A self-powered wireless optical communication sensor positioning method and system for a marine ranch

Abstract

The application discloses a self-powered wireless optical communication sensor positioning method and system for a mariculture, and the method comprises the following steps: character coding is performed on each LED light source in the mariculture to generate a unique optical identification code; a dimming symbol is inserted into the optical identification code to adjust the light intensity of the LED light source; the code word after the dimming symbol is inserted is interleaved and coded to optimize the optical communication performance; the interleaved and coded signal is converted into multiple positioning carrier frequencies in a Manchester coding format, and a cell is formed; a photovoltaic device is used to convert the LED light signal into an electrical signal, the electrical signal is received, and light energy is collected; Fourier transform is performed on the received electrical signal, a frequency up-conversion signal of each frequency is obtained through a band-pass filter, and the optical identification code is decoded to locate the corresponding cell; a multi-order regression model is used to iteratively train the position in the cell, and the position coordinates of the underwater sensor are determined according to the high-precision model.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of underwater environment monitoring of marine ranching aquaculture, and particularly relates to a self-powered wireless optical communication sensor positioning method and system for a marine ranch. BACKGROUND

[0002] Modern marine ranching is a modern fishing complex integrating new technologies, new modes and new formats in the ocean, and is an important engine for promoting high-quality development of the ocean. Developing deep-sea aquaculture is an important way to build a "blue granary" and build a diversified food supply system. Modern marine ranching is changing from extensive to professional and intensive, and using LED aquaculture lamps can control the optimal growth environment for fish, increase efficiency and reduce costs, while providing a solution for sustainable development of the aquaculture industry. In the process of modernization of marine ranching, real-time monitoring of the underwater environment in aquaculture is needed, and various water quality monitoring sensors can be carried on underwater vehicles with LED aquaculture lamps. As a new positioning scheme, wireless optical positioning technology uses light as an information carrier and has the advantages of low carbon, high precision, and no electromagnetic interference. It is a very promising technical solution for underwater environment optical sensor network communication and optical positioning. Wireless optical positioning technology usually uses LED light sources as transmitters, which can be modulated by different coding schemes to achieve positioning functions while providing appropriate lighting. At the same time, solar photovoltaic devices can receive optical signals to collect optical energy, and have good directivity, which is very suitable for the field of underwater environment monitoring technology.

[0003] However, the LED aquaculture lamps used as light sources for optical sensor networks in the prior art have many advantages in terms of "light formula", lighting and optical communication technology, but their functions are relatively single. Specifically, the existing LED aquaculture lamps cannot simultaneously provide energy supply for marine ranching underwater environment monitoring sensor devices and achieve high-precision positioning of underwater vehicles. This limitation limits its application scenarios and makes it difficult to meet the needs of modern marine ranching for high efficiency, integration and sustainable development. SUMMARY

[0004] To solve the above technical problems, the present application provides a self-powered wireless optical communication sensor positioning method and system for a marine ranch to solve the problems existing in the prior art.

[0005] To achieve the above purpose, in a first aspect, the present application provides a self-powered wireless optical communication sensor positioning method for a marine ranch, comprising:

[0006] A plurality of LED light sources are arranged in the marine ranch, and the LED light sources serve as signal base stations to modulate their brightness output baseband signals;

[0007] character coding is performed on each LED light source to generate a unique optical identification code;

[0008] A dimming symbol is inserted into the optical identification code to adjust the light intensity of the LED light source until a suitable light intensity for mariculture is reached, and interleaved coding is performed on the code word after the dimming symbol is inserted to optimize the performance of optical communication;

[0009] The interleaved coded signal is converted into multiple positioning carrier frequencies in Manchester coding format and constitutes a cell;

[0010] The LED light source signal is converted into an electrical signal by a photovoltaic device, and the electrical signal includes a positioning carrier signal and light energy, and the light energy is collected to achieve self-power supply;

[0011] The positioning carrier signal is subjected to Fourier transform, the upconversion signal of each frequency is obtained by a band-pass filter, and the optical identification code is decoded to locate the corresponding cell;

[0012] A multi-order regression model is used to iteratively train the position in the cell to obtain a high-precision model, and the position coordinates of the underwater sensor are determined according to the high-precision model.

[0013] Preferably, generating a unique optical identification code comprises:

[0014] Character coding is performed on each LED light source;

[0015] The coded LED light source is arranged in a regular polygon;

[0016] Each character-coded LED light source is subjected to secondary coding using cross code to generate a unique optical identification code.

[0017] Preferably, the secondary coding using cross code is that each character is composed of multiple black or white bars, and the black and white bars are arranged alternately, with black bars at odd positions and white bars at even positions.

[0018] Preferably, adjusting the light intensity of the LED light source comprises:

[0019] If the inserted dimming symbol is 1, the light intensity of the LED light source is increased;

[0020] If the inserted dimming symbol is 0, the light intensity of the LED light source is decreased.

[0021] Preferably, collecting the light energy to achieve self-power supply comprises:

[0022] The LED light signal is converted into an electrical signal by a photovoltaic device;

[0023] connecting a positive electrode of the photovoltaic device to an input end of a receiving circuit, receiving the electrical signal through the receiving circuit, the electrical signal comprising optical energy and optical identification code information;

[0024] collecting the optical energy through an energy storage inductor, charging a lithium battery of the underwater sensor through a battery management system to realize self-power supply of the underwater sensor.

[0025] Preferably, decoding the optical identification code to locate the corresponding cell comprises:

[0026] performing Fourier transform on the positioning carrier signal to obtain frequency spectrum information, and determining the positioning carrier frequency corresponding to each vertex in the cell;

[0027] filtering the positioning carrier frequency through a band-pass filter;

[0028] determining the cell position of the underwater sensor according to the filtered positioning carrier frequency information and the decoded optical identification code.

[0029] Preferably, iteratively training the position in the cell by using a multi-order regression model comprises:

[0030] selecting a plurality of training positions in the cell, and measuring the optical signal amplitude and the visual distance of each position as training data;

[0031] calculating a weight vector by maximum likelihood and least squares method to generate a high-precision model;

[0032] predicting the position coordinates of the underwater sensor according to the high-precision model.

[0033] In a second aspect, the present application also discloses a self-powered wireless optical communication sensor positioning system for a marine ranching, comprising:

[0034] a light source setting module for setting a plurality of LED light sources in the marine ranching, the LED light sources serving as signal base stations and outputting baseband signals by modulating their brightness;

[0035] a light source encoding module for character encoding each LED light source to generate a unique optical identification code;

[0036] a light intensity adjusting module for inserting dimming symbols into the optical identification code to adjust the light intensity of the LED light source until reaching a light intensity suitable for aquaculture in the marine ranching, and interleaving the code word after the dimming symbols to optimize the optical communication performance;

[0037] a cell forming module for converting the interleaved signal into a plurality of positioning carrier frequencies in a Manchester coding format, and forming a cell;

[0038] A signal conversion module is configured to convert the LED light source signal into an electrical signal through a photovoltaic device, the electrical signal comprising a positioning carrier signal and light energy, and the light energy is collected to realize self-power supply.

[0039] A cell positioning module is configured to perform Fourier transform on the positioning carrier signal, obtain an up-converted signal of each frequency through a band-pass filter, and decode the optical identification code to position the corresponding cell.

[0040] A position prediction module is configured to iteratively train the position in the cell by using a multi-order regression model, obtain a high-precision model, and determine the position coordinates of the underwater sensor according to the high-precision model.

[0041] In a third aspect, the present application further discloses a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the steps of the method in the first aspect.

[0042] In a fourth aspect, the present application further discloses a computer program product, which comprises a computer program, and the computer program is executed by a processor to realize the steps of the method in the first aspect.

[0043] Compared with the prior art, the present application has the following advantages and technical effects:

[0044] The present application provides a self-powered wireless optical communication sensor positioning method for a mariculture, which first sets a plurality of LED light sources in the mariculture, the LED light sources serving as signal base stations and outputting baseband signals by modulating the luminance thereof; secondly, each LED light source is character-encoded to generate a unique optical identification code; thirdly, the optical identification code is inserted with dimming symbols to adjust the light intensity of the LED light source until reaching a light intensity suitable for aquaculture in the mariculture; the code word after the insertion of the dimming symbols is interleaved to optimize the optical communication performance; the interleaved signal is converted into a plurality of positioning carrier frequencies in a Manchester coding format and constitutes a cell; further, the LED light source signal is converted into an electrical signal through a photovoltaic device, the electrical signal comprising a positioning carrier signal and light energy, and the light energy is collected to realize self-power supply; again, the positioning carrier signal is subjected to Fourier transform, an up-converted signal of each frequency is obtained through a band-pass filter, and the optical identification code is decoded to position the corresponding cell; finally, a multi-order regression model is used to iteratively train the position in the cell, a high-precision model is obtained, and the position coordinates of the underwater sensor are determined according to the high-precision model.

[0045] The application uses high-power LED as a signal source, and cooperates with various water quality monitoring sensors carried by underwater vehicles to realize real-time detection of underwater environment. Although the LED aquaculture lamp has many advantages in terms of light formula, lighting and optical communication technology, its function is relatively single, and the replacement of the traditional underwater sensor network power supply system is expensive and impractical. Using photovoltaic devices as a photoelectric conversion module can complete optical communication while realizing energy collection, which is an important new technology for underwater exploration. Combined with high-precision positioning algorithms, high-precision real-time underwater environment measurement can be further realized, which provides a new technical means for the demand of modern marine ranching for high efficiency, integration and sustainable development. BRIEF DESCRIPTION OF DRAWINGS

[0046] The accompanying drawings, which form a part of this application, are included to provide a further understanding of the application and are incorporated in and constitute a part of this application. The embodiments of this application, and their description, are used to explain the application and are not intended to limit the application unduly.

[0047] Figure 1 The LED lamp of the embodiment of the application is arranged in a regular triangle;

[0048] Figure 2 The encoding mode of the LED of the embodiment of the application is cross-coded;

[0049] Figure 3 The LED light intensity is changed by inserting a dimming symbol;

[0050] Figure 4 The energy is collected by using the energy storage inductor L of the embodiment of the application;

[0051] Figure 5 The unit cell of the embodiment of the application is shown in the figure;

[0052] Figure 6 The training data of the embodiment of the application is shown in the figure;

[0053] Figure 7 The principle block diagram of the embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0054] It should be noted that the embodiments and features in the embodiments of the application can be combined with each other without conflict. The application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0055] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in a different order.

[0056] Embodiment one

[0057] As Figure 7 shown, the embodiment provides a self-powered wireless optical communication sensor positioning method for mariculture, comprising:

[0058] S1, a plurality of LED light sources are arranged in the mariculture, the LED light sources are used as signal base stations, and a baseband signal is output by modulating the brightness of the LED light sources;

[0059] Specifically, 15 LED light sources with a power of 200W are used as mariculture aquaculture lights and are placed in water with a depth of 10m from the water surface. The LED light sources are used as signal base stations, and an On-Off Keying (OOK) modulation is used at the sending end to complete the baseband signal output. The LED light being on represents binary data "1", and the LED light being off represents binary data "0". The minimum period of switching change is set to 10us (half period 25us, i.e. the upper limit of the change frequency is 100kHz), and the maximum period is set to 100us (half period 50us, i.e. the lower limit of the change frequency is 10kHz), which can realize the LED aquaculture lighting function and prevent the LED from flickering.

[0060] S2, each LED light source is character encoded to generate a unique optical identification code;

[0061] Further, as an innovative implementation, each LED in the embodiment is character encoded, and the encoded LED lights are arranged in a regular triangle. Each character-encoded LED is cross-encoded for secondary encoding, and each LED light obtains a unique OID code.

[0062] Specifically, the following steps are included:

[0063] S21, each LED is character encoded, and the encoding information is shown in Table 1. The encoded LED lights are arranged in a regular triangle, and the arrangement method is shown in Figure 1 ;

[0064] Table 1

[0065] LED lamp Character LED lamp Character LED lamp Character LED1 0123 LED 6 0321 LED 11 ]] 1302 LED2 0132 LED 7 1023 LED 12 ]] 1320 LED3 0213 LED 8 1032 LED 13 ]] 2103 LED4 0231 LED 9 1203 LED 14 ]] 2130 LED5 0312 LED 10 ]] 1230 LED 15 ]] 2310

[0066] S22, each character-encoded LED is cross-encoded for secondary encoding, and the encoding method is shown in Figure 2As shown, each character is composed of 5 black or white bars, of which 2 are wide bars (represented by binary "1") and 3 are narrow bars (represented by binary "0"). The black and white bars are interleaved, and the black bars are placed at odd positions and the white bars are placed at even positions. The binary representation of each character is shown in Table 2. Each LED lamp has a unique OID after cross-encoding of the four-bit character. The OID corresponding to each LED lamp is shown in Table 3. Because the bright and dark stripes are interleaved after cross-encoding, the LED lamp rapidly alternates "on / off" without a continuous 1 or 0, and because the proportion of the duration of the "on / off" symbol is constant, the average brightness of the LED remains stable, and the brightness is stable during the LED baseband signal transmission and no flickering occurs.

[0067] Table 2

[0068] Character Binary Character Binary 0 00110 2 01001 1 10001 3 11000

[0069] Table 3

[0070] LED lamp Character OID LED1 0123 10000101101011000001 LED2 0132 10000101100111000010 LED3 0213 00100101101110000001 LED4 0231 00100101101101000010 LED5 0312 10100101000110111111 LED 6 0321 10100101001001000011 LED 7 1023 10000101101011000001 LED8 1032 10000101100111000010 LED 9 1203 01100000111010010100 LED 10 ]] 1230 01100000110101101000 LED 11 ]] 1302 11100000010010010110 LED 12 ]] 1320 11100000010001101001 LED 13 ]] 2103 10010000111010010100 LED 14 ]] 2130 10010000110101101000 LED 15 ]] 2310 10110000010101101000

[0071] S3, inserting dimming symbols into the optical recognition code to adjust the light intensity of the LED light source until reaching a light intensity suitable for mariculture aquaculture; and interleaving and encoding the code word after inserting the dimming symbols to optimize the performance of the optical communication.

[0072] As an innovative implementation, the step specifically includes:

[0073] S31, inserting a dimming symbol into each LED lamp, inserting all "1" to increase the light intensity, and inserting all "0" to reduce the light intensity, until the light intensity of the LED is adjusted to a light intensity suitable for the light formula of mariculture aquaculture, and the dimming symbol is as shown in Figure 3

[0074] S32, interleaving and encoding the code word after adjusting the light intensity by inserting the dimming symbol, and a large number of "1"s and "0"s will appear in the code word after inserting the dimming symbol, and interleaving and encoding can further suppress the flickering of the LED lamp.

[0075] S4, converting the signal after interleaving and encoding into a plurality of positioning carrier frequencies in a Manchester encoding format, and forming a cell;

[0076] Further, as an innovative implementation, the code after interleaving and encoding is converted into 3 different specific positioning carrier frequencies in a Manchester encoding format by frequency up-conversion, and the 3 specific frequencies form a specific cell.

[0077] Specifically includes the following steps:

[0078] ​S41, the encoding period after interleaving encoding is set to T0=1ms, and the frequency f0=1kHz. In the Manchester encoding format, frequency up-conversion is used to convert into three different specific carrier frequencies f1=10kHz, f2=20kHz, and f3=30kHz;

[0079] S42, the three different specific carrier frequencies f1=10kHz, f2=20kHz, and f3=30kHz form a specific cell, and after arrangement, each cell has three frequencies, and the frequency corresponding to each LED lamp is shown in Table 4;

[0080] Table 4

[0081] LED lamp Frequency Frequency value LED1 f1 10 kHz LED2 f2 20 kHz LED3 f3 30 kHz LED4 f3 30 kHz LED5 f1 10 kHz LED 6 f2 20 kHz LED 7 f2 20 kHz LED8 f3 30 kHz LED 9 f1 10 kHz LED 10 ]] f1 10 kHz LED 11 ]] f2 20 kHz LED 12 ]] f3 30 kHz LED 13 ]] f3 30 kHz LED 14 ]] f1 10 kHz LED 15 ]] f2 20 kHz

[0082] S5, converting the LED light source signal into an electrical signal through a photovoltaic device, the electrical signal including a positioning carrier signal and light energy, and collecting the light energy to achieve self-power supply;

[0083] Further, as an innovative implementation, in the receiving end, the underwater sensor completes photoelectric conversion through a photovoltaic device, synchronously completes reception of the positioning carrier signal and collection of light energy, charges the lithium battery through a battery management system using the collected light energy, and supplies power to the microcontroller of the underwater optical communication sensor network using the lithium battery, thereby achieving self-power supply.

[0084] Specifically, the method includes the following steps:

[0085] S51, the anode of the solar cell panel is connected to the input end of the receiving circuit, and the solar photovoltaic device converts the optical signal into an electrical signal, which can directly enter the receiver circuit;

[0086] S52, the received electrical signal contains energy P w and OID encoding information, wherein P w is used for energy collection, and the OID encoding information is used to confirm the corresponding LED lamp;

[0087] S53, the energy collection part, as shown in Figure 4 , uses an energy storage inductor L to complete energy collection, and then enters the BMS, and the BMS system charges the lithium battery of the underwater vehicle, thereby achieving energy collection of the underwater sensor.

[0088] S6, Fourier transforming the positioning carrier signal, obtaining an up-converted signal of each frequency through a band-pass filter, and decoding the optical recognition code to locate the corresponding cell;

[0089] Further, as an innovative implementation, the embodiment performs fast Fourier transform on the received three different positioning carrier frequencies to obtain the corresponding spectrum information, and then obtains the up-converted signal of each frequency through a band-pass filter, and the specific description of positioning to the corresponding unit cell through decoding OID is as follows:

[0090] S61, receiving three different positioning carrier frequencies f1, f2, f3 with OID through photovoltaic devices photoelectric conversion, performing fast Fourier transform on the carrier signal to obtain the corresponding spectrum According to the spectrum information, the positioning carrier frequencies corresponding to each triangular vertex in the unit cell can be obtained;

[0091] S62, using a band-pass filter (frequency range 9.5kHz-10.5kHz), (frequency range 19.5kHz-20.5kHz), (frequency range 29.5kHz-30.5kHz) respectively filter the positioning carrier f1, f2, f3 to prevent high-frequency crosstalk;

[0092] S63, as Figure 5 shown, according to the positioning carrier frequencies corresponding to each triangular vertex in the unit cell and decoding OID, the corresponding unit cell can be determined.

[0093] S7, using a multi-order regression model to iteratively train the position in the unit cell to obtain a high-precision model, and determining the position coordinates of the underwater sensor according to the high-precision model.

[0094] Further, as an innovative implementation, the embodiment uses a multi-order regression model to iteratively train the position in the unit cell to obtain a high-precision model, and according to the high-precision regression model, a high-precision coordinate (x, y, z) can be obtained;

[0095] In the embodiment, the multi-order regression model uses a third-order regression model;

[0096] Specifically, the following steps are included:

[0097] S71, using a third-order regression model to iteratively train the position in the unit cell, as formula (1):

[0098]

[0099] Where W is the weight, Ф and ⊙ are the amplitude and target vector respectively, and D is the dimension. Here, the positioning information is based on the FFT amplitude of the light signal received from three LEDs, and D=3;

[0100] Equation (1) can be separated into x and y coordinates as shown in Equation (2):

[0101]

[0102] The amplitude Φ in Equation (1) is shown in Equation (3):

[0103]

[0104] where N is the number of training data. Within one cell, we choose 120 training positions (with x and y coordinates) and measure 30 times at each training position during training. Thus, we have N = 120 x 30 = 3600 in the experiment. The elements in the signal amplitude vector Φ include q1, q2, and q3, which represent the received light signal FFT amplitudes of the up-converted signals at 10 kHz, 20 kHz, and 30 kHz, respectively. The positions of the 120 training points are denoted by x and y coordinates. They are recorded during the training process and represented by the target vector as shown in Equation (4):

[0105]

[0106] S72, the weight vector W is obtained using the maximum likelihood and least squares method, and the likelihood function is represented by Equation (5),

[0107]

[0108] where β is the precision (inverse of variance) of the data distribution. To calculate the maximum likelihood with respect to W, the gradient of the log-likelihood function in Equation (5) is set to zero, which is shown in Equation (6):

[0109]

[0110] The solved W is:

[0111] W = (Φ T Φ) -1 Φ T θ (7)

[0112] In the polynomial right triangle model, the received light signal of each LED is measured separately. As shown in Figure 6 , during the training process of LED1, the receiver is gradually moved horizontally away from LED1, and then the received light signal amplitude p and the line-of-sight (LOS) distance d are recorded as training data. Once W is calculated by substituting the amplitude vector Φ and the target vector obtained during the training process, the multi-order regression model shown in Equation (1) can be used according to Figure 5As shown, the position (x, y, z) of the receiver is predicted according to the newly received light signal amplitudes p1, p2 and p3. The position coordinate equation is:

[0113]

[0114] where (x1, y1, z1), (x2, y2, z2), (x3, y3, z3) are the coordinates of the vertices of the unit cell directly below LED1, LED2 and LED3, respectively.

[0115] The embodiment studies and researches the wireless optical communication sensor positioning system in the mariculture, and proposes a self-powered wireless optical communication sensor positioning method for the mariculture. First, the brightness of a high-power LED is modulated and the brightness change period is set. Then, each LED lamp is character-coded at the LED transmitting end, and the character coding is encoded again by using a cross code to determine the unique OID of each LED. After the OID is confirmed, the dimming symbol is inserted and interleaved coding is performed. The light intensity of the LED is adjusted to the light intensity suitable for the light formula of the mariculture aquaculture. After interleaved coding, the Manchester coding format is used, and the frequency up-conversion mode is used to convert into three different specific positioning carrier frequencies. The three specific frequencies constitute a specific unit cell. At the receiving end, the received three different positioning carrier frequencies are subjected to fast Fourier transform to obtain the corresponding frequency spectrum information. Then, the up-conversion signal of each frequency is obtained through a band-pass filter, and the corresponding unit cell is located by decoding the OID. The underwater sensor completes photoelectric conversion through a photovoltaic device, simultaneously receives the positioning carrier signal and collects light energy. In order to further improve the positioning accuracy, a multi-order regression model is used to iteratively train the position in the unit cell, obtain a high-precision model, and further determine the position of the underwater sensor in the mariculture aquaculture. At the same time, the photovoltaic device extracts the light energy, charges the super capacitor through the battery management system, and supplies power to the micro control unit of the underwater sensor network by using the energy storage unit. Thus, under the condition of suitable light formula illumination, the solar photovoltaic device is used as a receiver to realize high-precision positioning of the self-powered wireless optical communication sensor in the mariculture.

[0116] The embodiment provides lighting, light positioning, underwater environment monitoring, self-power supply and other technologies in the field of mariculture application, and has broad market and positive social benefits.

[0117] Embodiment two

[0118] Based on the same inventive concept, the embodiment also provides a self-powered wireless optical communication sensor positioning system for the mariculture, which comprises:

[0119] The light source setting module is configured to set a plurality of LED light sources in the marine ranching as signal base stations, and output baseband signals by modulating the luminance of the LED light sources.

[0120] The light source encoding module is configured to encode each LED light source as a character to generate a unique optical identification code.

[0121] The light intensity adjusting module is configured to insert a dimming symbol into the optical identification code to adjust the light intensity of the LED light source until the light intensity suitable for the marine ranching aquaculture is reached, and to interleave the code word after the dimming symbol is inserted to optimize the light communication performance.

[0122] The cell forming module is configured to convert the interleaved signal into a plurality of positioning carrier frequencies in a Manchester coding format, and form a cell.

[0123] The signal conversion module is configured to convert the LED light signal into an electrical signal by a photovoltaic device, receive the electrical signal, and collect light energy.

[0124] The cell positioning module is configured to perform Fourier transform on the received electrical signal, obtain an up-converted signal of each frequency by a band-pass filter, and decode the optical identification code to position the corresponding cell.

[0125] The position prediction module is configured to use a multi-order regression model to iteratively train the position in the cell, obtain a high-precision model, and determine the position coordinates of the underwater sensor according to the high-precision model.

[0126] The self-powered wireless optical communication sensor positioning system for the marine ranching provided in the embodiment has all the advantages of the self-powered wireless optical communication sensor positioning method for the marine ranching provided in the embodiment one.

[0127] Embodiment three

[0128] The embodiment also discloses a computer-readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the steps of the method in the embodiment one.

[0129] Embodiment four

[0130] The embodiment also discloses a computer program product, which includes a computer program. The computer program is executed by a processor to implement the steps of the method in the embodiment one.

[0131] The above merely provides the preferred embodiments of the present application, and the protection scope of the present application is not limited thereto, and any changes or substitutions within the technical scope disclosed by the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A self-powered wireless optical communication sensor positioning method for a marine ranching, characterized by, The method comprises the following steps: a plurality of LED light sources are arranged in the marine ranching as signal base stations, and a baseband signal is modulated by adjusting the brightness of the LED light sources; each LED light source is character coded to generate a unique optical identification code; a dimming symbol is inserted into the optical identification code to adjust the light intensity of the LED light source until the light intensity suitable for the marine ranching aquaculture is reached; and the code word after the dimming symbol is inserted is interleaved to optimize the light communication performance; the interleaved signal is converted into a plurality of positioning carrier frequencies in a Manchester coding format, and a cell is formed; the LED light source signal is converted into an electrical signal by a photovoltaic device, the electrical signal comprising a positioning carrier signal and light energy, and the light energy is collected to realize self-power supply; the positioning carrier signal is subjected to Fourier transform, an upconversion signal of each frequency is obtained by a band-pass filter, and the optical identification code is decoded to locate the corresponding cell; a multi-order regression model is used to iteratively train the position in the cell, an iteratively trained multi-order regression model is obtained, and the position coordinates of the underwater sensor are determined according to the iteratively trained multi-order regression model.

2. The method of claim 1, wherein generating a unique optical identification code comprises: character coding each LED light source; arranging the coded LED light sources in a regular polygon; secondary coding each character coded LED light source using cross code to generate a unique optical identification code.

3. The method of claim 2, wherein the secondary coding using cross code is that each character is composed of a plurality of black or white bars, the black and white bars are arranged alternately, the black bars are arranged at odd positions, and the white bars are arranged at even positions.

4. The method of claim 1, wherein adjusting the light intensity of the LED light source comprises: if the inserted dimming symbol is 1, the light intensity of the LED light source is enhanced; if the inserted dimming symbol is 0, the light intensity of the LED light source is reduced.

5. The method of claim 1, wherein collecting the light energy to realize self-power supply comprises: converting the LED light signal into an electrical signal by a photovoltaic device; connecting the anode of the photovoltaic device to the input end of a receiving circuit, receiving the electrical signal by the receiving circuit, the electrical signal comprising light energy and optical identification code information; collecting the light energy by an energy storage inductor, charging the lithium battery of the underwater sensor by a battery management system to realize self-power supply of the underwater sensor.

6. The method of claim 1, wherein decoding the optical identification code to locate the corresponding cell comprises: Fourier transforming the positioning carrier signal to obtain frequency spectrum information and determine the positioning carrier frequencies corresponding to each vertex in the cell; filtering the positioning carrier frequencies by a band-pass filter; determining the cell position of the underwater sensor according to the filtered positioning carrier frequency information and the decoded optical identification code.

7. The method of claim 1, wherein iteratively training the position in the cell using a multi-order regression model comprises: Selecting multiple training positions in the cell, measuring the light signal amplitude and visual distance of each position as training data; Calculating the weight vector by maximum likelihood and least squares method, generating the multi-order regression model after iterative training; According to the multi-order regression model after iterative training, the position coordinates of the underwater sensor are predicted.

8. A self-powered wireless optical communication sensor positioning system for a marine ranching, characterized by, Comprise: The light source setting module is used for setting a plurality of LED light sources in the mariculture, and the LED light sources are used as signal base stations to output baseband signals by modulating the luminance; The light source coding module is used for character coding each LED light source to generate a unique optical identification code; The light intensity adjustment module is used for inserting dimming symbols into the optical identification code to adjust the light intensity of the LED light source until the light intensity suitable for mariculture aquaculture is reached; and the code word after inserting the dimming symbols is interleaved and coded to optimize the light communication performance; The cell forming module is used for converting the interleaved and coded signal into a plurality of positioning carrier frequencies in the Manchester coding format, and forming a cell; The signal conversion module is used for converting the LED light source signal into an electrical signal through a photovoltaic device, and the electrical signal includes a positioning carrier signal and light energy, and the light energy is collected to realize self-power supply; The cell positioning module is used for performing Fourier transform on the positioning carrier signal, obtaining an upconversion signal of each frequency through a band-pass filter, and decoding the optical identification code to locate the corresponding cell; The position prediction module is used for adopting a multi-order regression model to iteratively train the positions in the cell, obtaining a multi-order regression model after iterative training, and determining the position coordinates of the underwater sensor according to the multi-order regression model after iterative training.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the method of any one of claims 1-7.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the method of any one of claims 1-7.

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