channel, is the noise power of the first candidate channel, is the noise power of the m-1th candidate channel, is the noise power of the mth candidate channel, SNR 12...m It represents the signal-to-noise ratio after combining the standard channel and the first, second, ..., mth candidate channels in the sorting result; Step 65: If SNR is satisfied 012...m >SNR 012...m-1 , then set m=m+1 and return to step 64; If the SNR is not met 012...m >SNR 012...m-1 , then the 1st, 2nd, ..., m-1th candidate channels in the sorting result are the channels that meet the merging conditions.

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

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