A wave monitoring array radar based on artificial intelligence algorithm

Abstract

The invention discloses a wave monitoring array radar based on an artificial intelligence algorithm, belongs to the technical field of ocean monitoring, and comprises a wave monitoring radar system. The wave monitoring radar system is composed of a remote communication module, a remote data service computer and a radar unit, and the radar unit is composed of a first radar, a second radar and a third radar; the first radar, the second radar and the third radar all comprise a baseband frequency source, a frequency synthesis unit, a first up-conversion unit, a second up-conversion unit, two groups of bandpass filters, a transmitting antenna, a receiving antenna, a first down-conversion unit, a second down-conversion unit, a radar signal processing unit, a radar data processing unit, a power supply unit and a communication interface. The invention can complete sea surface monitoring in real time and effectively, has the advantages of high real-time performance, reliable monitoring results, unattended operation, low implementation cost and the like, and is of great significance to the construction of a new generation of ocean monitoring systems.

Description

Technical Field

[0001] The present invention relates to the field of ocean monitoring technology, and in particular to an ocean wave monitoring array radar based on an artificial intelligence algorithm. Background Art

[0002] Energy is an important material basis and an important constraint for the development of modern economic and social development. With the continuous development of economy and society, the demand for energy in human society will continue to grow. At present, the energy used by humans mainly comes from traditional energy. Traditional energy has certain service life restrictions, and the use of traditional energy will emit a large amount of greenhouse gases, leading to the greenhouse effect and destroying the ecological balance. The development and utilization of new energy sources are gradually gaining attention. As a clean energy, offshore wind power does not consume resources or produce emissions, and does not occupy a large amount of land resources, and is increasingly valued by people.

[0003] Offshore wind power is one of the important means of new energy. It has the advantages of stable wind energy resources and does not occupy land. my country's industrial chain must be developed in the direction of clean and green. Offshore wind power is an important direction for future development. The open sea is an important area for the development of offshore wind power in my country. Building wind power platforms in the open sea is of great significance to our future energy construction.

[0004] The safe operation of offshore wind power is the guarantee for the development of new energy. In order to ensure the safe operation of offshore wind power, an overall assessment is needed during the construction process. This requires the construction of wave characteristic data in the sea area, and the use of relevant professional software to achieve the operational safety assessment and construction index requirements of the offshore wind power platform, to ensure that the constructed offshore wind power platform can operate safely and reliably, reducing potential dangers and construction costs.

[0005] Waves are a very common and important physical phenomenon in the ocean. Understanding, studying and utilizing waves is an important step in human development of the ocean. Quantities used to describe wave characteristics, such as effective wave height, wave period, wavelength, direction, etc., are important design parameters used in offshore wind power survey and resource reassessment, operational safety, offshore operation safety, life extension design safety and power generation prediction.

[0006] The acquisition of ocean information relies on ocean monitoring. Most coastal countries and national ocean organizations have successively formulated new century ocean strategies and implementation plans. For their own and common interests, coastal countries are actively developing modern ocean monitoring technology to conduct three-dimensional monitoring of the ocean environment from the air, on the surface and underwater. There are many methods for wave monitoring, such as manual monitoring, satellite observation, buoy wave measurement, radar detection, etc. However, the cost of manual monitoring is high, and it is not easy to achieve real-time and continuous monitoring. When the wind and waves are strong, it may even affect the safety of personnel; satellite monitoring is more convenient, but the monitoring accuracy is not high; the buoy system has high accuracy, but it needs to be deployed in a certain sea area for a long time, the data cannot be returned in real time, and the cost of implementation is high; radar wave measurement has the advantages of high accuracy, simple installation, all-weather, maintenance-free, and no need for on-site calibration. It is suitable for use in all weather conditions and is widely used in offshore wind power.

[0007] To this end, we propose a wave monitoring array radar based on artificial intelligence algorithm. Summary of the invention

[0008] In view of the above-mentioned problems and / or the problems existing in the existing wave monitoring array radar based on artificial intelligence algorithm, the present invention is proposed.

[0009] Therefore, the purpose of the present invention is to provide a wave monitoring array radar based on artificial intelligence algorithm, which can solve the above-mentioned existing problems.

[0010] To solve the above technical problems, according to one aspect of the present invention, the present invention provides the following technical solutions:

[0011] A wave monitoring array radar based on an artificial intelligence algorithm, comprising a wave monitoring radar system, wherein the wave monitoring radar system is composed of a remote communication module, a remote data service computer and a radar unit, and the radar unit is composed of a first radar, a second radar and a third radar;

[0012] The radar unit is connected to the remote communication module, and the remote communication module is connected to the remote data service computer;

[0013] The first radar, the second radar and the third radar all include a baseband frequency source, a frequency synthesizer unit, a first up-conversion unit, a second up-conversion unit, two groups of bandpass filters, a transmitting antenna, a receiving antenna, a first down-conversion unit, a second down-conversion unit, a radar signal processing unit, a radar data processing unit, a power supply unit and a communication interface.

[0014] As a preferred solution of a wave monitoring array radar based on an artificial intelligence algorithm described in the present invention, wherein: the receiving antenna is connected to the second down-conversion unit through a bandpass filter, the second down-conversion unit is connected to the first down-conversion unit, the first down-conversion unit is connected to a radar signal processing unit, the radar signal processing unit is connected to a radar data processing unit, the radar data processing unit is connected to a communication interface, the communication interface is connected to a baseband frequency source, the baseband frequency source is respectively connected to the radar signal processing unit and the first up-conversion unit, the first up-conversion unit is connected to the second up-conversion unit, the second up-conversion unit is connected to a transmitting antenna through a bandpass filter, the first up-conversion unit is connected to the first down-conversion unit, the second up-conversion unit is connected to the second down-conversion unit, and a frequency synthesis unit is connected between the first up-conversion unit and the first down-conversion unit and between the second up-conversion unit and the second down-conversion unit.

[0015] As a preferred solution of the wave monitoring array radar based on artificial intelligence algorithm described in the present invention, it also includes an operation method, and the specific steps are as follows:

[0016] S1, the remote data service computer sends radar operating parameters, including center frequency, radar modulation period, signal bandwidth, output power, operating frequency and other parameters. The configuration parameters are sent to each sub-radar system through the remote data communication module;

[0017] S2, the baseband frequency source in each sub-radar system generates the corresponding baseband radar transmission signal according to the sent center frequency, radar modulation period, signal bandwidth, output power, working frequency and other parameters, and divides it into two paths, one is sent to the first frequency up-conversion unit, and the other is sent to the radar signal processing unit to provide a reference signal for the de-slope mixing process of the radar signal processing unit;

[0018] S3, the frequency synthesis unit generates a 12 GHz mixing reference frequency signal, which is sent to the first up-conversion unit, the second up-conversion unit, the first down-conversion unit, and the second down-conversion unit respectively;

[0019] S4, the first up-conversion unit mixes the baseband radar transmission signal and moves the center frequency of the radar baseband signal to 12 GHz;

[0020] S5, the second up-conversion unit performs mixing processing on the 12 GHz radar transmission signal after the first-stage mixing, shifts the radar transmission signal frequency to 24 GHz, and generates a millimeter-wave radar transmission signal;

[0021] S6, passing the generated signal through a 24 GHz bandpass filter to filter out out-of-band components, and sending the filtered millimeter wave transmission signal to the transmitting antenna;

[0022] S7, the transmitting antenna unit radiates the millimeter wave signal into space for sea surface detection;

[0023] S8, the ocean surface scatters the electromagnetic waves irradiated on its surface, which are received by the receiving antenna and enter the radar receiver;

[0024] S9, the received radar echo signal passes through a receiving end bandpass filter to filter out the out-of-band interference components;

[0025] S10, the millimeter wave radar echo signal passes through the first down-conversion unit and the second down-conversion unit, the echo signal spectrum is moved to the zero intermediate frequency, and sent to the radar signal processing unit;

[0026] S11, the radar signal processing unit performs a de-slope mixing process on the zero intermediate frequency radar signal, and after the radar signal processing is completed, outputs the corresponding echo one-dimensional range profile information;

[0027] S12, the radar data processing unit stores the one-dimensional range image information of the echo transmitted by the radar signal processing unit, realizes the two-dimensional distance of the one-dimensional range image of the echo signal through the radar data processing unit, and then extracts the distance information and speed information hidden in the one-dimensional range image of the echo through an intelligent algorithm;

[0028] S13, sending the distance information and speed information extracted by the radar data processing unit to the transmission input terminal of the remote communication module, and transmitting them to the local remote data service computer through the remote communication module;

[0029] S14, the local remote data service computer fuses the speed and distance information received from the three radar subsystems, extracts the real-time characteristic components of the sea surface, and stores the extracted components in the database system for users to call and view at any time.

[0030] As a preferred solution of the wave monitoring array radar based on artificial intelligence algorithm described in the present invention, wherein: in S12, the extraction of distance information and speed information is calculated by using a particle swarm algorithm, and by constructing a parameter-containing target model and performing optimal estimation calculation through a particle swarm optimization algorithm to extract the parameters in the objective function, namely, the distance and speed characteristics.

[0031] As a preferred solution of the wave monitoring array radar based on artificial intelligence algorithm described in the present invention, wherein: in S1, the center frequency is 24 GHz, the signal bandwidth is 1.5 GHz, the modulation period is 100 us, and the output power is 0.1 W.

[0032] As a preferred solution of the wave monitoring array radar based on artificial intelligence algorithm described in the present invention, wherein: in the S10, after the echo signal spectrum is moved to zero intermediate frequency, it is input into the A / D converter, the A / D uses 12 bits, and the signal processing module is a 32-bit floating-point DSP to complete the subsequent radar signal processing and data processing.

[0033] Compared with existing technologies:

[0034] 1. From the system design, optimization layout, distance feature and Doppler feature extraction, data anomaly processing and other conveniences, a large number of intelligent optimization algorithms are integrated, which greatly improves the system layout, data processing and other conveniences. In terms of optimization layout, random simulation technology is used instead of theoretical derivation method, which reduces the difficulty of implementation and obtains better optimization results; in terms of feature extraction, the traditional Fourier transform feature extraction method is abandoned, and the particle swarm algorithm is used to solve the optimal model, which greatly improves the measurement accuracy and stability of the data; in terms of outlier processing, fuzzy clustering method is used to eliminate abnormal information during the use of the equipment, effectively improving the data quality; through comparative analysis with the measured data of the wave cage, it can be seen that the equipment provided by the present invention can complete the sea surface monitoring in real time and effectively, and has the advantages of high real-time performance, reliable monitoring results, unmanned operation, low implementation cost, etc., which is of great significance to the construction of a new generation of ocean monitoring system;

[0035] 2. The present invention has simple layout, easy operation, complete and reliable equipment, and a friendly human-computer interaction interface. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a composition diagram of the ocean wave monitoring radar system of the present invention;

[0037] Figure 2 The radar composition and signal flow chart of the present invention;

[0038] Figure 3 The radar signal processing unit of the present invention is implemented as a schematic diagram;

[0039] Figure 4 The radar data processing unit of the present invention is implemented as a schematic diagram;

[0040] Figure 5 This is a schematic diagram of the distance and speed feature extraction implementation of the present invention;

[0041] Figure 6 This is a schematic diagram of the installation position of the device of the present invention;

[0042] Figure 7 This is a working situation diagram of the wave monitoring array radar of the present invention;

[0043] Fig. 8A and 8B The radar of the present invention transmits a frequency modulated continuous wave signal in the time domain and spectrum diagram;

[0044] Fig. 9 The transceiver antenna model and antenna pattern gain diagram of the present invention;

[0045] Fig. 10A and 10B It is the time domain waveform and spectrum diagram of the zero intermediate frequency echo signal of the present invention;

[0046] Fig.11 It is a one-dimensional range image characteristic diagram after removing the slope mixing of the present invention;

[0047] Fig.12 It is the distance velocity distribution diagram of the strong scattering point on the sea surface after the distance Doppler processing of the present invention;

[0048] Fig.13 This is the result of the process of extracting distance and speed features using the particle swarm algorithm in the present invention;

[0049] Fig.14A , 14B, 14C and 14D are comparative analysis diagrams of the wave monitoring array radar extracted data and the wave cage measured data of the present invention. DETAILED DESCRIPTION

[0050] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0051] See also Figure 1-Figure 7 , Fig. 8A , Figure 8B , Fig. 9 , Fig. 10A , Fig. 10B , Figure 11-13 , Fig.14A , Fig. 14B , Fig. 14C and Fig.14D The present invention provides a wave monitoring array radar based on artificial intelligence algorithm, and includes a wave monitoring radar system.

[0052] like Figure 1 As shown:

[0053] The wave monitoring radar system is composed of a remote communication module, a remote data service computer and a radar unit, and the radar unit is composed of a first radar, a second radar and a third radar. The radar unit is connected to the remote communication module, and the remote communication module is connected to the remote data service computer.

[0054] like Figure 2 As shown:

[0055] The first radar, the second radar and the third radar all include a baseband frequency source, a frequency synthesis unit, a first up-conversion unit, a second up-conversion unit, two sets of band-pass filters, a transmitting antenna, a receiving antenna, a first down-conversion unit, a second down-conversion unit, a radar signal processing unit, a radar data processing unit, a power supply unit and a communication interface. The receiving antenna is connected to the second down-conversion unit through a band-pass filter, the second down-conversion unit is connected to the first down-conversion unit, and the first down-conversion unit is connected to the radar signal processing unit. The radar signal processing unit mainly completes the de-slope mixing of the signal and obtains the one-dimensional range image of the echo signal. The radar signal processing unit is connected to the radar data processing unit, the radar data processing unit is connected to the communication interface, the communication interface is connected to the baseband frequency source, the baseband frequency source is respectively connected to the radar signal processing unit and the first up-conversion unit, the first up-conversion unit is connected to the second up-conversion unit, the second up-conversion unit is connected to the transmitting antenna through a band-pass filter, the first up-conversion unit is connected to the first down-conversion unit, the second up-conversion unit is connected to the second down-conversion unit, and a frequency synthesis unit is connected between the first up-conversion unit and the first down-conversion unit and between the second up-conversion unit and the second down-conversion unit.

[0056] Also included is an operation method, the specific steps are as follows:

[0057] S1, the remote data service computer sends radar operating parameters, including center frequency, radar modulation period, signal bandwidth, output power, operating frequency and other parameters. The configuration parameters are sent to each sub-radar system through the remote data communication module. Among them, the center frequency is 24GHz, the signal bandwidth is 1.5GHz, the modulation period is 100us, and the output power is 0.1W;

[0058] S2, the baseband frequency source in each sub-radar system generates the corresponding baseband radar transmission signal according to the sent center frequency, radar modulation period, signal bandwidth, output power, working frequency and other parameters, and divides it into two paths, one is sent to the first frequency up-conversion unit, and the other is sent to the radar signal processing unit to provide a reference signal for the de-slope mixing process of the radar signal processing unit;

[0059] S3, the frequency synthesis unit generates a 12 GHz mixing reference frequency signal, which is sent to the first up-conversion unit, the second up-conversion unit, the first down-conversion unit, and the second down-conversion unit respectively;

[0060] S4, the first up-conversion unit mixes the baseband radar transmission signal and moves the center frequency of the radar baseband signal to 12 GHz;

[0061] S5, the second up-conversion unit performs mixing processing on the 12 GHz radar transmission signal after the first-stage mixing, shifts the radar transmission signal frequency to 24 GHz, and generates a millimeter-wave radar transmission signal;

[0062] S6, passing the generated signal through a 24 GHz bandpass filter to filter out out-of-band components, and sending the filtered millimeter wave transmission signal to the transmitting antenna;

[0063] S7, the transmitting antenna unit radiates the millimeter wave signal into space for sea surface detection;

[0064] S8, the ocean surface scatters the electromagnetic waves irradiated on its surface, which are received by the receiving antenna and enter the radar receiver;

[0065] S9, the received radar echo signal passes through a receiving end bandpass filter to filter out the out-of-band interference components;

[0066] S10, the millimeter wave radar echo signal passes through the first down-conversion unit and the second down-conversion unit, and the echo signal spectrum is moved to zero intermediate frequency, and sent to the radar signal processing unit. After the echo signal spectrum is moved to zero intermediate frequency, it is input to the A / D converter. The A / D uses 12 bits, and the signal processing module is a 32-bit floating point DSP to complete the subsequent radar signal processing and data processing. The zero intermediate frequency signal is as follows Fig. 10A and 10B As shown;

[0067] S11, the radar signal processing unit performs a de-slope mixing process on the zero intermediate frequency radar signal (the principle is as follows Figure 3 As shown in Figure 2, after the radar signal processing is completed, the corresponding echo one-dimensional range image information is output (as shown in Figure 2). Fig.11 ),

[0068] S12, the radar data processing unit stores the echo one-dimensional range image information transmitted by the radar signal processing unit, and realizes the two-dimensional distance of the echo signal one-dimensional range image through the radar data processing unit, and then extracts the distance information and speed information hidden in the echo one-dimensional range image through an intelligent algorithm (the principle is the Doppler principle, and the principle is as follows Figure 4 As shown in the figure, the distance information and speed information are extracted by using the particle swarm algorithm. By constructing a parameter-containing target model, the particle swarm optimization algorithm is used to perform optimal estimation calculations and extract the parameters in the target function, namely the distance and speed characteristics (the principle is shown in the figure). Figure 5 As shown in Figure 2), it has much higher extraction accuracy and stability than the traditional FFT algorithm;

[0069] S13, sending the distance information and speed information extracted by the radar data processing unit to the transmission input terminal of the remote communication module, and transmitting them to the local remote data service computer through the remote communication module;

[0070] S14, the local remote data service computer fuses the speed and distance information received from the three radar subsystems, extracts the real-time characteristic components of the sea surface, and stores the extracted components in the database system for users to call and view at any time.

[0071] In specific use, when the radar is working, the three radars illuminate the water surface according to a specific angle setting and receive the water surface echo. Through the optimization structure simulation, it can be seen that for different measurement heights, the installation angle and installation spacing have a greater impact on the measurement accuracy. From the optimization calculation results, it can be seen that when the footprint formed by the three wave measuring radars is arranged in a right-angled triangle, the error obtained is the smallest. Therefore, in the present invention, the first radar, the second radar and the third radar are at the three vertices of an equilateral triangle, and the first radar and the third radar are at an angle of 15° with the horizontal plane to ensure the system's distance measurement and speed measurement requirements (such as Figure 6 as shown).

[0072] Comparative analysis (such as Fig.14A ,14B,14C,14D):

[0073] Through comparative analysis, it can be seen that the measurement results of the wave monitoring array radar based on the intelligent algorithm are basically equivalent to the high-cost wave cage test results, which can effectively solve the problems of high cost, high difficulty, poor real-time performance and high risk of wave monitoring.

[0074] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced by equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed in the present invention may be used in combination with each other in any manner, and the fact that these combinations are not exhaustively described in this specification is only for the sake of omitting space and saving resources. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. An operation method of a wave monitoring array radar based on an artificial intelligence algorithm, characterized in that: The array radar includes a sea wave monitoring radar system, which is composed of a remote communication module, a remote data service computer and a radar unit, and the radar unit is composed of a first radar, a second radar and a third radar; The radar unit is connected to the remote communication module, and the remote communication module is connected to the remote data service computer; The first radar, the second radar and the third radar each include a baseband frequency source, a frequency synthesis unit, a first up-conversion unit, a second up-conversion unit, two groups of bandpass filters, a transmitting antenna, a receiving antenna, a first down-conversion unit, a second down-conversion unit, a radar signal processing unit, a radar data processing unit, a power supply unit and a communication interface; The receiving antenna is connected to the second down-conversion unit through a band-pass filter, the second down-conversion unit is connected to the first down-conversion unit, the first down-conversion unit is connected to a radar signal processing unit, the radar signal processing unit is connected to a radar data processing unit, the radar data processing unit is connected to a communication interface, the communication interface is connected to a baseband frequency source, the baseband frequency source is connected to the radar signal processing unit and the first up-conversion unit respectively, the first up-conversion unit is connected to the second up-conversion unit, the second up-conversion unit is connected to a transmitting antenna through a band-pass filter, the first up-conversion unit is connected to the first down-conversion unit, the second up-conversion unit is connected to the second down-conversion unit, and a frequency synthesis unit is connected between the first up-conversion unit and the first down-conversion unit and between the second up-conversion unit and the second down-conversion unit; The specific steps of the operation method are as follows: S1, the remote data service computer sends radar operating parameters, including center frequency, radar modulation period, signal bandwidth, output power, and operating frequency parameters. The configuration parameters are sent to each sub-radar system through the remote data communication module; S2, the baseband frequency source in each sub-radar system generates the corresponding baseband radar transmission signal according to the issued center frequency, radar modulation period, signal bandwidth, output power, and operating frequency parameters, and divides it into two paths, one is sent to the up-conversion module 1, and the other is sent to the radar signal processing unit to provide a reference signal for the de-slope mixing process of the radar signal processing unit; S3, the frequency synthesis unit generates a 12 GHz mixing reference frequency signal, which is sent to the first up-conversion unit, the second up-conversion unit, the first down-conversion unit, and the second down-conversion unit respectively; S4, the first up-conversion unit mixes the baseband radar transmission signal and moves the center frequency of the radar baseband signal to 12 GHz; S5, the second up-conversion unit performs mixing processing on the 12 GHz radar transmission signal after the first-stage mixing, shifts the radar transmission signal frequency to 24 GHz, and generates a millimeter-wave radar transmission signal; S6, passing the generated signal through a 24 GHz bandpass filter to filter out out-of-band components, and sending the filtered millimeter wave transmission signal to the transmitting antenna; S7, the transmitting antenna unit radiates the millimeter wave signal into space for sea surface detection; S8, the ocean surface scatters the electromagnetic waves irradiated on its surface, which are received by the receiving antenna and enter the radar receiver; S9, the received radar echo signal passes through a receiving end bandpass filter to filter out the out-of-band interference components; S10, the millimeter wave radar echo signal passes through the first down-conversion unit and the second down-conversion unit, the echo signal spectrum is moved to the zero intermediate frequency, and sent to the radar signal processing unit; S11, the radar signal processing unit performs a de-slope mixing process on the zero intermediate frequency radar signal, and after the radar signal processing is completed, outputs the corresponding echo one-dimensional range profile information; S12, the radar data processing unit stores the one-dimensional range image information of the echo transmitted by the radar signal processing unit, realizes the two-dimensional distance of the one-dimensional range image of the echo signal through the radar data processing unit, and then extracts the distance information and speed information hidden in the one-dimensional range image of the echo through an intelligent algorithm; S13, sending the distance information and speed information extracted by the radar data processing unit to the transmission input terminal of the remote communication module, and transmitting them to the local remote data service computer through the remote communication module; S14, the local remote data service computer fuses the speed and distance information received from the three radar subsystems, extracts the real-time characteristic components of the sea surface, and stores the extracted components in the database system for users to call and view at any time.

2. The method for operating a wave monitoring array radar based on an artificial intelligence algorithm according to claim 1, characterized in that: In S12, the distance information and speed information are extracted by using a particle swarm algorithm. By constructing a parameter-containing target model and performing optimal estimation calculation using a particle swarm optimization algorithm, the parameters in the target function, namely, the distance and speed characteristics, are extracted.

3. The method for operating a wave monitoring array radar based on an artificial intelligence algorithm according to claim 2, characterized in that: In the S1, the center frequency is 24 GHz, the signal bandwidth is 1.5 GHz, the modulation period is 100 us, and the output power is 0.1 W.

4. The method for operating a wave monitoring array radar based on an artificial intelligence algorithm according to claim 2, characterized in that: In S10, after the echo signal spectrum is moved to zero intermediate frequency, it is input to the A / D converter. The A / D uses 12 bits, and the signal processing module is a 32-bit floating point DSP to complete the subsequent radar signal processing and data processing.

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