A signal receiving method for spread spectrum underwater acoustic communication facing long-distance time-varying channel

Abstract

The application discloses a signal receiving method for spread spectrum underwater acoustic communication of long-distance time-varying channel, which comprises the following steps: obtaining the received communication signal, carrying out down-conversion and low-pass filtering to obtain a baseband signal, and carrying out synchronization to divide the baseband signal into pilot signals and spread spectrum sequence signals; using the pilot signals to complete initial channel estimation to obtain initial Doppler estimation value, time delay and amplitude response estimation value of each path; using the estimated Doppler to carry out frequency offset compensation and resampling on the first spread spectrum sequence receiving signal; using the estimated time delay and amplitude response to construct a first to-be-estimated spread spectrum sequence signal Rake receiver; combining the Rake receiver and using maximum likelihood estimation to realize the decision of the current spread spectrum sequence and the log-likelihood ratio of each bit; using the decided spread spectrum sequence to estimate the Doppler, time delay and amplitude response of the current spread spectrum sequence signal; and in this way, the decision of all spread spectrum sequences is completed. The application can effectively reduce the demodulation error rate.

Description

Technical Field

[0001] This invention relates to the field of underwater acoustic communication, and more particularly to a signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels. Background Technology

[0002] Long-distance underwater acoustic communication in the deep sea typically utilizes mid-to-low frequency acoustic waves with minimal propagation loss to achieve long-distance transmission. However, due to the limited signal bandwidth within the mid-to-low frequency band, spread spectrum communication methods are often used to increase signal processing gain and improve the system's anti-interference capability. In deep-sea long-distance underwater acoustic communication scenarios, not only is signal energy attenuated severely, but the signal propagation path is also complex, exhibiting significant long delay spread. Under these conditions, traditional channel shortening and signal equalization methods suffer from noise amplification and high computational complexity when facing low signal-to-noise ratios and long delay spread, leading to severe inter-symbol interference and significantly degrading the quality of the received signal. Therefore, research on high-gain demodulation methods for spread spectrum signals under long delay spread has significant engineering value.

[0003] To improve the signal-to-noise ratio and communication reliability, efficient multipath energy combining algorithms are needed to collect and utilize signal energy from multipath components to enhance signal processing gain. However, the movement of underwater communication platforms and dynamic changes in the marine environment cause time-varying channel characteristics. Therefore, how to achieve stable demodulation of spread spectrum signals in time-varying channels with long delay-Doppler double spread requires further research and application. Summary of the Invention

[0004] To address the issues of long-distance underwater acoustic communication, such as extended latency and the potential for traditional equalizers to exacerbate noise, this invention proposes a signal reception method for spread spectrum underwater acoustic communication in applications with highly time-varying channels and low signal-to-noise ratios. This method utilizes an estimated spreading sequence to update channel parameters in real time, enabling energy combining of the spread spectrum signal across multiple propagation paths. Furthermore, by dynamically updating Rake receiver parameters based on channel changes, the detection signal-to-noise ratio is effectively improved. This method is particularly suitable for applications requiring long-distance, low-rate underwater acoustic communication between mobile underwater platforms.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] A signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels includes the following steps:

[0007] S1: Obtain the passband communication signal received by the receiver, and obtain the baseband signal after down-conversion and low-pass filtering. After synchronization, the baseband signal is divided into blocks according to the pilot signal and the spread spectrum sequence signal.

[0008] S2: Use the pilot signal to complete the initial channel estimation and obtain the initial Doppler estimate. And the estimated time delay and amplitude response for each path;

[0009] S3: Using the Doppler obtained from pilot estimation, frequency offset compensation and resampling are performed on the received signal of the first spread spectrum sequence;

[0010] S4: Using the time delay and amplitude response estimates obtained from the pilot estimation in S2, construct the first Rake receiver for the spread spectrum sequence signal to be estimated;

[0011] S5: Combine the Rake receiver and utilize maximum likelihood estimation to make a decision on the current spread spectrum sequence and the corresponding log-likelihood ratio of each bit;

[0012] S6: Using the already decided spread spectrum sequence, construct the likelihood function of the Doppler of the current spread spectrum sequence signal and the cost function of the time delay and amplitude response. Then, use the maximum likelihood estimation to estimate the Doppler of the current spread spectrum sequence signal, and then estimate the time delay and amplitude response of the current spread spectrum sequence signal by minimizing the cost function.

[0013] S7: Use the Doppler of the previous spread spectrum sequence signal to perform frequency offset compensation and resampling on the received signal of the next spread spectrum sequence, and use the time delay and amplitude response of the current spread spectrum sequence signal to construct the Rake receiver for the next spread spectrum sequence signal;

[0014] S8: Repeat S5~S7 until all spread spectrum sequences have been decided.

[0015] Furthermore, S2 is implemented through the following sub-steps:

[0016] S2.1: First, construct the likelihood function with respect to Doppler using the pilot signal;

[0017] S2.2: Construct the cost function for Doppler, and use Newton's correction to refine the Doppler estimate, thus obtaining a precise estimate of Doppler. ;

[0018] S2.3: Using Doppler precision estimation, the pilot signal is processed according to the original sampling interval. The interpolation is performed by multiplying the result by a frequency offset compensation term to obtain the frequency offset compensated and resampled pilot signal;

[0019] S2.4: Sample the pilot signal after frequency offset compensation and resampling according to the original sampling interval to obtain the pilot symbol; initialize the path number p=1, the residual is equal to the pilot symbol, and give the number of multipaths;

[0020] S2.5: Construct a cost function for the time delay of the pilot signal corresponding to the time period using the residual; pre-set a time delay set, obtain a coarse estimate of the time delay by minimizing the cost function, and then refine the time delay estimate by using Newton correction to obtain a fine estimate of the time delay;

[0021] S2.6: Calculate the precise estimate of the magnitude response, update the path number p=p+1, and update the residuals;

[0022] S2.7: Determine if p is greater than the number of multipaths. If yes, complete the estimation of all paths. If no, return to S2.5.

[0023] Furthermore, S3 is implemented through the following sub-steps:

[0024] S3.1: Intercept the first spread spectrum sequence received signal;

[0025] S3.2: The received signal of the first spread spectrum sequence is processed according to the original sampling interval. The result is then interpolated by a factor of 1, and a frequency offset compensation term is added to the interpolated result to obtain the first spread spectrum sequence received signal after frequency offset compensation and resampling.

[0026] Furthermore, S4 is implemented through the following sub-steps:

[0027] S4.1: Construct the Rake receiver for the first spread spectrum sequence signal using the precise estimates of the path delay and amplitude response obtained from the pilot estimation.

[0028] S4.2: The received signal of the first spread spectrum sequence after frequency offset compensation and resampling is sampled at the baseband rate to obtain the first received symbol of the spread spectrum sequence; based on the Rake receiver of the first spread spectrum sequence signal and the first received symbol of the spread spectrum sequence, a likelihood function for the first spread spectrum sequence symbol to be estimated is constructed.

[0029] S4.3: Initialize the spread spectrum sequence signal index k=1.

[0030] Furthermore, S5 is implemented through the following sub-steps:

[0031] S5.1: Use maximum likelihood estimation to make symbol decisions on the current spread spectrum sequence signal and obtain the estimation result of the first spread spectrum sequence symbol to be estimated;

[0032] S5.2: According to the nth b The value of the nth bit is either 0 or 1. The spread spectrum sequence set is divided into two sets, and the value of the nth bit carried by the current spread spectrum sequence is calculated. b Log-likelihood ratio of bits.

[0033] Furthermore, S6 is implemented through the following sub-steps:

[0034] S6.1: Construct a Rake receiver for the current spread spectrum sequence signal based on the estimation results of the current spread spectrum sequence symbols and the estimated values ​​of the time delay and amplitude response of each path of the previous spread spectrum sequence signal;

[0035] S6.2: Using the Rake receiver of the current spread spectrum sequence signal and the signal vector obtained by sampling the received signal of the current spread spectrum sequence according to the sampling interval, construct the likelihood function of Doppler; pre-set a Doppler set and use maximum likelihood estimation to obtain a coarse estimate of Doppler;

[0036] S6.3: Initialize the path number p=1, residual r p It is equal to the signal vector obtained by sampling the received signal of the current spread spectrum sequence according to the sampling interval, and the number of multipaths is given;

[0037] S6.4: Construct a cost function for time delay using the estimation results and residuals of the current spread spectrum sequence symbols; pre-set a time delay set, and obtain the estimated value of the time delay of the current spread spectrum sequence signal by minimizing the cost function for time delay;

[0038] S6.5: Calculate the precise estimate of the magnitude response, update the path number p=p+1, and update the residuals;

[0039] S6.6: Determine if the path number p is greater than the number of multipaths. If yes, complete the estimation of all paths. If no, return to S6.4.

[0040] Furthermore, S7 is implemented through the following sub-steps:

[0041] S7.1: Update the spread spectrum sequence signal index k=k+1, and extract the received signal y of the kth spread spectrum sequence. k (t);

[0042] S7.2: Receive signal y for the kth spread spectrum sequence k (t) according to the original sampling interval The interpolation is performed by a factor of 1, and the interpolation result is multiplied by a frequency offset compensation term to obtain the received signal of the k-th spread spectrum sequence after frequency offset compensation and resampling. ;in, This represents the Doppler estimate of the (k-1)th spread spectrum sequence signal;

[0043] S7.3: Construct a Rake receiver for the k-th spread spectrum sequence signal using the path delay and amplitude response estimated from the (k-1)-th spread spectrum sequence signal;

[0044] S7.4: Receive the k-th spread spectrum sequence signal after frequency offset compensation and resampling. The k-th spread spectrum sequence received symbol is obtained by sampling at the baseband rate. According to the Rake receiver of the k-th spread spectrum sequence signal and Construct the likelihood function for the k-th spread spectrum sequence symbol to be estimated.

[0045] A signal receiving device for spread spectrum underwater acoustic communication for long-distance time-varying channels includes one or more processors for implementing a signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels.

[0046] An electronic device, comprising:

[0047] One or more processors;

[0048] A storage device for storing one or more programs that, when executed by the electronic device, enable the electronic device to implement a signal receiving method for spread spectrum underwater acoustic communication over long-distance time-varying channels.

[0049] A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements a signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels.

[0050] The beneficial effects of this invention are as follows:

[0051] (1) The present invention utilizes the signal energy in the multipath component through a Rake receiver, thereby improving the signal processing gain.

[0052] (2) This invention uses the already determined spread spectrum sequence to update the channel Doppler, time delay and amplitude response parameters, thereby realizing the adaptive update of the Rake receiver in time-varying channel scenarios.

[0053] (3) The method of the present invention can effectively reduce the demodulation error rate. Attached Figure Description

[0054] Figure 1 This is a flowchart of a signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels, according to an embodiment of the present invention.

[0055] Figure 2 This is a schematic diagram of the frame structure of the communication signal in an embodiment of the present invention.

[0056] Figure 3 This is a schematic diagram of the unit impulse response of the simulated channel used in the embodiments of the present invention.

[0057] Figure 4 This is a schematic diagram illustrating the change in coherence of the simulated channel over time in the embodiments of the present invention.

[0058] Figure 5This is a comparison of the signal demodulation bit error rate in the simulation experiment of this invention, using and not using an adaptive Rake receiver. Detailed Implementation

[0059] The present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments. The purpose and effects of the present invention will become clearer. It should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0060] like Figure 1 As shown, the signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels in this embodiment includes the following steps one through eight.

[0061] Step 1: Obtain the passband communication signal r(t) received by the receiver, and obtain the baseband signal y(t) after down-conversion and low-pass filtering. After synchronization, divide the baseband signal into blocks according to the pilot signal and the spread spectrum sequence signal.

[0062] like Figure 2 As shown, the communication signal r(t) is composed of a linear frequency modulated signal. The data frame consists of a pilot signal and multiple spread spectrum sequences transmitted as signals x(t).

[0063] Among them, linear frequency modulation signal Represented as:

[0064]

[0065] In the formula, μ represents the frequency modulation slope, B is the signal bandwidth, and T... q This represents the duration of the linear frequency modulated signal.

[0066] The baseband signal y(t) obtained by down-converting and low-pass filtering the communication signal r(t) is expressed as:

[0067]

[0068] in, f represents a low-pass filter. c Indicates the carrier frequency.

[0069] Calculate the baseband signal y(t) and the linear frequency modulated signal. correlation :

[0070]

[0071] The synchronization point is the location of the maximum correlation, represented as:

[0072]

[0073] Finally, the pilot signal y is extracted based on the synchronization results. q (t), and divide the spread spectrum sequence signal into blocks. For the k-th spread spectrum sequence received signal y k (t), for y q (t) Samples of length N are obtained according to the sampling rate. q The signal vector is denoted as y q , for y k (t) according to the sampling interval T s The sampling yields a length of N d The signal vector, denoted as 𝐲 𝑘 .

[0074] Step 2: Use the pilot signal to complete the initial channel estimation, and obtain the initial Doppler estimate and the time delay and amplitude response estimate for each path.

[0075] Step two is implemented through the following sub-steps:

[0076] S2.1: First, using the pilot signal y q Construct the likelihood function with respect to Doppler α0, expressed as:

[0077]

[0078] in, It is a function that follows the mean. The covariance matrix is is a Gaussian distribution, where:

[0079]

[0080] It is a length of N q The vector whose i-th element is represented as , It is the noise variance. It is a dimension The identity matrix.

[0081] Presuppose a Doppler set A coarse estimate of the Doppler effect is obtained using maximum likelihood estimation. .

[0082] S2.2: Construct a cost function for Doppler α0, and use Newton's correction to refine the Doppler estimate to obtain a precise estimate of Doppler.

[0083] Wherein, cost function Represented as:

[0084]

[0085] Precise estimation of Doppler Represented as:

[0086]

[0087] S2.3: Using Doppler's precise estimation for the pilot signal y q (t) according to the original sampling interval T s of Interpolate by a factor of 1 to obtain Then to Multiply by a frequency offset compensation term The pilot signal after frequency offset compensation and resampling is obtained. ,

[0088] Right now:

[0089]

[0090] S2.4: Pilot signal after frequency offset compensation and resampling According to the sampling interval T s Sampling is performed to obtain pilot symbols. Initialize the path number p=1, and the residual e p Equal to the pilot symbols after frequency offset compensation and resampling And give the number of multipaths P;

[0091] S2.5: Utilizing residual e p Construct the time delay for the time period corresponding to the pilot signal. The cost function; a pre-defined time delay set. The time delay is obtained by minimizing the cost function. rough estimate Then, by using Newton's correction to refine the delay estimate, a precise estimate of the delay is obtained. .

[0092] Among them, regarding latency Cost function Represented as:

[0093]

[0094] in, It is a length of N q The vector whose i-th element is .

[0095] Delay rough estimate Represented as:

[0096]

[0097] Precise estimation of latency Represented as:

[0098]

[0099] S2.6: Calculate the precise estimate of the magnitude response Update the path number p = p + 1, and update the residual e. p .

[0100] Among them, the precise estimate Represented as:

[0101]

[0102] The residual update is represented as:

[0103]

[0104] S2.7: Determine if p is greater than the number of multipaths P. If yes, complete the estimation of all paths; otherwise, return to S2.5.

[0105] Step 3: Using the Doppler obtained from pilot estimation The received signal y1(t) of the first spread spectrum sequence is compensated for by CFO (carrier frequency offset) and resampled.

[0106] Step three is implemented through the following sub-steps:

[0107] S3.1: Extract the first spread spectrum sequence received signal y1(t).

[0108] S3.2: For y1(t), according to the original sampling interval T s of Interpolation is performed to obtain Then to Multiply by a frequency offset compensation term The first spread spectrum sequence received signal after frequency offset compensation and resampling is obtained. ,Right now:

[0109]

[0110] Step 4: Using the time delay and amplitude response estimates obtained from the pilot estimation in Step 2, construct the first Rake receiver for the spread spectrum sequence signal to be estimated.

[0111] Step four is implemented through the following sub-steps:

[0112] S4.1: Fine estimates of path delays obtained using pilot estimation and precise estimate of amplitude response Constructing the Rake receiver for the first spread spectrum sequence signal :

[0113]

[0114] Where x1 is a string of length N d The vector, whose i-th element is:

[0115]

[0116]

[0117] Where g(t) is the pulse shaping filter, β is the roll-off factor, and N is the spreading sequence s. k Length; T s This represents the sampling time interval.

[0118] S4.2: Receive the first spread spectrum sequence signal after frequency offset compensation and resampling. The first spread spectrum sequence received symbol is obtained by sampling at the baseband rate. According to the Rake receiver of the first spread spectrum sequence signal and Construct the likelihood function for the first spread spectrum sequence symbol s1 to be estimated. :

[0119]

[0120] in, It is a function that follows the mean. The covariance matrix is Gaussian distribution, It is a dimension The identity matrix.

[0121] S4.3: Initialize the spread spectrum sequence signal index k=1.

[0122] Step 5: Combine the Rake receiver and use maximum likelihood estimation to make a decision on the current spread spectrum sequence and the log-likelihood ratio of each corresponding bit.

[0123] Step five is implemented through the following sub-steps:

[0124] S5.1: Utilize maximum likelihood estimation to determine the symbol of the current spread spectrum sequence signal, obtaining the estimation result of the first spread spectrum sequence symbol to be estimated. :

[0125]

[0126] in, Given a pre-set set of spreading sequences before spread spectrum modulation, containing Q spreading sequences with weak cross-correlation characteristics, each spreading sequence carries... 1 bit.

[0127] S5.2: Based on the nth b bits ,according to The value of 0 or 1 will set the spread spectrum sequence. Divided into two sets and Calculate the nth spread spectrum carried by the kth spread spectrum sequence. b The log-likelihood ratio of each bit :

[0128]

[0129] in, This represents the received signal of the k-th spread spectrum sequence after frequency offset compensation and resampling. Based on the vector obtained by sampling at the baseband rate Let s represent the k-th spreading sequence symbol to be estimated. k The likelihood function.

[0130] Step 6: Using the already decided spread spectrum sequence, construct the likelihood function for the Doppler of the current sequence signal, and the cost function for the time delay and amplitude response. Then, use maximum likelihood estimation to estimate the Doppler of the current spread spectrum sequence signal, and then estimate the time delay and amplitude response of the current spread spectrum sequence signal by minimizing the cost function.

[0131] Step six is ​​implemented through the following sub-steps:

[0132] S6.1: Construct a Rake receiver for the current spread spectrum sequence signal based on the estimation results of the symbols in the current spread spectrum sequence and the estimated values ​​of the time delay and amplitude response of each path of the previous spread spectrum sequence signal.

[0133] Rake receiver for the kth spread spectrum sequence signal Represented as:

[0134]

[0135] in, It is a length of N d The vector, whose i-th element is:

[0136]

[0137] in, This represents the estimation result of the k-th spreading sequence symbol. , These represent the estimated time delay and amplitude response of the p-th path of the (k-1)-th spread spectrum sequence symbol, respectively. The Doppler effect is yet to be estimated.

[0138] S6.2: Using the Rake receiver of the current spread spectrum sequence signal and the signal vector obtained by sampling the current spread spectrum sequence received signal according to the sampling interval, construct the likelihood function of Doppler; pre-set a Doppler set and use maximum likelihood estimation to obtain a coarse estimate of Doppler.

[0139] Among them, the likelihood function with respect to Doppler Represented as:

[0140]

[0141] in, It is a function that follows the mean. The covariance matrix is Gaussian distribution; Let be the Rake receiver for the k-th spread spectrum sequence signal.

[0142] Coarse estimate of Doppler obtained by maximum likelihood estimation Represented as:

[0143]

[0144] in, This represents the predefined Doppler set.

[0145] S6.3: Initialize the path number p=1, residual r p equal And give the number of multipaths P.

[0146] S6.4: Construct a cost function for time delay using the estimation results and residuals of the current spread spectrum sequence symbols; pre-set a time delay set, and obtain the estimated value of the time delay of the current spread spectrum sequence signal by minimizing the cost function for time delay.

[0147] Among them, the cost function for latency Represented as:

[0148]

[0149] in, This represents the time delay of the p-th path for the k-th spread spectrum sequence symbol; It is a length of N d The vector, whose i-th element is:

[0150]

[0151] in, This represents the estimation result of the k-th spread spectrum sequence symbol.

[0152] By minimizing the cost function Obtain an estimate of the time delay of the current spread spectrum sequence signal. , is represented as:

[0153]

[0154] in, This represents the preset set of time delays.

[0155] S6.5: Calculate the precise estimate of the magnitude response and update the path number p=p+1 and the residual r. p .

[0156] Among them, the precise estimate of the magnitude response The calculation formula is as follows:

[0157]

[0158] The formula for calculating the updated residual is as follows:

[0159]

[0160] S6.6: Determine if the path number p is greater than the number of multipaths P. If yes, complete the estimation of all paths; otherwise, return to S6.4.

[0161] Step 7: Use the Doppler effect of the previous spread spectrum sequence signal to perform CFO compensation and resampling on the received signal of the next spread spectrum sequence. Construct a Rake receiver for the next spread spectrum sequence signal using the time delay and amplitude response of the current spread spectrum sequence signal.

[0162] Step seven is implemented through the following sub-steps:

[0163] S7.1: Update the spread spectrum sequence signal index k=k+1, and extract the received signal y of the kth spread spectrum sequence. k (t).

[0164] S7.2: Receive signal y for the kth spread spectrum sequence k (t) according to the original sampling interval T s of Interpolation is performed to obtain Then to Multiply by a frequency offset compensation term The received signal of the kth spread spectrum sequence after frequency offset compensation and resampling is obtained. .

[0165] in, This represents the Doppler estimate of the (k-1)th spread spectrum sequence signal; The calculation formula is as follows:

[0166]

[0167] S7.3: Construct a Rake receiver for the k-th spread spectrum sequence signal using the path delays and amplitude responses estimated from the (k-1)-th spread spectrum sequence signal. Specifically, it is expressed as:

[0168]

[0169] in, , Let represent the time delay and amplitude response of the p-th path estimated from the (k-1)-th spread spectrum sequence signal, respectively.

[0170] S7.4: Receive the k-th spread spectrum sequence signal after frequency offset compensation and resampling. The k-th spread spectrum sequence received symbol is obtained by sampling at the baseband rate. According to the Rake receiver of the k-th spread spectrum sequence signal and Construct the spread spectrum sequence symbol s for the k-th to be estimated k likelihood function .

[0171] Where, the likelihood function , It is a function that follows the mean. The covariance matrix is The Gaussian distribution.

[0172] Step 8: Repeat steps 5 through 7 until all spread spectrum sequences have been decided.

[0173] Corresponding to the aforementioned embodiments of the signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels, the present invention also provides embodiments of the signal receiving apparatus for spread spectrum underwater acoustic communication for long-distance time-varying channels.

[0174] The signal receiving device for spread spectrum underwater acoustic communication for long-distance time-varying channels provided in this embodiment of the invention includes one or more processors for implementing the signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels in the above embodiment.

[0175] The signal receiving device for spread spectrum underwater acoustic communication over long-distance time-varying channels, as described in this invention, can be applied to any device with data processing capabilities, such as a computer. The device can be implemented in software, hardware, or a combination of both. Taking software implementation as an example, as a logical device, it is formed by the processor of the device with data processing capabilities loading the corresponding computer program instructions from non-volatile memory into memory for execution. From a hardware perspective, in addition to the processor, memory, network interface, and non-volatile memory, the device with data processing capabilities in the embodiment may also include other hardware depending on its actual functions; these will not be elaborated further.

[0176] The specific implementation process of the functions and roles of each unit in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0177] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the present invention according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0178] This invention also provides a computer-readable storage medium storing a program thereon, which, when executed by a processor, implements the signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels described in the above embodiments.

[0179] The computer-readable storage medium can be an internal storage unit of any data processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data processing device, and can also be used to temporarily store data that has been output or will be output.

[0180] To verify the performance of the method of the present invention, corresponding performance simulation experiments were conducted, and the following examples illustrate this in detail.

[0181] To test the performance of the spread spectrum underwater acoustic communication signal reception method in this embodiment under long-distance communication scenarios, a simulation test was conducted under a long-delay Doppler spread channel. The simulation scenario was a platform area at a depth of 1000m, with the sound source located 800m above the seabed and the receiver located 500m above the seabed, for a test distance of 10km. Under this simulation scenario, the channel impulse response at a certain moment is as follows: Figure 3 As shown, the maximum delay spread can reach 250ms. Furthermore, the temporal coherence of this channel changes within 200s as follows: Figure 4 As shown, the channel exhibits rapid time-varying characteristics. Furthermore, the simulation employs spread spectrum modulation, selecting a set of spread spectrum sequences with weak cross-correlation. This set consists of 256 spread spectrum sequences, each 400 bits long, carrying 8 information bits.

[0182] The specific parameter settings are shown in Table 1 below.

[0183] Table 1 Specific Parameters

[0184]

[0185] Under these simulation parameters, each simulation transmitted a 200s spread spectrum signal. Within a signal-to-noise ratio (SNR) range of -20 to 0dB, 100 Monte Carlo experiments were performed for each SNR condition. The demodulation methods of this embodiment (using an adaptive Rake receiver) and those without an adaptive Rake receiver were compared. The bit error rate results for both demodulation methods within the SNR range of -20 to 0dB are as follows: Figure 5 As shown in the figure, the signal receiving method for spread spectrum underwater acoustic communication proposed in this embodiment effectively reduces the demodulation bit error rate under full signal-to-noise ratio conditions.

[0186] In summary, the signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels in this embodiment can achieve energy accumulation and channel tracking of multipath signals for time-varying channels with long delay-Doppler double spread, thereby ensuring long-distance communication between underwater mobile platforms.

[0187] It will be understood by those skilled in the art that the above descriptions are merely preferred examples of the invention and are not intended to limit the invention. Although the invention has been described in detail with reference to the foregoing examples, those skilled in the art can still modify the technical solutions described in the foregoing examples or make equivalent substitutions for some of the technical features. All modifications and equivalent substitutions made within the spirit and principles of the invention should be included within the scope of protection of the invention.

Claims

1. A signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels, characterized in that, Includes the following steps: S1: Obtain the passband communication signal received by the receiver, and obtain the baseband signal after down-conversion and low-pass filtering. After synchronization, the baseband signal is divided into blocks according to the pilot signal and the spread spectrum sequence signal. S2: Use the pilot signal to complete the initial channel estimation and obtain the initial Doppler estimate. And the estimated time delay and amplitude response for each path; S3: Using the Doppler obtained from pilot estimation, frequency offset compensation and resampling are performed on the received signal of the first spread spectrum sequence; S4: Using the time delay and amplitude response estimates obtained from the pilot estimation in S2, construct the first Rake receiver for the spread spectrum sequence signal to be estimated; S5: Combine the Rake receiver and utilize maximum likelihood estimation to make a decision on the current spread spectrum sequence and the corresponding log-likelihood ratio of each bit; S6: Using the already decided spread spectrum sequence, construct the likelihood function of the Doppler of the current spread spectrum sequence signal, and the cost function of the time delay and amplitude response. Then, use maximum likelihood estimation to estimate the Doppler of the current spread spectrum sequence signal, and then estimate the time delay and amplitude response of the current spread spectrum sequence signal by minimizing the cost function. S6 is specifically implemented through the following sub-steps: S6.1: Construct a Rake receiver for the current spread spectrum sequence signal based on the estimation results of the current spread spectrum sequence symbols and the estimated values ​​of the time delay and amplitude response of each path of the previous spread spectrum sequence signal; S6.2: Using the Rake receiver of the current spread spectrum sequence signal and the signal vector obtained by sampling the received signal of the current spread spectrum sequence according to the sampling interval, construct the likelihood function of Doppler; pre-set a Doppler set and use maximum likelihood estimation to obtain a coarse estimate of Doppler; S6.3: Initialize the path number p=1, residual r p It is equal to the signal vector obtained by sampling the received signal of the current spread spectrum sequence according to the sampling interval, and the number of multipaths is given; S6.4: Construct a cost function for time delay using the estimation results and residuals of the current spread spectrum sequence symbols; Given a predefined set of time delays, the estimated time delay of the current spread spectrum sequence signal is obtained by minimizing the cost function related to the time delay. S6.5: Calculate the precise estimate of the magnitude response, update the path number p=p+1, and update the residuals; S6.6: Determine if the path number p is greater than the number of multipaths. If yes, complete the estimation of all paths. If no, return to S6.

4. S7: Use the Doppler of the previous spread spectrum sequence signal to perform frequency offset compensation and resampling on the received signal of the next spread spectrum sequence, and use the time delay and amplitude response of the current spread spectrum sequence signal to construct the Rake receiver for the next spread spectrum sequence signal; S8: Repeat S5~S7 until all spread spectrum sequences have been decided.

2. The signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels according to claim 1, characterized in that, S2 is implemented through the following sub-steps: S2.1: First, construct the likelihood function with respect to Doppler using the pilot signal; S2.2: Construct the cost function for Doppler, and use Newton's correction to refine the Doppler estimate, thus obtaining a precise estimate of Doppler. ; S2.3: Using Doppler precision estimation, the pilot signal is processed according to the original sampling interval. The interpolation is performed by multiplying the result by a frequency offset compensation term to obtain the frequency offset compensated and resampled pilot signal; S2.4: The pilot signal after frequency offset compensation and resampling is sampled according to the original sampling interval to obtain the pilot symbol; Initialize the path number p=1, set the residual to the pilot symbol, and specify the number of multipaths; S2.5: Construct a cost function for the time delay of the pilot signal corresponding to the time period using the residual; Given a set of time delays, a coarse estimate of the time delay is obtained by minimizing the cost function, and then a fine estimate of the time delay is obtained by using Newton correction. S2.6: Calculate the precise estimate of the magnitude response, update the path number p=p+1, and update the residuals; S2.7: Determine if p is greater than the number of multipaths. If yes, complete the estimation of all paths. If no, return to S2.

5.

3. The signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels according to claim 2, characterized in that, S3 is implemented through the following sub-steps: S3.1: Intercept the first spread spectrum sequence received signal; S3.2: The received signal of the first spread spectrum sequence is processed according to the original sampling interval. The result is then interpolated by a factor of 1, and a frequency offset compensation term is added to the interpolated result to obtain the first spread spectrum sequence received signal after frequency offset compensation and resampling.

4. The signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels according to claim 1, characterized in that, S4 is implemented through the following sub-steps: S4.1: Construct the Rake receiver for the first spread spectrum sequence signal using the precise estimates of the path delay and amplitude response obtained from the pilot estimation. S4.2: The received signal of the first spread spectrum sequence after frequency offset compensation and resampling is sampled at the baseband rate to obtain the first spread spectrum sequence received symbol; Based on the Rake receiver of the first spread spectrum sequence signal and the first received spread spectrum sequence symbol, construct the likelihood function for the first spread spectrum sequence symbol to be estimated; S4.3: Initialize the spread spectrum sequence signal index k=1.

5. The signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels according to claim 1, characterized in that, S5 is implemented through the following sub-steps: S5.1: Use maximum likelihood estimation to make symbol decisions on the current spread spectrum sequence signal and obtain the estimation result of the first spread spectrum sequence symbol to be estimated; S5.2: According to the nth b The value of the nth bit is either 0 or 1. The spread spectrum sequence set is divided into two sets, and the value of the nth bit carried by the current spread spectrum sequence is calculated. b Log-likelihood ratio of bits.

6. The signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels according to claim 1, characterized in that, S7 is implemented through the following sub-steps: S7.1: Update the spread spectrum sequence signal index k=k+1, and extract the received signal y of the kth spread spectrum sequence. k (t); S7.2: Receive signal y for the kth spread spectrum sequence k (t) according to the original sampling interval The interpolation is performed by a factor of 1, and the interpolation result is multiplied by a frequency offset compensation term to obtain the received signal of the k-th spread spectrum sequence after frequency offset compensation and resampling. ;in, This represents the Doppler estimate of the (k-1)th spread spectrum sequence signal; S7.3: Construct a Rake receiver for the k-th spread spectrum sequence signal using the path delay and amplitude response estimated from the (k-1)-th spread spectrum sequence signal; S7.4: Receive the k-th spread spectrum sequence signal after frequency offset compensation and resampling. The k-th spread spectrum sequence received symbol is obtained by sampling at the baseband rate. According to the Rake receiver of the k-th spread spectrum sequence signal and Construct the likelihood function for the k-th spread spectrum sequence symbol to be estimated.

7. A signal receiving device for spread spectrum underwater acoustic communication for long-distance time-varying channels, characterized in that, It includes one or more processors for implementing the signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels as described in any one of claims 1 to 6.

8. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by the electronic device, cause the electronic device to implement the signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, It stores a program that, when executed by a processor, implements the signal receiving method for spread spectrum underwater acoustic communication for long-distance time-varying channels as described in any one of claims 1 to 6.

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