A method for receiving underwater acoustic communication based on two-dimensional orthogonal inverse transform

Abstract

The application discloses a kind of based on two-dimensional orthogonal inverse transform underwater acoustic communication receiving method, by alternating matching to LFM sequence in received signal, identify effective frame and reconstruct multi-frame boundary;Waveform compression or expansion is estimated by LFM template search, resample correction is carried out to received signal;Joint cycle prefix correlation index and pilot matching index correction symbol starting position, then carry out frequency domain equalization;According to two-dimensional hybrid orthogonal transformation used by sending end, transpose inverse mapping is carried out to equalization data matrix, restores the original data grid before two-dimensional hybrid orthogonal expansion;In frequency dimension, chebyshev orthogonal base is used after QR numerical orthogonalization, in time symbol dimension, normalized Walsh-Hadamard block base is used, realize with chebyshev-Walsh base construction strict consistency, while having alternate LFM chain detection, time scale compensation, phase-aware pilot interpolation and regularization equalization, can reduce the coupling influence of synchronization error and channel estimation error to orthogonal recovery.

Description

Technical Field

[0001] This invention relates to the field of communications, and more particularly to a method for receiving underwater acoustic communications based on two-dimensional orthogonal inverse transform. Background Technology

[0002] Underwater acoustic channels are characterized by prolonged propagation time, significant multipath spread, noticeable timescale variations caused by motion, and limited available bandwidth. Multicarrier receivers typically need to sequentially perform frame synchronization, resampling, carrier down-conversion, cyclic prefix localization, frequency offset correction, channel estimation, equalization, and data demodulation. Residuals from any of these steps will propagate to subsequent processing, particularly disrupting the invertibility of two-dimensional orthogonal mappings.

[0003] Existing orthogonal precoding reception methods typically treat the Chebyshev-Walsh transform as an independent module, assuming that frame boundaries, time scales, and carrier frequency offsets have been accurately corrected. This approach fails to unify the constraints of synchronization correlation peaks, cyclic prefix indices, pilot channel phase, and the inverse mapping of the two-dimensional hybrid orthogonal transform. When the underwater acoustic channel experiences non-integer sampling drift, inter-frame interval changes, or rapid pilot phase rotation, directly performing the inverse transform can easily lead to constellation rotation, energy amplification, and bit error accumulation.

[0004] Furthermore, using an unnormalized transformation matrix, or directly truncating a Hadamard matrix with dimensions other than powers of 2, may cause the mapping matrix to fail to satisfy the orthogonality / unitary condition; for some polynomial bases, numerical construction errors may also cause orthogonality degradation. Summary of the Invention

[0005] The following is an overview of the topics described in detail in this article.

[0006] The purpose of this application is to at least partially solve one of the technical problems existing in the related technologies. The embodiments of this application provide an underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform, which achieves strict consistency with the Chebyshev-Wolshki construction and simultaneously possesses alternating LFM chain detection, time scale compensation, phase-aware pilot interpolation and regularized equalization, and can reduce the coupling influence of synchronization error and channel estimation error on orthogonal recovery.

[0007] An embodiment of this application provides an underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform, comprising:

[0008] Obtain the real-valued passband sequence and transmitting parameters collected by the hydrophone;

[0009] Alternate matching is performed on the up-sweep and down-sweep linear frequency modulated (LFM) signal sequences in the real-value passband sequence, and valid frames are identified and multi-frame boundaries are reconstructed based on the arrangement of relevant peaks.

[0010] By searching the LFM template at different time scales, the waveform compression or expansion caused by the relative motion between the transmitter and receiver is estimated, and the received signal is resampled and corrected.

[0011] The symbol start position is corrected by combining the cyclic prefix correlation index and the pilot matching index. Channel response interpolation is performed using pilot amplitude and phase information. Frequency domain equalization is performed by a minimum mean square error single-tap equalizer with regularization term based on data symbols and effective subcarriers.

[0012] Based on the two-dimensional hybrid orthogonal transformation adopted by the transmitting end, the equalization data matrix is ​​transposed and inversely mapped to restore the original data grid before the two-dimensional hybrid orthogonal expansion;

[0013] The two-dimensional hybrid orthogonal transform uses a Chebyshev orthogonal basis obtained by QR numerical orthogonalization in the frequency dimension and a normalized Walsh-Hadamard block basis in the time symbol dimension. When the OFDM symbol dimension is not an integer power of 2, a block diagonal matrix of the corresponding order Hadamard sub-block is constructed according to the binary expansion of that dimension to maintain the orthogonality of the time symbol dimension transform.

[0014] According to certain embodiments of this application, prior to the alternating matching step, the method further includes:

[0015] Establish the input interface between received data and system parameters using the following steps:

[0016] Read the received data file;

[0017] Check the number and data types of variables in the received data file, and verify the integrity of each configuration in the parameter file;

[0018] Check the matching relationship between the orthogonal transform matrix and the data grid, the effective number of subcarriers and the transform dimension, and calculate the orthogonality error of the transform matrix;

[0019] When the number of variables, parameter dimensions, or orthogonality error does not meet the preset conditions, the subsequent processing is terminated and the corresponding abnormal information is output.

[0020] According to certain embodiments of this application, the alternating matching of the up-scan and down-scan LFM sequences in the received signal, identifying valid frames and reconstructing multi-frame boundaries based on the arrangement of correlation peaks, includes:

[0021] The received signal is normalized and matched with the upper-sweep LFM template and the lower-sweep LFM template respectively to obtain two types of synchronization correlation sequences and their corresponding candidate peak positions;

[0022] Based on the pre-set alternation pattern of up-scan and down-scan frequencies at the transmitting end, candidate peaks are combined in time sequence and filtered group by group.

[0023] When the following conditions are met: the peak amplitude reaches the detection threshold, the relative difference of peaks within the group is within the allowable range, the interval between adjacent peaks conforms to the frame structure constraints, and the number of detected peaks is consistent with the number of frames contained in a complete playback, the peak group is determined as a valid LFM frame chain, and the initial boundary of each frame in this playback is determined.

[0024] Isolated peaks, out-of-order peaks, and incomplete peak groups that do not meet the aforementioned joint conditions are removed.

[0025] According to certain embodiments of this application, waveform compression or expansion caused by relative motion between transmit and receive signals is estimated through LFM template search at different time scales, and resampling correction is performed on the received signal, including:

[0026] By using LFM template search at different time scales, coarse search sets and fine search sets for candidate time scales are established around zero scale bias.

[0027] Scaling the LFM template for each candidate time scale and using the median of the LFM correlation peaks of all frames of the correct type as the score, we estimate the waveform compression or expansion caused by the relative motion between the transmitter and receiver.

[0028] Select the time scale with the highest score;

[0029] When the deviation of the time scale with the largest score from 1 exceeds a set threshold, reverse linear interpolation correction is performed on the entire received waveform of the received signal.

[0030] According to certain embodiments of this application, the joint cyclic prefix correlation index and pilot matching index correct the symbol start position, including:

[0031] The load segment is extracted based on the independently detected LFM start point of each frame. The load segment is multiplied by the carrier complex exponent and resampled to the baseband sampling rate.

[0032] Candidate offsets are searched around the prediction starting point, and OFDM symbol boundaries are selected using a weighted average of the cyclic prefix correlation index and the pilot matching index to correct the symbol starting position.

[0033] According to certain embodiments of this application, after correcting the symbol start position of the joint cyclic prefix correlation index and pilot matching index, the method includes:

[0034] The correlation between the cyclic prefix and the corresponding tail sample of the OFDM symbol in a frame is accumulated to estimate the residual common frequency offset and correct the residual common frequency offset.

[0035] After removing the cyclic prefix, a Fast Fourier Transform is performed to retain the valid subcarriers.

[0036] According to certain embodiments of this application, channel response interpolation is performed using pilot amplitude and phase information, including:

[0037] Extract the received values ​​of the pilot OFDM symbols on each effective subcarrier, and perform a complex ratio operation between the received values ​​and the corresponding known pilot symbols to obtain the discrete channel frequency response at the pilot time.

[0038] For data symbols located between adjacent pilot symbols, the channel responses at both ends are decomposed into amplitude and phase components. The phase sequence is unwrapped, and the amplitude and continuous phase are interpolated along the OFDM symbol direction to reconstruct the complex channel response corresponding to each data symbol.

[0039] For subcarriers with isolated abrupt changes in frequency direction or with strong estimated noise, the complex channel response is locally smoothed.

[0040] According to certain embodiments of this application, the regularization coefficient of the regularization term of the minimum mean square error single-tap equalizer is the product of the median channel power and a fixed proportion or is adaptively determined by the variance of the inactive subcarrier noise, and is limited to a preset upper and lower bound.

[0041] According to certain embodiments of this application, non-periodic frequency domain structures are described using Chebyshev polynomial bases, including:

[0042] Select standard Chebyshev polynomial discrete sampling nodes to generate the original discrete Chebyshev sampling matrix;

[0043] The original discrete Chebyshev sampling matrix is ​​decomposed into an orthogonal matrix Q and an upper triangular matrix R.

[0044] The orthogonal matrix Q is used as the frequency-wise Vichebyshev orthogonal basis after numerical orthogonalization;

[0045] Using Walsh-Hadamaki for piecewise sign extension in the time sign dimension, including:

[0046] When the symbol dimension of Orthogonal Frequency Division Multiplexing (OFDM) is not an integer power of 2, it is represented as the sum of several integer powers of 2 according to the binary expansion of that dimension, and the order of each Hadamard sub-block and the block diagonal structure are determined accordingly.

[0047] Generate unnormalized Hadamard matrices corresponding to the order of each sub-block, and normalize them according to the square root of the order of the corresponding sub-block so that each Hadamard sub-block satisfies the unitary condition.

[0048] Each normalized Hadamard sub-block is used to form a block diagonal matrix, and the block diagonal matrix is ​​then used for piecewise orthogonal expansion in the time symbol dimension.

[0049] According to certain embodiments of this application, the received recovery grid obtained by inverse mapping is expanded into a complex symbol sequence by column, the QPSK common phase is estimated, decision-guided gain normalization is performed, and then QPSK hard decision, block deinterleaving and pseudo-random sequence descrambling are performed; when the transmitter uses convolutional coding, Viterbi decoding is performed.

[0050] For multiple complete received records corresponding to the same transmitted waveform, a no-reference quality evaluation is performed based on frame synchronization correlation strength, cyclic prefix correlation, pilot reconstruction consistency, and equalization error vector magnitude. At least one received result is selected based on the quality evaluation results, or multiple received results are fused.

[0051] The above-mentioned solution has at least the following beneficial effects:

[0052] (1) High transformation consistency: The transmitting mapping and receiving inverse mapping use the same set of unitary matrices, and the Chebyshev-Walsh matrix construction rules are given to avoid systematic bit errors caused by inconsistencies in normalization, sorting or symbol conventions.

[0053] (2) Synchronous robustness: By using alternating type constraints of upsweep and time-reversed downsweep LFM, isolated strongly correlated peaks are filtered out. Data is extracted according to the actual measured starting point of each frame instead of a fixed frame interval, which can adapt to the situation of insertion or deletion of silence by playback devices.

[0054] (3) Motion adaptation: Non-integer sampling scale estimation is achieved by searching at two levels of coarse and fine time scales and using the median of multi-frame LFM correlation as the evaluation quantity; after correction, bandpass filtering is performed to reduce the damage to OFDM orthogonality caused by Doppler time compression or stretching.

[0055] (4) Equalization and stability: Interpolation of amplitude and phase between adjacent pilots is performed, and MMSE single-tap equalization with regularization term is used to suppress noise enhancement on deep fading subcarriers.

[0056] (5) Complete implementation: The method covers synchronization, scale compensation, fine timing, frequency offset correction, channel estimation, inverse transformation, phase normalization, deinterleaving and decoding, and can directly form an executable receiver processing chain. Attached Figure Description

[0057] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0058] Figure 1 This is a flowchart illustrating the steps of an underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform.

[0059] Figure 2This is a flowchart illustrating the steps involved in establishing an input interface between received data and system parameters.

[0060] Figure 3 This is a step diagram of alternating matching of the up-scan and down-scan LFM sequences in the received signal, identifying valid frames and reconstructing multi-frame boundaries based on the arrangement of related peaks;

[0061] Figure 4 This diagram illustrates the steps involved in estimating waveform compression or expansion caused by relative motion between the transmitter and receiver using LFM template search at different time scales, and then resampling and correcting the received signal.

[0062] Figure 5 This is a step diagram illustrating the process of correcting the starting position of the symbol for the combined cyclic prefix correlation index and pilot matching index;

[0063] Figure 6 This is a step diagram of the residual common frequency offset correction and FFT process;

[0064] Figure 7 This is a flowchart illustrating the steps involved in channel response interpolation using pilot amplitude and phase information.

[0065] Figure 8 This is a step diagram of the residual phase normalization and bit recovery steps;

[0066] Figure 9 This is a step diagram of the steps for fusing and receiving results. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0068] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, or the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0069] The characters and symbols appearing in this application are explained in Table 1.

[0070] Table 1. Explanation of the meanings of characters and symbols

[0071]

[0072] Underwater acoustic channels are characterized by prolonged propagation time, significant multipath spread, noticeable timescale variations caused by motion, and limited available bandwidth. Multicarrier receivers typically need to sequentially perform frame synchronization, resampling, carrier down-conversion, cyclic prefix localization, frequency offset correction, channel estimation, equalization, and data demodulation. Residuals from any of these steps will propagate to subsequent processing, particularly disrupting the invertibility of two-dimensional orthogonal mappings.

[0073] Existing orthogonal precoding reception methods typically treat the Chebyshev-Walsh transform as an independent module, assuming that frame boundaries, time scales, and carrier frequency offsets have been accurately corrected. This approach fails to unify the constraints of synchronization correlation peaks, cyclic prefix indices, pilot channel phase, and the inverse mapping of the two-dimensional hybrid orthogonal transform. When the underwater acoustic channel experiences non-integer sampling drift, inter-frame interval changes, or rapid pilot phase rotation, directly performing the inverse transform can easily lead to constellation rotation, energy amplification, and bit error accumulation.

[0074] In addition, some implementations directly call the non-normalized transformation matrix, or forcibly truncate the Hadamard matrix for dimensions that are not integer powers of 2, causing the mapping matrix to not satisfy the unitary condition; some polynomial bases and data-driven bases also have insufficient numerical orthogonality.

[0075] To address the above problems, embodiments of this application provide an underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform.

[0076] The embodiments of this application will be further described below with reference to the accompanying drawings.

[0077] Reference Figure 1 A method for receiving underwater acoustic communication based on two-dimensional orthogonal inverse transform includes the following steps:

[0078] Step S100: Obtain the real-valued passband sequence and transmitting parameters collected by the hydrophone;

[0079] Step S200: Alternately match the up-sweep and down-sweep linear frequency modulated (LFM) signal sequences in the real-value passband sequence, identify valid frames and reconstruct multi-frame boundaries based on the arrangement of relevant peaks;

[0080] Step S300: Through LFM template search at different time scales, estimate the waveform compression or expansion caused by the relative motion between the transmitter and receiver, and perform resampling correction on the received signal;

[0081] Step S400: Combine the cyclic prefix correlation index and pilot matching index to correct the symbol start position, use pilot amplitude and phase information to perform channel response interpolation, and use a minimum mean square error single-tap equalizer with regularization term to perform frequency domain equalization based on data symbols and effective subcarriers.

[0082] Step S500: According to the two-dimensional hybrid orthogonal transformation adopted by the transmitting end, the equalization data matrix is ​​transposed and inversely mapped to restore the original data grid before the two-dimensional hybrid orthogonal expansion;

[0083] The two-dimensional hybrid orthogonal transform uses a Chebyshev orthogonal basis obtained by QR numerical orthogonalization in the frequency dimension and a normalized Walsh-Hadamard block basis in the time symbol dimension. When the OFDM symbol dimension is not an integer power of 2, a block diagonal matrix of the corresponding order Hadamard sub-block is constructed according to the binary expansion of that dimension to maintain the orthogonality of the time symbol dimension transform.

[0084] Reference Figure 2 At the receiving end, the first step is to establish an input interface between the received data and system parameters, including the following steps:

[0085] Step S11: Read the received data file;

[0086] Step S12: Check the number and data type of variables in the received data file, and verify the integrity of each configuration in the parameter file;

[0087] Step S13: Check the matching relationship between the orthogonal transformation matrix and the data grid, the number of effective subcarriers and the transformation dimension, and calculate the orthogonality error of the transformation matrix;

[0088] Step S14: When the number of variables, parameter dimensions, or orthogonality error does not meet the preset conditions, terminate the subsequent processing and output the corresponding abnormal information.

[0089] Specifically, the received data file only retains the received signal sequence to be processed, while the parameter file centrally stores the received sampling rate, carrier bandwidth, OFDM modulation parameters, up-and-down sweep LFM reference templates, pilot symbols, frame structure configuration, Chebyshev orthogonal matrix, block Walsh-Hadamard matrix, and two-dimensional hybrid orthogonal transform parameters. After reading, the number and data types of variables in the received data file are checked, and the completeness of each configuration in the parameter file is verified. Further checks are performed on the matching relationship between the orthogonal transform matrix and the data grid, the number of effective subcarriers, and the transform dimension, while calculating the orthogonality error of the transform matrix. If the number of variables, parameter dimension, or orthogonality error does not meet the preset conditions, subsequent processing is terminated and corresponding abnormal information is output, thereby avoiding imperceptible interface mismatch due to inconsistencies in transmit and receive parameters.

[0090] For step S100, the real-valued passband sequence acquired by the hydrophone is obtained. And the sending parameters.

[0091] In real-valued passband sequences middle, This is the discrete sampling sequence number.

[0092] The steps for parameter reading and interface verification. Reading only includes the received sequence. The data file and the parameter file containing sampling rate, carrier frequency band, OFDM parameters, LFM template, pilot sequence, frame structure and orthogonal matrix; verify the uniqueness of variables, matrix dimension and unitary error of the two files to prevent silent mismatch between the transmitting and receiving ends.

[0093] The steps for performing front-end resampling and bandpass limiting. Depend on Resampling to ,get ; Use passband coverage Finite impulse response filters suppress out-of-band noise. If If the ratio cannot be approximated to a small integer, then anti-aliasing multiphase resampling is used.

[0094] Reference Figure 3 For step S200, the up-scan and down-scan LFM sequences in the received signal are alternately matched, and valid frames are identified and multi-frame boundaries are reconstructed based on the arrangement of related peaks, including the following steps:

[0095] Step S210: Normalize and match the received signal with the upper frequency sweep LFM template and the lower frequency sweep LFM template respectively to obtain two types of synchronization correlation sequences and corresponding candidate peak positions;

[0096] Step S220: Based on the pre-set alternation pattern of up-scanning and down-scanning frequencies at the transmitting end, the candidate peaks are combined in time sequence and filtered group by group.

[0097] Step S230: When the peak amplitude reaches the detection threshold, the relative difference of peaks within the group is within the allowable range, the interval between adjacent peaks conforms to the frame structure constraints, and the number of detected peaks is consistent with the number of frames included in a complete playback, the peak group is determined as a valid LFM frame chain, and the initial boundary of each frame in this playback is determined.

[0098] Step S240: Remove isolated peaks, out-of-order peaks, and incomplete peak groups that do not meet the joint conditions.

[0099] Among them are: ;

[0100] In the formula, Indicates the up-scan or down-scan template. For candidate delay The normalized correlation coefficient at the given point, within the summation range This is the LFM sample point number.

[0101] Reference Figure 4For step S300, the waveform compression or expansion caused by the relative motion between the transmitter and receiver is estimated by searching the LFM template at different time scales, and the received signal is resampled and corrected, including the following steps:

[0102] Step S310: By searching the LFM template at different time scales, establish a coarse search set and a fine search set for candidate time scales around zero scale bias;

[0103] Step S320: Scale the LFM template for each candidate time scale and use the median of the LFM correlation peaks of all frames of the correct type as the score to estimate the waveform compression or expansion caused by the relative motion of the transmit and receive.

[0104] Step S330: Select the time scale with the highest score;

[0105] Step S340: When the deviation of the time scale with the largest score relative to 1 exceeds a set threshold, reverse linear interpolation correction is performed on the entire received waveform of the received signal.

[0106] Specifically, a coarse search set and a fine search set are established around zero-scale bias. The LFM template is scaled for each candidate scale, and the median of the LFM correlation peaks of all frames with correct types is used as the score. The scale with the highest score is selected. When its deviation from 1 exceeds a set threshold, reverse linear interpolation correction is performed on the entire received waveform.

[0107] ;

[0108] in, For the candidate timescale set, For the first Frame uses scale The correct LFM template related sequence.

[0109] ;

[0110] in, This represents a linear interpolation operator. For non-integer input positions; This is the scale-corrected sequence.

[0111] Reference Figure 5 For step S400, the joint cyclic prefix correlation index and pilot matching index correct the symbol start position, including the following steps:

[0112] Step S411: Extract the load segment based on the independently detected LFM start point of each frame, multiply the load segment by the carrier complex exponent and resample to the baseband sampling rate;

[0113] Step S412: Search for candidate offsets around the prediction start point, and select OFDM symbol boundaries using the weighted values ​​of the cyclic prefix correlation index and pilot matching index to correct the symbol start position.

[0114] Specifically, the load segment is truncated based on the independently detected LFM start point of each frame, multiplied by the carrier complex exponent, and resampled. Candidate offsets are searched around the prediction starting point, and OFDM symbol boundaries are selected using a weighted average of the cyclic prefix correlation index and the pilot matching index.

[0115] ;

[0116] in, For the first Frame load at The starting sample points in the sample, This is the down-conversion complex envelope.

[0117] ;

[0118] in, For fine timing candidate offsets, This is a normalized cyclic prefix correlation index.

[0119] Reference Figure 6 After correcting the symbol start position using the joint cyclic prefix correlation index and pilot matching index, the residual common frequency offset correction and FFT steps are performed, including the following steps: Step S421, the correlation between the cyclic prefix and the corresponding tail sample of the OFDM symbol in a frame is accumulated to estimate the residual common frequency offset and correct the residual common frequency offset; Step S422, after removing the cyclic prefix, a fast Fourier transform is performed to retain the effective subcarrier.

[0120] Specifically, the steps for residual common frequency offset correction and FFT are as follows: The correlation between the cyclic prefix and the corresponding tail sample of all OFDM symbols within a frame is accumulated to estimate and correct the residual common frequency offset; after removing the cyclic prefix, the following steps are performed: Point FFT, retain One effective subcarrier.

[0121] ;

[0122] in, Intra-frame OFDM symbol number, Represents the complex phase angle. This is the estimated value of the residual frequency offset.

[0123] ;

[0124] in, For the first The OFDM symbol of the first FFT output at each frequency point.

[0125] Reference Figure 7 Channel response interpolation using pilot amplitude and phase information includes the following steps:

[0126] Step S431: Extract the received values ​​of the pilot OFDM symbols on each effective subcarrier, and perform a complex ratio operation between the received values ​​and the corresponding known pilot symbols to obtain the discrete channel frequency response at the pilot time.

[0127] For data symbols located between adjacent pilot symbols, the channel responses at both ends are decomposed into amplitude and phase components. The phase sequence is unwrapped, and the amplitude and continuous phase are interpolated along the OFDM symbol direction to reconstruct the complex channel response corresponding to each data symbol.

[0128] For subcarriers with isolated abrupt changes in frequency direction or with strong estimated noise, the complex channel response is locally smoothed.

[0129] Specifically, the steps for time-varying channel reconstruction are as follows: Extract the received values ​​of the pilot OFDM symbols on each effective subcarrier, and perform a complex ratio operation with the corresponding known pilot symbols to obtain the discrete channel frequency response at the pilot time.

[0130] For data symbols located between adjacent pilot symbols, the channel responses at both ends are first decomposed into amplitude and phase components. The phase sequence is then unwrapped, and the amplitude and continuous phase are interpolated along the OFDM symbol direction to reconstruct the complex channel response corresponding to each data symbol.

[0131] For subcarriers with isolated abrupt changes in frequency direction or with strong estimated noise, local smoothing can be further applied to the complex channel response to suppress pilot noise propagation while preserving the main characteristics of channel amplitude and phase changes with time and frequency.

[0132] ;

[0133] in, This refers to the pilot OFDM symbol number. For the first Known pilots on each effective subcarrier, Channel estimation for pilot positions.

[0134]

[0135] in, and Data symbols Pilot numbers before and after, , and These represent the channel amplitude and unwrapped phase obtained through interpolation, respectively.

[0136] A minimum mean square error (MMS) single-tap equalizer with a regularization term is used for frequency domain equalization based on data symbols and effective subcarriers. The regularization coefficient of the MMS single-tap equalizer is the product of the median channel power and a fixed proportion, or is adaptively determined by the variance of the inactive subcarrier noise, and is limited to preset upper and lower bounds.

[0137] Specifically, the steps for performing regularized MMSE equalization are as follows: Single-tap MMSE equalization is performed based on data symbols and effective subcarriers. The regularization coefficient can be the product of the median channel power and a fixed proportion, or it can be adaptively determined by the variance of the inactive subcarrier noise and limited to preset upper and lower bounds.

[0138] ;

[0139] in, For balanced output, For the first The regularization coefficient of each data symbol.

[0140] For step S500, the equalization data matrix is ​​transposed and inversely mapped according to the two-dimensional hybrid orthogonal transform used by the transmitter. The aperiodic frequency domain structure is described using Chebyshev polynomial basis, and piecewise symbol extension is performed in the time symbol dimension using Walsh-Hadamardi.

[0141] Among them, the non-periodic frequency domain structure is described using Chebyshev polynomial bases, including:

[0142] Select standard Chebyshev polynomial discrete sampling nodes to generate the original discrete Chebyshev sampling matrix;

[0143] The original discrete Chebyshev sampling matrix is ​​decomposed into QR matrix to obtain the orthogonal matrix Q and the upper triangular matrix R.

[0144] The orthogonal matrix Q is used as the frequency-wise Vichebyshev orthogonal basis after numerical orthogonalization.

[0145] Using Walsh-Hadamaki for piecewise sign extension in the time sign dimension, including:

[0146] When the symbol dimension of Orthogonal Frequency Division Multiplexing (OFDM) is not an integer power of 2, it is represented as the sum of several integer powers of 2 according to the binary expansion of that dimension, and the order of each Hadamard sub-block and the block diagonal structure are determined accordingly.

[0147] Generate unnormalized Hadamard matrices corresponding to the order of each sub-block, and normalize them according to the square root of the order of the corresponding sub-block so that each Hadamard sub-block satisfies the unitary condition.

[0148] Each normalized Hadamard sub-block is used to form a block diagonal matrix, and the block diagonal matrix is ​​then used for piecewise orthogonal expansion in the time symbol dimension.

[0149] Specifically, the construction and inverse mapping of the Chebyshev-Wolsh orthogonal matrix are explained below.

[0150] The transmitting end first maps the data grid according to the following formula; the receiving end performs its conjugate transpose inverse operation after equalization. The non-periodic frequency domain structure is described using Chebyshev polynomial basis, and piecewise symbol extension is performed in the time symbol dimension using Walsh-Hadamardi.

[0151] ;

[0152] in, For the QPSK data grid to be sent, The time-frequency data grid after orthogonal mapping and See the symbol explanation for the meaning of .

[0153] ;

[0154] The unitary constraint ensures that the total energy remains unchanged before and after the mapping, and allows the receiver to use the conjugate transpose to complete the lossless inverse mapping.

[0155] ;

[0156] in, For the first One Chebyshev node, , It is a discrete Chebyshev sampling matrix.

[0157] ;

[0158] in, and They are respectively The unitary matrix and upper triangular matrix obtained by QR decomposition This is the Chebyshev transformation matrix after numerical orthogonalization.

[0159] ;

[0160] in, Number of binary blocks For the first a non-negative integer, Indicates a diagonal combination of blocks; when When it is not an integer power of 2, press binary expansion construction .

[0161] ;

[0162] in, for Unnormalized Hadamard matrix; Normalized Hadamard matrix satisfy .

[0163] ;

[0164] in, After subcarrier-by-subcarrier MMSE equalization, according to OK, A matrix arranged in columns. The data grid is to be restored; all matrix dimensions are determined by... and The only certainty.

[0165] The process of restoring the original data grid before the two-dimensional hybrid orthogonal expansion includes the following residual phase normalization and bit recovery steps:

[0166] Step S510: Expand the received recovery grid obtained by inverse mapping into a complex symbol sequence by column, estimate the QPSK common phase, perform decision-guided gain normalization, and then perform QPSK hard decision, block deinterleaving and pseudo-random sequence descrambling; when the transmitter uses convolutional coding, perform Viterbi decoding.

[0167] Specifically, the received recovery grid is expanded into a complex symbol sequence column by column, the QPSK common phase is estimated, decision-guided gain normalization is performed, and then QPSK hard decision, block deinterleaving and pseudo-random sequence descrambling are completed; when the transmitter uses convolutional coding, Viterbi decoding is performed.

[0168] ;

[0169] in, The first after inverse mapping A QPSK symbol, Represents the sample mean. QPSK module / 2 Common Phase Estimation.

[0170] Reference Figure 9 Restoring the original data grid before the two-dimensional hybrid orthogonal expansion also includes the following steps for receiving the fusion results:

[0171] Step S521: For multiple sets of complete received records corresponding to the same transmitted waveform, calculate the frame synchronization correlation strength, cyclic prefix correlation, pilot reconstruction consistency and equalization error vector magnitude as indicators, and combine the normalized indicators into a referenceless reception quality evaluation value.

[0172] Step S522: Sort the reception results according to the no-reference reception quality evaluation value and select the single demodulation result with the highest quality.

[0173] In this process, a bit-by-bit majority decision is performed on each decoded bit, or the common phase deviation between equalized symbols is eliminated first, and then symbol-level fusion is completed using the median, truncated mean, or weighted average method.

[0174] Specifically, for multiple complete received records corresponding to the same transmitted waveform, the frame synchronization correlation strength, cyclic prefix correlation, pilot reconstruction consistency, and equalization error vector magnitude are calculated separately. These indicators are then normalized and combined into a referenceless reception quality evaluation value. The received results are sorted according to the evaluation value, with the highest-quality single demodulation result selected as the output. To utilize the time diversity gain from repeated transmissions, a bit-by-bit majority decision can be performed on each decoded bit, or the common phase deviation between equalization symbols can be eliminated first, followed by symbol-level fusion using median, truncated mean, or weighted average methods to reduce the impact of abnormal received records on the recovery results. After processing, the final recovered data, error statistics for each and the fused data, quality evaluation results, and processing diagrams for synchronization, channel estimation, equalization, and constellation distribution are output.

[0175] Perform the above steps for multiple complete playbacks of the same transmitted content, and form a blind quality score based on the LFM correlation peak, cyclic prefix index, pilot matching index, and error vector amplitude, and select the result with the highest blind quality score; or perform a position-by-position robust averaging on the phase-aligned equalized QPSK symbols before demodulation.

[0176] An embodiment of this application provides an underwater acoustic communication receiving device, including a sampling interface, a memory, and a processor. The memory stores a program, up-sweep and down-sweep LFM templates, pilot signals, Chebyshev orthogonal matrices, block Walsh-Hadamard matrices, and two-dimensional hybrid orthogonal transformation parameters. When the program is executed by the processor, it implements the underwater acoustic communication receiving method based on two-dimensional inverse orthogonal transformation as described above.

[0177] An embodiment of this application provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform.

[0178] In one specific embodiment, a mid-frequency underwater acoustic communication configuration is adopted: nominal transmit sampling rate Received sampling rate passband carrier center frequency Baseband sampling rate ; , , , The modulation scheme is QPSK, and the pilot spacing is 2 data OFDM symbols. Each frame uses... LFM serves as the synchronization header; the protection interval after LFM is... Odd-numbered frames use an upsweep frequency, while even-numbered frames use a downsweep frequency formed by time reversal.

[0179] At the sending end, construct according to this method. ,calculate Pilot signals are then inserted and OFDM modulation is performed. At the receiver, the 100kHz data is first resampled to 96kHz, and the complete frame chain is detected using up-sweep and down-sweep normalized correlation. Coarse and fine LFM scale searches are performed within a preset symmetrical ppm range, and time scale correction is implemented when the threshold is exceeded. Subsequently, down-conversion, fine timing, residual frequency offset estimation, FFT, pilot phase interpolation, and MMSE equalization are completed.

[0180] Combining all balanced data Then, calculate In this embodiment, the matrix generation program is verified offline. and ,in The Frobenius norm is represented. After inverse mapping, the symbols undergo QPSK phase correction, decision-guided amplitude normalization, deinterleaving, and descrambling to obtain the information bits. For records with multiple replays, the highest blind quality result is prioritized, and soft symbol fusion may be added.

[0181] Those skilled in the art can adjust the filter order, pilot density, modulation order, time scale search range, and regularization coefficient without changing the above-mentioned key technical relationships; such equivalent substitutions are all within the scope of this invention.

[0182] The underwater acoustic communication receiving method based on the above two-dimensional orthogonal inverse transform achieves the following beneficial effects:

[0183] (1) High transformation consistency: The transmitting mapping and receiving inverse mapping use the same set of unitary matrices, and the Chebyshev-Walsh matrix construction rules are given to avoid systematic bit errors caused by inconsistencies in normalization, sorting or symbol conventions.

[0184] (2) Synchronous robustness: By using alternating type constraints of upsweep and time-reversed downsweep LFM, isolated strongly correlated peaks are filtered out. Data is extracted according to the actual measured starting point of each frame instead of a fixed frame interval, which can adapt to the situation of insertion or deletion of silence by playback devices.

[0185] (3) Motion adaptation: Non-integer sampling scale estimation is achieved by searching at two levels of coarse and fine time scales and using the median of multi-frame LFM correlation as the evaluation quantity; after correction, bandpass filtering is performed to reduce the damage to OFDM orthogonality caused by Doppler time compression or stretching.

[0186] (4) Equalization and stability: Interpolation of amplitude and phase between adjacent pilots is performed, and MMSE single-tap equalization with regularization term is used to suppress noise enhancement on deep fading subcarriers.

[0187] (5) Complete implementation: The method covers synchronization, scale compensation, fine timing, frequency offset correction, channel estimation, inverse transformation, phase normalization, deinterleaving and decoding, and can directly form an executable receiver processing chain.

[0188] The above is a detailed description of the preferred embodiments of this application, but this application is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A method for receiving underwater acoustic communication based on two-dimensional orthogonal inverse transform, characterized in that, include: Obtain the real-valued passband sequence and transmitting parameters collected by the hydrophone; Alternate matching is performed on the up-sweep and down-sweep linear frequency modulated (LFM) signal sequences in the real-value passband sequence, and valid frames are identified and multi-frame boundaries are reconstructed based on the arrangement of relevant peaks. By searching the LFM template at different time scales, the waveform compression or expansion caused by the relative motion between the transmitter and receiver is estimated, and the received signal is resampled and corrected. The symbol start position is corrected by combining the cyclic prefix correlation index and the pilot matching index. Channel response interpolation is performed using pilot amplitude and phase information. Frequency domain equalization is performed by a minimum mean square error single-tap equalizer with regularization term based on data symbols and effective subcarriers. Based on the two-dimensional hybrid orthogonal transformation adopted by the transmitting end, the equalization data matrix is ​​transposed and inversely mapped to restore the original data grid before the two-dimensional hybrid orthogonal expansion; The two-dimensional hybrid orthogonal transform uses a Chebyshev orthogonal basis obtained by QR numerical orthogonalization in the frequency dimension and a normalized Walsh-Hadamard block basis in the time symbol dimension. When the OFDM symbol dimension is not an integer power of 2, a block diagonal matrix of the corresponding order Hadamard sub-block is constructed according to the binary expansion of that dimension to maintain the orthogonality of the time symbol dimension transform.

2. The underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform according to claim 1, characterized in that, Prior to the alternating matching step, the method further includes: Establish the input interface between received data and system parameters using the following steps: Read the received data file; Check the number and data types of variables in the received data file, and verify the integrity of each configuration in the parameter file; Check the matching relationship between the orthogonal transform matrix and the data grid, the effective number of subcarriers and the transform dimension, and calculate the orthogonality error of the transform matrix; When the number of variables, parameter dimensions, or orthogonality error does not meet the preset conditions, the subsequent processing is terminated and the corresponding abnormal information is output.

3. The underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform according to claim 1, characterized in that, The step of alternately matching the up-scanning and down-scanning LFM sequences in the received signal, identifying valid frames and reconstructing multi-frame boundaries based on the arrangement of relevant peaks, includes: The received signal is normalized and matched with the upper-scanning frequency LFM template and the lower-scanning frequency LFM template respectively to obtain two types of synchronization correlation sequences and their corresponding candidate peak positions; Based on the pre-set alternation pattern of up-scanning and down-scanning frequencies at the transmitting end, candidate peaks are combined in a time sequence and filtered group by group. When the following conditions are met: the peak amplitude reaches the detection threshold, the relative difference of peaks within the group is within the allowable range, the interval between adjacent peaks conforms to the frame structure constraints, and the number of detected peaks is consistent with the number of frames contained in a complete playback, the peak group is determined as a valid LFM frame chain, and the initial boundary of each frame in this playback is determined. Isolated peaks, out-of-order peaks, and incomplete peak groups that do not meet the aforementioned joint conditions are removed.

4. The underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform according to claim 1, characterized in that, By searching LFM templates at different time scales, the waveform compression or expansion caused by the relative motion between the transmitter and receiver is estimated, and the received signal is resampled and corrected, including: By using LFM template search at different time scales, coarse search sets and fine search sets for candidate time scales are established around zero scale bias. Scaling the LFM template for each candidate time scale and using the median of the LFM correlation peaks of all frames of the correct type as the score, we estimate the waveform compression or expansion caused by the relative motion between the transmitter and receiver. Select the time scale with the highest score; When the deviation of the time scale with the largest score from 1 exceeds a set threshold, reverse linear interpolation correction is performed on the entire received waveform of the received signal.

5. The underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform according to claim 1, characterized in that, The joint cyclic prefix correlation index and pilot matching index correct the symbol start position, including: The load segment is extracted based on the independently detected LFM start point of each frame. The load segment is multiplied by the carrier complex exponent and resampled to the baseband sampling rate. Candidate offsets are searched around the prediction starting point, and OFDM symbol boundaries are selected using a weighted average of the cyclic prefix correlation index and the pilot matching index to correct the symbol starting position.

6. The underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform according to claim 1, characterized in that, After correcting the symbol start position using the joint cyclic prefix correlation index and pilot matching index, the method includes: The correlation between the cyclic prefix and the corresponding tail sample of the OFDM symbol in a frame is accumulated to estimate the residual common frequency offset and correct the residual common frequency offset. After removing the cyclic prefix, a Fast Fourier Transform is performed to retain the valid subcarriers.

7. The underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform according to claim 1, characterized in that, Channel response interpolation using pilot amplitude and phase information includes: Extract the received values ​​of the pilot OFDM symbols on each effective subcarrier, and perform a complex ratio operation between the received values ​​and the corresponding known pilot symbols to obtain the discrete channel frequency response at the pilot time. For data symbols located between adjacent pilot symbols, the channel responses at both ends are decomposed into amplitude and phase components. The phase sequence is unwrapped, and the amplitude and continuous phase are interpolated along the OFDM symbol direction to reconstruct the complex channel response corresponding to each data symbol. For subcarriers with isolated abrupt changes in frequency direction or with strong estimated noise, the complex channel response is locally smoothed.

8. The underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform according to claim 1, characterized in that, The regularization coefficient of the regularization term of the minimum mean square error single-tap equalizer is the product of the median channel power and a fixed proportion or is adaptively determined by the variance of the inactive subcarrier noise, and is limited to preset upper and lower bounds.

9. The underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform according to claim 1, characterized in that, Describing aperiodic frequency domain structures using Chebyshev polynomial bases includes: Select standard Chebyshev polynomial discrete sampling nodes to generate the original discrete Chebyshev sampling matrix; The original discrete Chebyshev sampling matrix is ​​decomposed into an orthogonal matrix Q and an upper triangular matrix R. The orthogonal matrix Q is used as the frequency-wise Vichebyshev orthogonal basis after numerical orthogonalization; Using Walsh-Hadamaki for piecewise sign extension in the time sign dimension, including: When the symbol dimension of Orthogonal Frequency Division Multiplexing (OFDM) is not an integer power of 2, it is represented as the sum of several integer powers of 2 according to the binary expansion of that dimension, and the order of each Hadamard sub-block and the block diagonal structure are determined accordingly. Generate unnormalized Hadamard matrices corresponding to the order of each sub-block, and normalize them according to the square root of the order of the corresponding sub-block so that each Hadamard sub-block satisfies the unitary condition. Each normalized Hadamard sub-block is used to form a block diagonal matrix, and the block diagonal matrix is ​​then used for piecewise orthogonal expansion in the time symbol dimension.

10. The underwater acoustic communication receiving method based on two-dimensional orthogonal inverse transform according to claim 1, characterized in that, Restore the original data grid before the two-dimensional hybrid orthogonal expansion, including: The received recovery grid obtained by inverse mapping is expanded into a complex symbol sequence by column, the QPSK common phase is estimated, decision-guided gain normalization is performed, and then QPSK hard decision, block deinterleaving and pseudo-random sequence descrambling are performed; when the transmitter uses convolutional coding, Viterbi decoding is performed. For multiple complete received records corresponding to the same transmitted waveform, a no-reference quality evaluation is performed based on frame synchronization correlation strength, cyclic prefix correlation, pilot reconstruction consistency, and equalization error vector magnitude. At least one received result is selected based on the quality evaluation results, or multiple received results are fused.

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