CN111723478A - Clear ocean water quality UWOC system channel impulse response fitting function solving method and system - Google Patents

Clear ocean water quality UWOC system channel impulse response fitting function solving method and system Download PDF

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CN111723478A
CN111723478A CN202010527287.9A CN202010527287A CN111723478A CN 111723478 A CN111723478 A CN 111723478A CN 202010527287 A CN202010527287 A CN 202010527287A CN 111723478 A CN111723478 A CN 111723478A
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impulse response
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CN111723478B (en
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谭跃跃
李岳衡
刘陕陕
史宏强
居美艳
黄平
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Hohai University HHU
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Abstract

The invention discloses a method for solving a channel impulse response fitting function of a UWOC system for clear ocean water quality, which firstly proposes to use a double-exponential function to fit a channel impulse response curve under the clear ocean water quality and provides a simple method for solving each coefficient to be optimized of a fitting expression of the double-exponential function, namely, an effective thought for dividing the double-exponential function into a front weighting part and a rear weighting part and determining the initial value by obtaining the least square solution of two over-determined equation sets is proposed by using a key link of 'nonlinear least square curve fitting' function inherent in an Optimization tool box (Optimization toolbox) in Matlab software to obtain the final Optimization coefficient.

Description

Clear ocean water quality UWOC system channel impulse response fitting function solving method and system
Technical Field
The invention belongs to the technical field of Underwater Wireless Optical Communication (UWOC), and particularly relates to a method for solving a channel impulse response fitting function of a UWOC system for clear ocean water quality.
Background
In recent years, with the development of Wireless communication technology and the increasing depth of people's exploration for the ocean, Underwater Wireless Optical Communications (UWOC) is becoming a research hotspot. In order to transplant the terrestrial wireless optical communication technology to the marine underwater environment, modeling an underwater wireless optical communication channel model becomes work to be completed in the first step. The basic principle of Monte Carlo simulation is that the transmission process of light beams emitted by a light source in seawater is regarded as the process that a plurality of photons move forwards or backwards in the seawater along the transmission direction, and the photons collide with particles such as chlorophyll, mineral substances, plankton and the like in the seawater when being transmitted in the seawater, so that the scattering and absorption conditions of different degrees occur, and the receiver can obtain key channel characteristics such as channel impulse response, relative receiving power and the like by counting the number, loss, movement path and the like of the received photons.
At present, a Monte Carlo simulation method is used for researching channel impulse responses of the UWOC system under different ocean water qualities, but the channel impulse response curves are given in a specific data form, and obviously, the results in the form are not convenient for developing subsequent derivation and analysis of theoretical levels such as error rate analysis, channel capacity, system optimization and the like, so that a mathematical fitting method is necessary to give a closed expression of the channel impulse response curves under different water qualities according to data. According to our research, so far, no complete and universal closed form expression can accurately represent the channel impulse response curve of UWOC under various water qualities: in 2009, haipen Ding (Modeling of non-line-of-sight scaling channels for communication, IEEE j.on Selected Areas in comm., vol.27, No.9) proposed to use a single gamma function to fit a channel impulse response curve when non-line-of-sight ultraviolet light is transmitted in an atmospheric environment, but we transplanted this method to UWOC to fit a channel impulse response of coastal or port water quality, the fitting effect is not ideal, there is a large deviation, and clear ocean water quality cannot be simulated well. In 2011, Wei (Time domain dispersion of underserver optical wireless communication, chinese optics Letters, vol.9, No.3) proposed fitting an Inverse Gaussian (IG) function to the underwater optical channel impulse response waveform; however, the paper does not show the comparison between the theoretical shape of the channel impulse response and the monte carlo simulation or experimental test data, and according to our research, the channel impulse response effect of the IG function used for simulating three water qualities (clear sea, coast and harbor) of UWOC is still not ideal. Until 2014, Shijian Tang (impulse model for underserver water wireless communication links, ieee trans on Communications, vol.62, No.1) of the university of qing has proposed a method of fitting coast (coast water) and harbour (harbor water) water quality, i.e., the impulse response curve of the UWOC channel under a multi-scattering environment, using a double gamma function, and has obtained a good fitting effect. However, this method is not suitable for channel impulse response fitting in clear ocean water quality because the clear ocean water quality has relatively few impurities and small attenuation length or optical thickness τ, which results in that the channel impulse response does not have a pulse waveform with certain rising and falling sections like those of coast or harbor water quality, which means that a new fitting method is required to approximate the channel impulse response of clear ocean water quality.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a method for solving a channel impulse response fitting function of a UWOC system for clear ocean water quality, firstly proposes to use a double exponential function to fit a channel impulse response curve under the clear ocean water quality, and provides a simple method for solving each coefficient to be optimized of a fitting expression of the double exponential function, namely, provides an effective idea for dividing the double exponential function into a front weighting part and a rear weighting part and determining the initial value by obtaining the least square solution of two over-determined equation sets by using a key link of 'nonlinear least square curve fitting' function which is inherent in an Optimization toolbox (Optimization toolbox) in Matlab software to obtain the final Optimization coefficient.
The invention discloses a method for solving a clear ocean water UWOC system channel impulse response fitting function, which is characterized by comprising the following steps of:
obtaining channel impulse response h under clear ocean water qualitymc(t)；
Constructing a double-exponential function for fitting channel impulse response; wherein, the fitting coefficient to be determined is contained in the double-exponential function;
calculating fitting coefficient according to the exponential function weight, substituting the fitting coefficient into the dual exponential function to obtain a fitting function, and calculating channel impulse response and h fitted by the fitting functionmc(t) root mean square error, adjusting the exponential function weight, and repeating the steps until the exponential function weight reaches a threshold;
and taking the fitting function corresponding to the minimum root mean square error as the finally needed fitting function.
Further, the expression of the bi-exponential function is set as:
h(t)＝a·eb·△t+c·ed·△t
△t＝t-t0is the relative transit time of the photon, t is the absolute transit time of the photon, t0Is the transit time of the photon through the path, t0L/v, where L is the direct path distance from the transmitter to the receiver, and v is the transmission speed of light in seawater; a, b, c and d are four fitting coefficients to be determined, and e is a natural constant.
Further, the process of calculating the fitting coefficient is as follows: calculating an iteration initial value of the fitting coefficient according to a condition preset by the exponential function weight; and calling a nonlinear least square fitting function to calculate a final fitting coefficient based on the iteration initial value of the fitting coefficient.
Further, the iterative initial value formula for calculating the fitting coefficient is,
Figure BDA0002534052670000031
wherein the content of the first and second substances,
Figure BDA0002534052670000032
Figure BDA0002534052670000033
Figure BDA0002534052670000034
Figure BDA0002534052670000035
Figure BDA0002534052670000036
r is an n × 2 dimensional matrix, y1And y2Is an n × 1 dimensional vector.
Further, the clear ocean water UWOC system channel impulse response fitting function solving system comprises:
an impulse response acquisition module: obtaining channel impulse response h under clear ocean water qualitymc(t)；
A double-exponential function construction module: constructing a double-exponential function for fitting channel impulse response; wherein, the fitting coefficient to be determined is contained in the double-exponential function;
a fitting function obtaining module: calculating fitting coefficient according to the exponential function weight, substituting the fitting coefficient into the dual exponential function to obtain a fitting function, and calculating channel impulse response and h fitted by the fitting functionmc(t) root mean square error, adjusting the exponential function weight, and repeating the steps until the exponential function weight reaches a threshold;
a fitting module: and taking the fitting function corresponding to the minimum root mean square error as the finally needed fitting function.
Further, the expression of the double-exponential function constructed by the double-exponential function construction module is set as:
h(t)＝a·eb·△t+c·ed·△t
△t＝t-t0is the relative transit time of the photon, t is the absolute transit time of the photon, t0Is the transit time of the photon through the path, t0L/v, where L is the direct path distance from the transmitter to the receiver, and v is the transmission speed of light in seawater; a, b, c and d are four fitting coefficients to be determined, and e is a natural constant.
Further, the fitting function obtaining module further comprises a fitting coefficient calculating module;
the fitting coefficient calculation module comprises an initial value calculation module and a calling module;
an initial value calculation module: calculating an iteration initial value of the fitting coefficient according to a condition preset by the exponential function weight;
a calling module: and calling a nonlinear least square fitting function to calculate a final fitting coefficient based on the iteration initial value of the fitting coefficient.
Further, the initial value calculation module calculates the iterative initial value formula of the fitting coefficient as follows,
Figure BDA0002534052670000041
wherein the content of the first and second substances,
Figure BDA0002534052670000042
Figure BDA0002534052670000043
Figure BDA0002534052670000044
Figure BDA0002534052670000045
r is n × 2D matrix, a is 2 × 1D vector containing the initial value information of the coefficient, and y1And y2Is an n × 1 dimensional vector.
Further, a computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform any of the methods of claims 1-4.
Further, a computing device, comprising,
one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods of claims 1-4.
The invention has the following beneficial effects:
the method is characterized in that a simple method for fitting a channel impulse response curve under clear ocean water quality by using a double exponential function is firstly provided, and each coefficient to be optimized of a fitting expression of the double exponential function is solved, namely, a final Optimization coefficient is obtained by means of a 'nonlinear least square curve fitting' Lsqcurvefit function inherent in an Optimization tool box (Optimization toolbox) in Matlab software, and an effective thought for dividing the double exponential function into a front weighting part and a rear weighting part and determining the initial value by obtaining a least square solution of two over-determined equation sets is provided in a key link of calling an 'initial value' of the fitting coefficient required by the Lsqcurvefit function.
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FIG. 1 is a comparison of a double-exponential function fitting curve with a clear ocean original channel impulse response curve obtained by Monte Carlo simulation at a transmission distance of 10 m;
FIG. 2 is a comparison of a double exponential function fitting curve with a clear ocean original channel impulse response curve obtained by Monte Carlo simulation at a transmission distance of 20 m;
FIG. 3 is a comparison of a bi-exponential function fitting curve with a clear ocean original channel impulse response curve obtained by Monte Carlo simulation at a transmission distance of 50 m;
fig. 4 is a flow chart for implementing the method of fitting the clear ocean UWOC channel impulse response by using a double-exponential function.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in FIGS. 1-4, the present invention fits the channel impulse response curve of Monte Carlo UWOC clear ocean (clear ocean) water quality environment with a double-exponential function on the basis of the obtained channel impulse response simulation curve, and determines each fitting coefficient of the fitting expression through optimization calculation.
According to prior research efforts, in the UWOC system, the photon signal received by the receiver can be divided into a multiple-scattered part (via multiple scattering and absorption) and a non-multiple-scattered part (i.e., a low-order scattered and direct part). In clear ocean water, the received signal is dominated by the non-multiple-scattering fraction due to the presence of fewer impurities in the water; in contrast, the signals received in the more turbid coastal and harbor water qualities are dominated by the multiple scattering fractions. It is noted that even in clear ocean waters, which still contain large amounts of dissolved inorganic salts and minerals, visible light is transmitted in them with some degree of low-order small-angle forward scattering, not a complete hundred percent direct absorption. Based on this fact, if a single exponential function is only used to fit the monotonous decreasing curve of the clear ocean channel impulse response at different transmission distances obtained by the monte carlo simulation (see dotted lines in fig. 1 to 3), an ideal fitting effect cannot be obtained. The channel impulse response curve under the clear ocean water quality is fitted by using double exponential functions, namely, one exponential function is used for fitting a slow decay multi-scattering part, the other exponential function is used for fitting a fast decay low-order scattering part and a direct part, and the two parts are combined into a final simulation result through linear combination.
The expression of the double exponential function for fitting the clear ocean channel impulse response is set as:
h(t)＝a·eb·△t+c·ed·△t(1)
wherein △ t is t-t0Is the relative transit time of the photon, t is the absolute transit time of the photon, t0Is the transit time of the photon through the path, t0L/v, where L is the direct path distance from the transmitter to the receiver, and v is the transmission speed of light in seawater; a, b, c and d are four fitting coefficients to be determined, and e is a natural constant.
Solving the optimal values of the coefficients a, b, c and d of the double exponential function
Figure BDA0002534052670000061
Then, it can be determined with the least squares (least square) criterion, i.e. it is necessary to satisfy:
Figure BDA0002534052670000062
where h (t) is a target bi-exponential function, hmc(t) obtaining a known value of clear ocean water quality channel impulse response by utilizing Monte Carlo method simulation;
Figure BDA0002534052670000063
the operator of the parameter to be optimized when the target function described in the parenthesis is returned to take the minimum value can be calculated by directly calling the nonlinear least square fitting function Lsqcurvefit which is inherent in the Matlab software optimization tool box (the specific usage of the Lsqcurvefit can refer to the help document of the Matlab software). In the process of calling the nonlinear fitting function Lsqcurvefit, a very critical and core link is to determine the iteration initial values of four coefficients to be optimized of the bi-exponential function. Experimental simulation shows that: the more reasonable the initial value is set, the better the effect of the drawn fitting curve is; on the contrary, the fitting curve is far from the simulation experience data. Obviously, for different channel impulse response simulation results obtained by different UWOC communication environment settings (such as transmission distance, receiving field angle FOV, receiver coordinate offset, etc.), it is not reasonable nor possible to set iteration initial values by means of human heuristicsAnd (4) taking. It should be noted that, according to our investigation, no specific method for determining the fitting function coefficient is provided in the existing literature relating to terrestrial wireless optical communication or UWOC fitting channel impulse response, and almost all the clear colors are generally stated to be obtained by computer monte carlo simulation; clearly, this is not theoretical and it is difficult for the skilled person to reproduce their numerical results. In the invention, a simple and effective method is provided for solving the iteration initial value of the coefficient to be optimized of the double-exponential function.
The energy of the received signal of the UWOC can be divided into two parts of multiple scattering and non-multiple scattering, and the UWOC channel impulse response obtained in Monte Carlo simulation is obtained by counting the proportion of the energy of the received photon to the total energy of the emitted photon, and based on the above, when the iterative initial value of the four to-be-optimized coefficients of the expression is solved, the double-exponential function can be divided into two exponential functions to be solved respectively, namely, the double-exponential function is ordered to be solved
h(t)＝h1(t)+h2(t) (3)
In the formula, h1(t)＝a·eb·△t，h2(t)＝c·ed·△t. Setting a weight factor w, obviously, the value of the weight factor w should fall between 0 and 1, and h is provided1(t)＝w·h(t)，h2(t) — (1-w) h (t). In order to determine the best fitting effect, w can be gradually increased between 0 and 1 by a certain step length (such as 0.05), and h is respectively solved by adopting a least square method1(t) and h2(t) the initial value of the coefficient iteration corresponding to the (t) is substituted into the Lsqcurvefit function to perform curve fitting, and finally the best fitting effect (corresponding to h (t) and h) is selectedmcThe minimum root mean square error between (t) as the final result.
Solving the function h1The iterative initial values of the coefficients a and b of (t) are taken as an example to introduce the empirical data h of Monte Carlo simulation corresponding to h (t)mc(t) constructing an over-determined equation set to determine a process of a, b least squares solution. As known from the basic knowledge of linear algebra, when the number of equations is larger than the number of unknowns, the equation set at the moment is an overdetermined equation set which only hasA least squares solution. By a data function hmc(t) the overdetermined system of equations including undetermined coefficients a and b is:
Figure BDA0002534052670000071
in the above formula, n is hmc(t) the number of empirical data points, which generally satisfy n>>2, w ∈ (0,1) is variable channel impulse response weight coefficient.
Taking into account the channel impulse response hmc(t)>The nature of 0, which must be an exponential function, is taken to be the natural logarithm of each equation on both sides in equation (4), as follows:
Figure BDA0002534052670000072
let lna be a', the above-mentioned over-determined system of equations can be written in the form of a matrix-vector product as follows:
Figure BDA0002534052670000073
in the above formula, R is n × 2 dimensional matrix, wherein △ ti＝ti-t0The time axis variable corresponding to the Monte Carlo channel impulse response simulation value is substituted and calculated, a is 2 × 1 dimensional vector containing the initial value information of the coefficient, y1Is n × 1-dimensional vector, is obtained by substituting w and Monte Carlo channel impulse response value into calculation, has no loss of generality, R is column full rank matrix, and the least square solution of over-determined equation set (6) is known by matrix theory
Figure BDA0002534052670000074
In the formula, the upper label (·)TRepresenting a matrix transpose operation. Obviously, fit the iterative initial values a of the expression coefficients a and b0、b0Can be expressed as
Figure BDA0002534052670000081
The same can be derived from the function h2(t) the overdetermined system of equations including undetermined coefficients c and d is:
Figure BDA0002534052670000082
least squares solution thereof
Figure BDA0002534052670000083
In the formula, lnc ═ c'. Iterative initial value c of fitting expression coefficients c and d0、d0Is composed of
Figure BDA0002534052670000084
The initial iteration value of the coefficient to be optimized of the double-exponential function determined by the formulas (8) and (11) takes the influence of all Monte Carlo simulation experience values on the curve to be fitted into consideration, so that the initial iteration value is very suitable; however, the initial values of the weights w correspond to the initial values of the iterations, and the curve fitted by the weights w is not necessarily the curve which best matches the target simulation data. Therefore, iterative initial values corresponding to different energy weight w values are substituted into a nonlinear least square function Lsqcurvefit to carry out iterative fitting to obtain a convergence coefficient of a group of fitting curves, and a fitting curve h (t) formed by the coefficients and target simulation data h (t) are calculatedmcAnd (t) selecting a fitting curve corresponding to the w value with the minimum Root Mean Square Error (RMSE) to be the final fitting curve (according to our simulation, the w value corresponding to the minimum RMSE is not unique, and any one w value can be selected). This algorithmic solution flow to obtain the best fit function can be summarized as shown in table 1 below.
TABLE 1 clear ocean Water quality channel Impulse response double exponential fitting function solving step
Figure BDA0002534052670000085
Figure BDA0002534052670000091
Numerical simulation is carried out on the UWOC system photon transmission under clear ocean Water quality by utilizing a Monte Carlo simulation method, wherein a scattering phase function adopts Petzold classical experimental data (C.Mobley, Light and Water: Radiationtransfer in Natural Water.academic Press, Ch.3, 1994); the attenuation parameter values of the clear ocean seawater quality are shown in table 2, and the main parameters of Monte Carlo channel impulse response simulation are shown in table 3; assuming that the transmitting end and the receiving end are aligned, the transmission distances are set to 10m, 20m and 50m respectively for comparative analysis.
Fig. 1 to fig. 3 are comparison results between a fitting curve of a double exponential function and simulation empirical data of a monte carlo channel impulse response at transmission distances of 10m, 20m and 50m, respectively, wherein a blue point value represents a simulation value of the monte carlo, and a red solid line represents a curve of the double exponential function; the abscissa represents the relative transit time of a photon in nanoseconds (ns); the ordinate represents the normalized reception intensity, i.e. the ratio of the total photon weight received by the receiver to the total photon weight transmitted by the transmitter over the same time. By comparing and analyzing the data of fig. 1 to 3, it can be found that: as the transmission distance increases, the more times photons are scattered, the photon loss is easily smaller than the survival threshold, and the photons are easily lost beyond the aperture set by the receiver, so that the probability of being received is reduced, and the reception intensity is continuously reduced. At the same time, most of the photons already reach the receiving end within 0.5ns of absolute time. It can also be seen from the results of fig. 1 to 3 that fitting a simulated monte carlo value with a double exponential function works very well. In addition, table 4 shows the optimal fitting coefficients of the double-exponential function calculated by using the algorithm given in table 1 under different transmission distances; table 5 summarizes the root mean square error values RMSE between the monte carlo simulation results and the fitting values of the dual-exponential functions at different transmission distances, and it can be found that the RMSE values are all less than 5%, which again shows that the channel impulse response monte carlo simulation results under clear ocean water quality can be well fitted by using the dual-exponential functions.
TABLE 2 attenuation parameters of seawater quality
Figure BDA0002534052670000092
TABLE 3 Monte Carlo simulation of channel Impulse response parameters
Figure BDA0002534052670000093
Figure BDA0002534052670000101
TABLE 4 best fit coefficient of the dual exponential function
Figure BDA0002534052670000102
TABLE 5 root mean square error at different transmission distances
Figure BDA0002534052670000103
A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to execute a clear marine water quality UWOC system channel impulse response fitting function solving system.
A computing device comprising one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for executing a clear marine water quality UWOC system channel impulse response fitting function solving system.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.

Claims (10)

1. The method for solving the channel impulse response fitting function of the UWOC system for clear ocean water quality is characterized by comprising the following steps of:
obtaining channel impulse response h under clear ocean water qualitymc(t)；
Constructing a double-exponential function for fitting channel impulse response; wherein, the fitting coefficient to be determined is contained in the double-exponential function;
calculating fitting coefficient according to the exponential function weight, substituting the fitting coefficient into the dual exponential function to obtain a fitting function, and calculating channel impulse response and h fitted by the fitting functionmc(t) root mean square error, adjusting the exponential function weight, and repeating the steps until the exponential function weight reaches a threshold;
and taking the fitting function corresponding to the minimum root mean square error as the finally needed fitting function.
2. The method of claim 1, wherein the expression of the bi-exponential function is set as:
h(t)＝a·eb·△t+c·ed·△t
△t＝t-t0is the relative transit time of the photon, t is the absolute transit time of the photon, t0Is the transit time of the photon through the path, t0L/v, where L is the direct path distance from the transmitter to the receiver, and v is the transmission speed of light in seawater; a, b, c and d are four fitting coefficients to be determined, and e is a natural constant.
3. The method for solving the channel impulse response fitting function of the clear marine water UWOC system as claimed in claim 1, wherein the process for calculating the fitting coefficient is as follows: calculating an iteration initial value of the fitting coefficient according to a condition preset by the exponential function weight; and calling a nonlinear least square fitting function to calculate a final fitting coefficient based on the iteration initial value of the fitting coefficient.
4. The method of claim 3 for solving the channel impulse response fitting function of a clear marine water UWOC system, wherein the iterative initial value formula for calculating the fitting coefficient is,
Figure FDA0002534052660000011
wherein the content of the first and second substances,
Figure FDA0002534052660000012
Figure FDA0002534052660000013
Figure FDA0002534052660000021
Figure FDA0002534052660000022
Figure FDA0002534052660000023
r is an n × 2 dimensional matrix, y1And y2Is an n × 1 dimensional vector.
5. A clear ocean water quality UWOC system channel impulse response fitting function solving system is characterized by comprising the following steps:
an impulse response acquisition module: obtaining channel impulse response h under clear ocean water qualitymc(t)；
A double-exponential function construction module: constructing a double-exponential function for fitting channel impulse response; wherein, the fitting coefficient to be determined is contained in the double-exponential function;
fitting function acquisition module: calculating fitting coefficient according to the exponential function weight, substituting the fitting coefficient into the dual exponential function to obtain a fitting function, and calculating channel impulse response and h fitted by the fitting functionmc(t) root mean square error, adjusting the exponential function weight, and repeating the steps until the exponential function weight reaches a threshold;
a fitting module: and taking the fitting function corresponding to the minimum root mean square error as the finally needed fitting function.
6. The system for solving the channel impulse response fitting function of the clear marine water UWOC system as claimed in claim 5, wherein the expression of the double exponential function constructed by the double exponential function construction module is set as:
h(t)＝a·eb·△t+c·ed·△t
△t＝t-t0is the relative transit time of the photon, t is the absolute transit time of the photon, t0Is the transit time of the photon through the path, t0L/v, where L is the direct path distance from the transmitter to the receiver, and v is the transmission speed of light in seawater; a, b, c and d are four fitting coefficients to be determined, and e is a natural constant.
7. The system for solving the channel impulse response fitting function of the clear marine water UWOC system as claimed in claim 5, wherein the fitting function obtaining module further comprises a fitting coefficient calculating module;
the fitting coefficient calculation module comprises an initial value calculation module and a calling module;
an initial value calculation module: calculating an iteration initial value of the fitting coefficient according to a condition preset by the exponential function weight;
a calling module: and calling a nonlinear least square fitting function to calculate a final fitting coefficient based on the iteration initial value of the fitting coefficient.
8. The system of claim 7, wherein the initial value calculation module calculates an iterative initial value formula of the fitting coefficients as,
Figure FDA0002534052660000031
wherein the content of the first and second substances,
Figure FDA0002534052660000032
Figure FDA0002534052660000033
Figure FDA0002534052660000034
Figure FDA0002534052660000035
r is n × 2 dimensional matrix, y1And y2Is an n × 1 dimensional vector.
9. A computer readable storage medium storing one or more programs, characterized in that: the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods of claims 1-4.
10. A computing device, characterized by: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods of claims 1-4.
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