Analog method for underwater optical communication transmission positioning integration

Abstract

The application discloses an underwater optical communication transmission positioning integrated simulation method, which comprises the following steps: a light emitting diode of a sending end sends a signal to a surrounding receiving end; when the receiving end receives the signal from the sending end, the receiving end sends a light intensity signal to the sending end; the sending end receives the light intensity signal through a prism, calculates corresponding light intensity information through the light intensity signal, calculates the position of the sending end relative to the receiving end according to the light intensity information, and performs underwater node positioning; the sending end sends an acknowledgement signal to the receiving end, judges whether the handshake is completed according to the acknowledgement signal, if yes, establishes a link between the sending end and the receiving end, and maintains the link through optical pointing and tracking, otherwise, returns to step S1 and performs the next positioning. The application solves the problems that the expression of a beam spread function BSF value is relatively complex, the calculation time is long, and a certain scattering phase function is simplified and not scalable in the underwater wireless optical communication transmission positioning process.

Description

Technical Field

[0001] This invention belongs to the field of underwater wireless communication technology, specifically relating to a simulation method for integrated underwater optical communication transmission and positioning. Background Technology

[0002] Underwater wireless communication refers to data transmission in an unguided underwater environment using wireless carriers, namely radio frequency (RF) waves, sound waves, and light waves. Compared with RF and acoustic communication, underwater wireless optical communication can provide higher transmission bandwidth and higher data rates. Therefore, underwater wireless optical communication (UWOC), with its advantages of high transmission rate, low latency, and high security, has become a popular underwater communication method recently.

[0003] The beam spread function (BSF) describes the relationship between the irradiance received by the receiver and the distance from the main beam axis in underwater wireless optical communication (UWOC) at a specific link length. Compared with the traditional Beer-Lambert model, the BSF can more accurately characterize the absorption and scattering effects of light beam propagation in water. In UWOC, irradiance can be used for AUV docking at the transmitting end and for underwater node positioning. Traditional underwater irradiance calculations require Monte Carlo simulations or complex theoretical solutions, involving multiple integration operations with Bessel functions. Furthermore, the BSF values ​​calculated using different scattering phase functions (SPFs) also vary.

[0004] Existing simplified expressions for the beam spread function (BSF) value involve hypergeometric functions and infinite series, remaining relatively complex and computationally time-consuming. Furthermore, they primarily simplify a single scattering phase function and lack scalability. Summary of the Invention

[0005] This invention provides a simulation method for integrated underwater optical communication transmission and positioning, which solves the problems of relatively complex expressions for beam spread function (BSF) values, long calculation times, and lack of scalability due to simplification of a certain scattering phase function during underwater wireless optical communication transmission and positioning.

[0006] To solve the above-mentioned technical problems, the technical solution of the present invention is: a simulation method for integrated underwater optical communication transmission and positioning, comprising the following steps:

[0007] S1. The transmitter sends a signal to the surrounding receivers through the LED of the transmitter, and keeps the transmitter relatively stationary so that the receivers can determine the location.

[0008] S2. When the receiving end receives a signal from the transmitting end, it performs a cooperative scan through the optical receiver at the receiving end and sends a light intensity signal back to the transmitting end.

[0009] S3. Receive the light intensity signal through the prism at the transmitting end, calculate the corresponding light intensity information based on the light intensity signal, calculate its own position relative to the receiving end based on the light intensity information, and perform underwater node positioning.

[0010] S4. Send an acknowledgment signal from the sending end to the receiving end. Determine whether the handshake is complete based on the acknowledgment signal. If yes, establish a link between the sending end and the receiving end and maintain it through optical pointing and tracking. Otherwise, return to step S1 and perform the next positioning.

[0011] The beneficial effects of this invention are as follows: This invention establishes an optical communication link between the transmitting and receiving ends, and calculates its own position relative to the receiving end using light intensity signals for underwater node positioning. After establishing the link between the transmitting and receiving ends, it can be maintained through optical pointing and tracking. Furthermore, by simplifying the calculation process of the beam spread function (BSF) value relative to the receiving end, it solves the problems of long calculation time for the original BSF value and lack of scalability by simplifying a certain scattering phase function, thus improving the speed of underwater optical communication transmission and positioning.

[0012] Furthermore, the specific steps of step S3 are as follows:

[0013] S31. Receive the light intensity signal through the prism at the transmitting end, and calculate the corresponding light intensity information based on the light intensity signal;

[0014] S32. Calculate the beam spread function (BSF) value using light intensity information to simplify the calculation process of the BSF value, and calculate the channel gain coefficient using the simplified BSF value.

[0015] S33. Calculate the signal strength RSS in the optical intensity information using the channel gain coefficient;

[0016] S34. Input the signal strength RSS into the BP neural network and output the position of the transmitter relative to the receiver to perform underwater node localization.

[0017] The beneficial effects of the above-mentioned further scheme are: underwater node positioning can be achieved using light intensity information during the underwater node positioning process, and the BP neural network can be used to quickly locate in various underwater environments, thereby improving positioning accuracy and reducing positioning time.

[0018] Furthermore, the specific steps for simplifying the beam spread function (BSF) value in step S32 are as follows:

[0019] A1. Select the scattering phase function, integrate using the Gauss-Legendé formula, and approximate the Hankel transform of the scattering phase function to obtain the Hankel transform P_legendre(v) of the scattering phase function obtained using the Gauss-Legendé integration formula.

[0020] A2. Fit the Hankel transform of the scattering phase function P_legendre(v) using a symmetric α-stable distribution model or a hybrid model to obtain the fitted model and its parameters.

[0021] A3. Substitute the fitted model and its parameters into the expression for the beam spread function (BSF) value in step S32, and simplify it using the Gauss-Laguerre integral formula to obtain the simplified BSF value.

[0022] The beneficial effects of the above-mentioned further scheme are as follows: During the calculation process, the Gauss-Legendal formula and the Gauss-Laguerre formula are used to simplify the beam spread function (BSF), avoiding the use of integrals to calculate the BSF. Compared with the original multiple integral calculation of the BSF, the simplified BSF calculation method provided by this invention has the advantages of fast calculation speed, high fitting accuracy, and strong scalability. It requires extremely short time to accurately simulate various scattering phase functions under different water qualities, distances, and beam divergence angles, and is applicable to various scattering phase functions (SPFs), allowing for rapid and accurate determination of irradiance.

[0023] Furthermore, the expression for integration using the Gauss-Legendé formula in step A1 is:

[0024]

[0025] Where f(x) represents the Hankel transform function of the original scattering phase function, x represents the independent variable of the Hankel transform of the scattering phase function, a' represents the lower limit of the integral of the Hankel transform of the scattering phase function, b' represents the upper limit of the integral of the Hankel transform of the scattering phase function, and w k Let x represent the weight of the k-th term in the Gauss-Legend integral formula. k Let represent the k-th node of the Gauss-Legendé integral formula, and T represent the order of the Gauss-Legendé integral formula.

[0026] Furthermore, the expression for the symmetric α-stable distribution model in A2 is:

[0027]

[0028] in, Let φ(·) represent the symmetric α-stable distribution model, φ(·) represent the characteristic function of the random variable, ω represent the variable of the characteristic function, j represent the imaginary number, α represent the characteristic exponent, β represent the symmetry parameter, γ represent the scale parameter, v represent the spatial frequency domain variable, δ represent the location parameter, and sign(·) represent the sign function.

[0029] The expression for the hybrid model in A2 is:

[0030]

[0031] in, Let Y represent the Gaussian mixture model, and A represent the order of the Gaussian mixture model. q Let B represent the q-th parameter controlled by the weights and mean of the Gaussian function. q Let C represent the q-th parameter controlled by the weights of the Gaussian function. q Let G represent the standard deviation of the Gaussian function of the q-th term, G represent the order of the exponential model, and T represent the standard deviation of the Gaussian function of the q-th term. f Q represents the rate of change of the f-th term in the exponential model. f represents the weight parameter of the f-th term in the exponential model, and exp(·) represents the exponential function.

[0032] The beneficial effects of the above-mentioned further scheme are as follows: compared with the Gaussian mixture model and the exponential model alone, the symmetric α-stable distribution model and the mixture model of the present invention improve the accuracy of fitting the Hankel transform function of the scattering phase function within a limited complexity, making the fitted Hankel transform function of the scattering phase function more closely resemble the original Hankel transform function of the scattering phase function.

[0033] Furthermore, the expression for the Gauss-Laguerre integral formula in step A3 is:

[0034]

[0035] Where M represents the order of the Gauss-Laguerre integral formula, F(v) represents the symmetric α-stable distribution model or mixture model, v represents the spatial frequency domain variable, and w i Let F(v) represent the weight of the i-th term in the Gauss-Laguerre integral formula. i ) represents the symmetric α-stable distribution model or hybrid model after substituting the i-th node, v i Let represent the i-th node of the Gauss-Laguerre integral formula.

[0036] Furthermore, the simplified expression for the beam spread function (BSF) value in step A3 is as follows:

[0037]

[0038]

[0039]

[0040] in, This represents the simplified beam spread function (BSF) value using a symmetric α-stable distribution model. The simplified beam spread function (BSF) value using the hybrid model is represented by r, which represents the radial distance between the receiver aperture center and the receiver plane beam center, assuming the beam center is perpendicular to the beam axis. c represents the attenuation coefficient corresponding to seawater, L represents the link distance between the laser source and the receiver plane, J0(·) represents the zeroth-order Bessel function of the first kind, and P... t W(L) represents the power of the emitted laser source, and W(L) represents the wave propagation distance L after passing through a link. Equal radius of line, S(v) i L) represents an intermediate variable, b represents the scattering coefficient corresponding to seawater, N represents the number of terms in the Gauss-Hermitian integral formula, and R d Let v represent the weight of the d-th term in the Gauss-Hermitian integral formula. d Let d represent the node of the Gauss-Hermet integral formula, and erf(·) represent the error function.

[0041] Furthermore, the expression for the channel gain coefficient in step S32 is as follows:

[0042] h = h pl ·h t

[0043]

[0044] Where h represents the channel gain coefficient, h pl h represents the alignment error attenuation coefficient. t P represents the light intensity fluctuation coefficient. t P represents the power of the emitted laser source. r S represents the average optical power at the receiving end. r Indicates the receiver's reception area, BSF US (r,L) represents the beam spread function (BSF) value simplified using the symmetric α-stable distribution model. Alternatively, a simplified beam spread function (BSF) value can be used from a hybrid model. Both m and n represent the integration variables during integration.

[0045] Furthermore, the formula for calculating the signal strength RSS in step S33 is as follows:

[0046] RSS = ρP t hx'+z

[0047] x'∈{0,2}

[0048] Where ρ represents the photoelectric conversion efficiency, P t Let represent the emitted laser source power, h represent the channel gain coefficient, x' represent the emitted binary amplitude shift keying (OOK) modulated signal, and z represent the signal that follows the (0, σ) property. 2 Gaussian white noise.

[0049] The beneficial effects of the above-mentioned further scheme are as follows: by using the beam spread function (BSF) value which can be solved quickly, the channel gain coefficient in the underwater environment can be solved quickly. Based on this, the purpose of quickly obtaining light intensity information can be achieved, thereby realizing the purpose of quickly locating underwater nodes. Attached Figure Description

[0050] Figure 1 This is a flowchart of the simulation method for the integrated underwater optical communication transmission and positioning of the present invention.

[0051] Figure 2 A comparison of the time required to solve the beam spread function (BSF) for different values ​​of r.

[0052] Figure 3 A comparison of the time required to solve the beam spread function (BSF) for different L values.

[0053] Figure 4 A comparison of the time required to solve the beam spread function (BSF) at different θ values.

[0054] Figure 5 A comparison of the time required to solve for the beam spread function (BSF) at different locations. Detailed Implementation

[0055] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

[0056] Example

[0057] like Figure 1 As shown, this invention provides a simulation method for integrated underwater optical communication transmission and positioning, comprising the following steps:

[0058] S1. The transmitter sends a signal to the surrounding receivers through the LED of the transmitter, and keeps the transmitter relatively stationary so that the receivers can determine the location.

[0059] S2. When the receiving end receives a signal from the transmitting end, it performs a cooperative scan through the optical receiver at the receiving end and sends a light intensity signal back to the transmitting end.

[0060] S3. Receive the light intensity signal through the prism at the transmitting end, calculate the corresponding light intensity information based on the light intensity signal, calculate its own position relative to the receiving end based on the light intensity information, and perform underwater node positioning.

[0061] S4. Send an acknowledgment signal from the sending end to the receiving end. Determine whether the handshake is complete based on the acknowledgment signal. If yes, establish a link between the sending end and the receiving end and maintain it through optical pointing and tracking. Otherwise, return to step S1 and perform the next positioning.

[0062] In this embodiment, the light-emitting diode of the transmitting end broadcasts a signal to the surrounding spherical optical base station, i.e. the receiving end. At the same time, the transmitting end adjusts itself to maintain a relatively stationary state for a short period of time to facilitate the receiving end in determining its location.

[0063] When the receiver receives a signal from the transmitter, it performs a coordinated scan using the receiver's optical receivers. After receiving the intensity information of the emitted light within a short time, the transmitter estimates its own position. Each optical receiver's beacon signal records the orientation of its own laser beam.

[0064] When the prism mounted on the transmitter receives a light intensity signal, the transmitter extracts the beam information from the signal and estimates its position relative to the receiver. It then sends an acknowledgment signal to complete the handshake. A link is then established between the transmitter and receiver and maintained through optical pointing and tracking. If the attempt fails, the process is repeated until the maximum number of attempts is reached.

[0065] The specific steps of step S3 are as follows:

[0066] S31. Receive the light intensity signal through the prism at the transmitting end, and calculate the corresponding light intensity information based on the light intensity signal;

[0067] S32. Calculate the beam spread function (BSF) value using light intensity information to simplify the calculation process of the BSF value, and calculate the channel gain coefficient using the simplified BSF value.

[0068] S33. Calculate the signal strength RSS in the optical intensity information using the channel gain coefficient;

[0069] S34. Input the signal strength RSS into the BP neural network and output the position of the transmitter relative to the receiver to perform underwater node localization.

[0070] In this embodiment, the received signal strength (RSS) of the optical receiver constitutes a one-dimensional array of length S, which serves as the input for deep learning. When the relative positions of the transmitter and receiver or the emission direction of the laser beam are different, the RSS of the various signal strengths detected by the optical receiver on the receiver are not exactly the same. This can be used as a feature for deep learning to train the network model to estimate the relative position and beam direction of the emitted laser, and output the position information of the transmitter relative to the receiver, thereby performing underwater node localization.

[0071] The expression for the original beam spread function (BSF) value in step S32 is:

[0072]

[0073] Where B(r,L) represents the beam spread function (BSF) value, E(r,L) represents the Gaussian irradiance distribution in the spatial coordinate system, E(v,L) represents the Gaussian irradiance distribution in the spatial frequency domain, exp(·) represents the exponential function, c represents the attenuation coefficient corresponding to seawater, r represents the radial distance between the center of the receiver aperture and the center of the receiver plane beam, assuming the beam center is perpendicular to the beam axis, L represents the link distance between the laser source and the receiving plane, v represents the spatial frequency domain variable, b represents the scattering coefficient corresponding to seawater, p(·) represents the Hankel transform of the scattering phase function, l represents the integral variable, and J0(·) represents the zeroth-order Bessel function of the first kind.

[0074] The specific steps for simplifying the beam spread function (BSF) value in step S32 are as follows:

[0075] A1. Select the scattering phase function, integrate using the Gauss-Legendé formula, and approximate the Hankel transform of the scattering phase function to obtain the Hankel transform P_legendre(v) of the scattering phase function obtained using the Gauss-Legendé integration formula.

[0076] A2. Fit the Hankel transform of the scattering phase function P_legendre(v) using a symmetric α-stable distribution model or a hybrid model to obtain the fitted model and its parameters.

[0077] A3. Substitute the fitted model and its parameters into the expression for the beam spread function (BSF) value in step S32, and simplify it using the Gauss-Laguerre integral formula to obtain the simplified BSF value.

[0078] The expression for integration using the Gauss-Legendé formula in step A1 is:

[0079]

[0080] Where f(x) represents the Hankel transform function of the original scattering phase function, x represents the independent variable of the Hankel transform of the scattering phase function, a' represents the lower limit of the integral of the Hankel transform of the scattering phase function, b' represents the upper limit of the integral of the Hankel transform of the scattering phase function, and w k Let x represent the weight of the k-th term in the Gauss-Legend integral formula. k Let represent the k-th node of the Gauss-Legendé integral formula, and T represent the order of the Gauss-Legendé integral formula.

[0081] The expression for the symmetric α-stable distribution model in A2 is:

[0082]

[0083] in, Let φ(·) represent the symmetric α-stable distribution model, φ(·) represent the characteristic function of the random variable, ω represent the variable of the characteristic function, j represent the imaginary number, α represent the characteristic exponent, β represent the symmetry parameter, γ represent the scale parameter, v represent the spatial frequency domain variable, δ represent the location parameter, and sign(·) represent the sign function.

[0084] The expression for the hybrid model in A2 is:

[0085]

[0086] in, Let Y represent the Gaussian mixture model, and A represent the order of the Gaussian mixture model. q Let B represent the q-th parameter controlled by the weights and mean of the Gaussian function. q Let C represent the q-th parameter controlled by the weights of the Gaussian function. q Let G represent the standard deviation of the Gaussian function of the q-th term, G represent the order of the exponential model, and T represent the standard deviation of the Gaussian function of the q-th term. f Q represents the rate of change of the f-th term in the exponential model. f represents the weight parameter of the f-th term in the exponential model, and exp(·) represents the exponential function.

[0087] From the standard characteristic function of the random variables in the symmetric α-stable distribution model, the standard expression of the symmetric α-stable distribution model is:

[0088]

[0089] Where Γ(·) represents the gamma function.

[0090] The characteristic exponent α reflects both the impact intensity of the stable distribution and the thickness of the tail of the distribution function. The symmetry parameter β determines the degree of distortion in the distribution, and the scale parameter γ determines the degree to which the stable distribution variable deviates from its mean. Considering that the characteristic function is a Fourier transform of the probability density function, which determines the offset of the probability density function on the x-axis, the method of moments can be used to estimate the characteristic exponent α, the symmetry parameter β, the scale parameter γ, and the location parameter δ.

[0091] When α≠1, the expression for the symmetric α-stable distribution model can be simplified using the Gauss-Hermitian integral formula as follows:

[0092]

[0093] Where N represents the number of terms in the Gauss-Hermitian integral formula, and R... d Let v represent the weight of the d-th term in the Gauss-Hermitian integral formula. d Let d represent the node of the Gauss-Hermet integral formula.

[0094] The expression for Gauss-Hermitian integral formula is:

[0095]

[0096] The expression for the Gauss-Laguerre integral formula in step A3 is as follows:

[0097]

[0098] Where M represents the order of the Gauss-Laguerre integral formula, F(v) represents the symmetric α-stable distribution model or mixture model, v represents the spatial frequency domain variable, and w i Let F(v) represent the weight of the i-th term in the Gauss-Laguerre integral formula. i ) represents the symmetric α-stable distribution model or hybrid model after substituting the i-th node, v i Let represent the i-th node of the Gauss-Laguerre integral formula.

[0099] The simplified expression for the beam spread function (BSF) value in step A3 is as follows:

[0100]

[0101]

[0102]

[0103] in, This represents the simplified beam spread function (BSF) value using a symmetric α-stable distribution model. The simplified beam spread function (BSF) value using the hybrid model is represented by r, which represents the radial distance between the receiver aperture center and the receiver plane beam center, assuming the beam center is perpendicular to the beam axis. c represents the attenuation coefficient corresponding to seawater, L represents the link distance between the laser source and the receiver plane, J0(·) represents the zeroth-order Bessel function of the first kind, and P... t W(L) represents the power of the emitted laser source, and W(L) represents the wave propagation distance L after passing through a link. Equal radius of line, S(v) i L) represents an intermediate variable, b represents the scattering coefficient corresponding to seawater, N represents the number of terms in the Gauss-Hermitian integral formula, and R d Let v represent the weight of the d-th term in the Gauss-Hermitian integral formula. d Let d represent the node of the Gauss-Hermet integral formula, and erf(·) represent the error function.

[0104] In this embodiment, the simplified beam spread function (BSF) value using the mixture model is a simplified BSF value obtained by combining the Gaussian mixture model and the exponential model. Compared with the Gaussian mixture model and the exponential model alone, it improves the accuracy of fitting the Hankel transform function of the scattering phase function within a limited complexity, making the fitted Hankel transform function of the scattering phase function more closely resemble the original Hankel transform function of the scattering phase function, and greatly reducing the time required to solve for the BSF value.

[0105] The expression for the channel gain coefficient in step S32 is as follows:

[0106] h = h pl ·h t

[0107]

[0108] Where h represents the channel gain coefficient, h pl h represents the alignment error attenuation coefficient. t P represents the light intensity fluctuation coefficient. t P represents the power of the emitted laser source. r S represents the average optical power at the receiving end. r Indicates the receiver's reception area, BSF US (r,L) represents the beam spread function (BSF) value simplified using the symmetric α-stable distribution model. Alternatively, a simplified beam spread function (BSF) value can be used from a hybrid model. Both m and n represent the integration variables during integration.

[0109] In this embodiment, the light intensity fluctuation coefficient h t The light intensity fluctuations caused by turbulence affect the reception of optical signals, and the light intensity fluctuation coefficient ht The probability density distribution function can be simulated using the mixed exponential-generalized gamma distribution EGG model:

[0110] f EGG (h t )=ω e f E (h t ;λ e )+(1-ω e )f GG (h t ;[a”,b”,c”])

[0111]

[0112]

[0113] Among them, f EGG (h t ) represents the mixed exponential-generalized gamma distribution EGG model, ω e f represents the mixed weighting factor. E (h t ;λ e ) represents a negative exponential function, λ e f represents the negative exponential parameter. GG (h t [a”,b”,c”]) represents the generalized gamma distribution function, where a” and c” are both shape parameters of the generalized gamma distribution, b” represents the scale parameter of the generalized gamma distribution, exp(·) represents the exponential function, and Γ(·) represents the gamma function.

[0114] The mixing index-generalized gamma distribution (EGG) model takes into account the effects of different bubble densities and sizes, salt water, and temperature gradients on light intensity fluctuations in turbulence.

[0115] When the receiver's receiving area S r When the value is sufficiently small, the alignment error attenuation coefficient h pl It can be represented as:

[0116]

[0117] The formula for calculating the signal strength RSS in step S33 is as follows:

[0118] RSS = ρP t hx'+z

[0119] x'∈{0,2}

[0120] Where ρ represents the photoelectric conversion efficiency, P tLet represent the emitted laser source power, h represent the channel gain coefficient, x' represent the emitted binary amplitude shift keying (OOK) modulated signal, and z represent the signal that follows the (0, σ) property. 2 Gaussian white noise.

[0121] In this embodiment, as Figure 2 , Figure 3 , Figure 4 and Figure 5 As shown, the time required to solve for the beam spread function (BSF) using the hybrid model of this invention, the fitting formula US, the original triple integral OTI, and the Monte Carlo simulation (MC) differs under different conditions. Figure 2 In the figures, r represents 0m, 0.4m, and 0.8m, respectively, where r denotes the radial distance between the center of the receiver aperture and the center of the beam in the receiver plane, assuming the beam center is perpendicular to the beam axis. Figure 3 In the figures, L represents 5m, 10m, and 15m respectively, where L indicates the link distance between the laser source and the receiving plane. Figure 4 In the above, θ is 0.01 rad, 0.05 rad, and 0.1 rad, respectively, where θ represents the beam divergence angle.

[0122] By simplifying the beam spread function (BSF) value, from the perspective of computational time consumption, our proposed hybrid model fitting algorithm only requires O(10^6) time. -4 It takes O(10^2) seconds to calculate the beam spread function (BSF) value, while the original triple integral OTI or Monte Carlo simulation MC requires O(10^2) seconds. 2 )Second.

[0123] Furthermore, using the symmetric α-stable distribution model provides higher accuracy and better results than using the hybrid model to simulate various scattering phase functions. However, it consumes slightly more computation time than using the hybrid model to calculate a beam spread function (BSF) value, but it is still within O(10^6) time. -4 This reduces the time required by the original triple integral OTI or Monte Carlo simulation (MC) to 1000 seconds, significantly lower than the time required by the original OTI or Monte Carlo simulation. Therefore, in practical situations, a symmetric α-stable distribution model or a hybrid model can be selected to calculate the beam spread function (BSF) value for underwater wireless optical communication transmission and positioning, greatly reducing the time required for underwater wireless optical communication transmission and positioning.

[0124] In the application of the integrated underwater wireless optical communication transmission and positioning system, the amount of precise irradiance data generated by the method according to the present invention is 10. 5 At this scale, deep learning is used for positioning, with an average positioning error of less than 0.8m and a mean square error (MSE) of less than 1.5. This represents a significant improvement compared to existing technologies with an average positioning error greater than 4m and an MSE greater than 6.

[0125] In summary, the method of this invention can accurately simulate various scattering phase functions under different water qualities, distances, and beam divergence angles in a very short time, and is applicable to a variety of scattering phase functions (SPF). This demonstrates that the method of this invention can solve for the beam spread function (BSF) value very quickly, and can also perform underwater wireless optical communication transmission and positioning very quickly while ensuring accuracy.

[0126] During communication, the transmitting end simultaneously transmits information and positioning results to the receiving end. After a certain period of time, the positions of the transmitting and receiving ends change due to the influence of water flow. In order to maintain the stability of the communication link, the receiving end returns the updated position information to the transmitting end, enabling the transmitting end to adjust the laser emission direction in time. The method of this invention calculates position information extremely quickly, solving the problem of relatively complex expressions and long calculation times for the beam spread function (BSF) value in underwater wireless optical communication transmission positioning. Furthermore, it can simplify various scattering phase functions, solving the problem of lack of scalability.

Claims

1. A simulation method for integrated underwater optical communication transmission and positioning, characterized in that, Includes the following steps: S1. The transmitter sends a signal to the surrounding receivers through the LED of the transmitter, and keeps the transmitter relatively stationary so that the receivers can determine the location. S2. When the receiving end receives a signal from the transmitting end, it performs a cooperative scan through the optical receiver at the receiving end and sends a light intensity signal back to the transmitting end. S3. Receive the light intensity signal through the prism at the transmitting end, calculate the corresponding light intensity information based on the light intensity signal, calculate its own position relative to the receiving end based on the light intensity information, and perform underwater node positioning. S4. Send an acknowledgment signal from the sending end to the receiving end. Determine whether the handshake is complete based on the acknowledgment signal. If yes, establish a link between the sending end and the receiving end and maintain it through optical pointing and tracking. Otherwise, return to step S1 and perform the next positioning. The specific steps of step S3 are as follows: S31. Receive the light intensity signal through the prism at the transmitting end, and calculate the corresponding light intensity information based on the light intensity signal; S32. Calculate the beam spread function (BSF) value using light intensity information to simplify the calculation process of the BSF value, and calculate the channel gain coefficient using the simplified BSF value. S33. Calculate the signal strength RSS in the optical intensity information using the channel gain coefficient; S34. Input the signal strength RSS into the BP neural network and output the position of the transmitter relative to the receiver to perform underwater node localization. The specific steps for simplifying the beam spread function (BSF) value in step S32 are as follows: A1. Select the scattering phase function, integrate using the Gauss-Legendé formula, and approximate the Hankel transform of the scattering phase function to obtain the Hankel transform P_legendre(v) of the scattering phase function obtained using the Gauss-Legendé integration formula. A2. Using symmetry The stable distribution model or the hybrid model is fitted to the Hankel transform of the scattering phase function P_legendre(v) to obtain the fitted model and its parameters; A3. Substitute the fitted model and its parameters into the expression for the beam spread function (BSF) value in step S32, and simplify it using the Gauss-Laguerre integral formula to obtain the simplified BSF value.

2. The simulation method for integrated underwater optical communication transmission and positioning according to claim 1, characterized in that, The expression for integration using the Gauss-Legendé formula in step A1 is: in, The Hankel transform function represents the original scattering phase function. The independent variable represents the Hankel transform of the scattering phase function. This represents the lower bound of the Hankel transform integral for the scattering phase function. This represents the upper limit of the Hankel transform integral of the scattering phase function. The Gauss-Legends integral formula is expressed as follows: The weight of the item, The first expression in the Gauss-Legendé integral formula is... Item node, This indicates the order of the Gauss-Legendé integral formula.

3. The simulation method for integrated underwater optical communication transmission and positioning according to claim 1, characterized in that, Symmetry in A2 The expression for the stable distribution model is: in, Represents symmetry Stable distribution model The characteristic function of a random variable, The variable representing the characteristic function, represents an imaginary number, Represents the characteristic index, Represents the symmetry parameter. Indicates the scale parameter. Represents spatial frequency domain variables, Indicates position parameters, Represents a symbolic function; The expression for the hybrid model in A2 is: in, Indicates a hybrid model. This indicates the order of the Gaussian mixture model. This represents the first [function] controlled by the weights and mean of a Gaussian function. Item parameters, This indicates the first [function] controlled by the weights of the Gaussian function. Item parameters, Indicates the first The standard deviation of the Gaussian function of the term, Indicates the order of the exponential model. Indicating the exponential model, the first... The rate of change of the term, Indicating the exponential model, the first... The weight parameters of the item, This represents an exponential function.

4. The simulation method for integrated underwater optical communication transmission and positioning according to claim 3, characterized in that, The expression for the Gauss-Laguerre integral formula in step A3 is as follows: in, This indicates the order of the Gauss-Laguerre integral formula. Represents symmetry Stable distribution model or mixture model, Represents spatial frequency domain variables, The Gauss-Laguerre integral formula is expressed as follows: The weight of the item, Indicates substitution into the first Symmetry after the item node Stable distribution model or mixture model, The first expression of the Gauss-Laguerre integral formula Item node.

5. The simulation method for integrated underwater optical communication transmission and positioning according to claim 4, characterized in that, The simplified expression for the beam spread function (BSF) value in step A3 is as follows: in, Indicates the use of symmetry The simplified beam spread function (BSF) value of the stable distribution model. This represents the simplified beam spread function (BSF) value using the hybrid model. This represents the radial distance between the center of the receiver aperture and the center of the beam in the receiver plane, assuming the beam center is perpendicular to the beam axis. This represents the attenuation coefficient corresponding to seawater. This indicates the link distance between the laser source and the receiving plane. Denotes the zeroth-order Bessel function of the first kind. Indicates the power of the laser source. This represents the distance a wave travels along a link. After Equal line radius Indicates intermediate variables. This represents the scattering coefficient corresponding to seawater. This indicates the number of terms in the Gauss-Hermitian integral formula. The Gauss-Hermitian integral formula is expressed as follows: The weight of the item, The first expression of the Gauss-Hermitian integral formula Item node, This represents the error function.

6. The simulation method for integrated underwater optical communication transmission and positioning according to claim 5, characterized in that, The expression for the channel gain coefficient in step S32 is as follows: in, Represents the channel gain coefficient. This represents the alignment error attenuation coefficient. This represents the light intensity fluctuation coefficient. Indicates the power of the laser source. This represents the average optical power at the receiving end. Indicates the receiving area of ​​the receiver. Indicates the use of symmetry Simplified beam spread function (BSF) value of stable distribution model Alternatively, a simplified beam spread function (BSF) value can be used from a hybrid model. , and Both represent the integration variables during integration.

7. The simulation method for integrated underwater optical communication transmission and positioning according to claim 1, characterized in that, The formula for calculating the signal strength RSS in step S33 is as follows: in, Indicates photoelectric conversion efficiency. Indicates the power of the laser source. Represents the channel gain coefficient. This indicates the transmitted binary amplitude keying (OOK) modulated signal. To show obedience Gaussian white noise.

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