CN114779163B - Underwater sound detection, identification and obstacle avoidance method and system based on wave glider - Google Patents
Underwater sound detection, identification and obstacle avoidance method and system based on wave glider Download PDFInfo
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Abstract
The invention discloses an underwater sound detection, identification and obstacle avoidance method and system based on a wave glider, and relates to the technical field of sound wave measurement, wherein the method comprises the following steps: converting the acoustic signal detected by the hydrophone array into a digital quantity acoustic signal; preprocessing a digital quantity acoustic signal in a sliding window with a set window length to obtain spectral energy of a specific frequency band; calculating the probability that the spectrum energy is greater than a preset threshold value within set time; when the probability is greater than the preset probability, estimating the spectral energy greater than a preset threshold value by adopting a conventional beam forming algorithm to obtain the direction of the ship target; and adjusting the course of the wave glider according to the change of the spectrum energy in the direction, and avoiding obstacles on the ship target. The invention determines the orientation of the ship target existing in the wave glider by processing the acoustic signals received by the hydrophone array, and can avoid the obstacle of the ship target according to the energy change trend of the acoustic signals.
Description
Technical Field
The invention relates to the technical field of sound wave measurement, in particular to a method and a system for detecting, identifying and avoiding obstacles based on underwater sound of a wave glider.
Background
The wave glider utilizes wave energy to drive the platform, uses solar energy as power supply, has the advantages of small platform self-noise, long endurance time, controllable platform and the like, and is very suitable for carrying acoustic loads to perform tasks such as patrol observation in sea areas.
However, when the wave glider carries out a task of sea patrol observation, the wave glider is small in size and is not easy to be found by ships in the sea, so that the ships easily crash the wave glider in navigation, and the wave glider cannot complete the task of sea patrol observation.
Disclosure of Invention
The invention aims to provide a method and a system for detecting, identifying and avoiding obstacles based on underwater sound of a wave glider, which can avoid obstacles of a ship target.
In order to achieve the purpose, the invention provides the following scheme:
an underwater sound detection and identification obstacle avoidance method based on a wave glider, comprising the following steps:
converting the acoustic signal detected by the hydrophone array into a digital quantity acoustic signal;
preprocessing the digital quantity acoustic signal in a sliding window with a set window length to obtain the spectral energy of a specific frequency band;
calculating the probability that the spectrum energy is larger than a preset threshold value within a set time;
when the probability is greater than the preset probability, estimating the spectral energy greater than a preset threshold value by adopting a conventional beam forming algorithm to obtain the direction of the ship target;
and adjusting the course of the wave glider according to the change of the spectrum energy in the direction, and avoiding the obstacle of the ship target.
Optionally, the preprocessing the digital quantity acoustic signal in the sliding window with the set window length to obtain the spectral energy of the specific frequency band specifically includes:
performing Fourier transform on the digital quantity acoustic signal in a sliding window with a set window length to obtain an acoustic signal after Fourier transform;
taking an absolute value of the sound signal after Fourier transform to obtain full-band spectrum energy;
and filtering the full-frequency-band spectrum energy to obtain the specific-frequency-band spectrum energy.
Optionally, the calculating the probability that the spectrum energy is greater than the preset threshold within the set time specifically includes:
counting the times that the spectrum energy is larger than a preset threshold value within a set time and the total times of comparison between the spectrum energy and the preset threshold value;
and dividing the times of the spectrum energy being larger than a preset threshold value by the total times to obtain the probability of the spectrum energy being larger than the preset threshold value.
Optionally, the adjusting the heading of the wave glider according to the change of the spectral energy in the azimuth to avoid the obstacle of the ship target specifically includes:
judging whether the spectral energy in the direction becomes large or not;
when the spectrum energy in the direction is increased, the wave glider sails along a course vertical to the target course of the ship;
when the spectral energy of the azimuth is not increased, the wave glider sails along a preset course; the preset course is a preset sailing route of the wave glider.
Optionally, the method further comprises:
and sending the probability, the orientation of the ship target and the course of the wave glider to a shore base in real time.
A wave glider-based underwater sound detection, identification and obstacle avoidance system is applied to the wave glider-based underwater sound detection, identification and obstacle avoidance method, and comprises the following steps:
the conversion module is used for converting the acoustic signals detected by the hydrophone array into digital quantity acoustic signals;
the spectrum energy determining module is used for preprocessing the digital quantity acoustic signal in a sliding window with a set window length to obtain the spectrum energy of a specific frequency band;
the probability determination module is used for calculating the probability that the spectrum energy is larger than a preset threshold value within set time;
the azimuth determination module is used for estimating the spectral energy which is greater than a preset threshold value by adopting a conventional beam forming algorithm when the probability is greater than a preset probability to obtain the azimuth of the ship target;
and the course determining module is used for adjusting the course of the wave glider according to the change of the spectral energy in the direction and avoiding the obstacle of the ship target.
Optionally, the spectral energy determination module comprises:
the Fourier transform sub-module is used for carrying out Fourier transform on the digital quantity acoustic signal in a sliding window with a set window length to obtain an acoustic signal after Fourier transform;
the absolute value operation sub-module is used for taking an absolute value of the sound signal after Fourier transform to obtain full-band spectrum energy;
and the filtering submodule is used for filtering the full-frequency-band spectrum energy to obtain the specific frequency-band spectrum energy.
Optionally, the probability determination module comprises:
the counting submodule is used for counting the times that the spectrum energy is greater than a preset threshold value within set time and the total times of comparing the spectrum energy with the preset threshold value;
and the probability determination submodule is used for dividing the times of the spectrum energy being larger than a preset threshold value by the total times to obtain the probability of the spectrum energy being larger than the preset threshold value.
Optionally, the heading determination module includes:
the judgment submodule is used for judging whether the spectral energy in the direction is increased;
the course adjusting submodule is used for sailing the wave glider along a course vertical to the ship target course when the spectral energy of the azimuth is increased;
the course recovery submodule is used for sailing the wave glider along a preset course when the spectral energy of the azimuth is not increased; the preset course is a preset navigation route of the wave glider.
Optionally, the system further comprises:
and the sending module is used for sending the probability, the orientation of the ship target and the course of the wave glider to a shore base in real time.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a wave glider-based underwater sound detection, identification and obstacle avoidance method, which comprises the following steps: converting the acoustic signal detected by the hydrophone array into a digital quantity acoustic signal; preprocessing a digital quantity acoustic signal in a sliding window with a set window length to obtain spectral energy of a specific frequency band; calculating the probability that the spectrum energy is greater than a preset threshold value within set time; when the probability is greater than the preset probability, estimating the spectral energy greater than a preset threshold value by adopting a conventional beam forming algorithm to obtain the direction of the ship target; and adjusting the course of the wave glider according to the change of the spectrum energy in the direction, and avoiding obstacles on the ship target. The invention determines the orientation of the ship target in the wave glider by processing the acoustic signal received by the hydrophone array, and avoids the obstacle of the ship target according to the energy change trend of the acoustic signal, thereby improving the observation capability and the life cycle of the wave glider platform.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flow chart of an underwater acoustic detection, identification and obstacle avoidance method based on a wave glider, provided by the invention;
fig. 2 is a flow chart of the work of detecting underwater sound of a ship target provided by the invention;
FIG. 3 is a flow chart of a ship target detection algorithm of the present invention;
FIG. 4 is a flow chart of a platform obstacle avoidance algorithm based on target heading estimation according to the present invention;
fig. 5 is a block diagram of the underwater acoustic detection, identification and obstacle avoidance system based on the wave glider provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a method and a system for detecting, identifying and avoiding obstacles based on underwater sound of a wave glider, which can avoid obstacles of a ship target.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The underwater sound detection, identification and obstacle avoidance method based on the wave glider is based on power spectrum energy detection. The hydrophone array receives external sound signals, converts the sound signals into charge signals, further converts the charge signals into voltage signals through the signal conditioning circuit, and inputs the voltage signals into the ADC, and the ADC samples and quantizes the analog voltage signals; specifically, the signal conditioning circuit includes: the system comprises a program control gain amplification module, a program control filtering module, a power circuit module and other peripheral components. The signal conditioning steps are as follows: after the signals are input, input impedance matching is achieved through the voltage follower, then the signals are subjected to differential mode amplification through the low noise amplifier, and common mode noise in the signal transmission process is reduced as much as possible in the input signals. The signal after the differential mode amplification is subjected to fixed gain precision operational amplification, the signal is converted from double ends into a single end, and a fixed gain with a larger relative gain coefficient is realized. And a program-controlled attenuation module consisting of a DAC and a precise operational amplifier can perform adjustable attenuation on the signal with the fixed gain, so that the gain is adjusted. And finally, the input and output voltages are in the same phase, so that the program control gain module is completed, and high-precision signal conditioning is realized. And inputting the conditioned voltage signal into the ADC, wherein the sampling precision is 24bits at the moment, and the sampling frequency is 32 kHz.
As shown in fig. 1, the invention provides a wave glider-based underwater sound detection and identification obstacle avoidance method, which includes:
step S1: converting the acoustic signal detected by the hydrophone array into a digital quantity acoustic signal; specifically, the sampled and quantized acoustic data is in a big-end complement format, and the acoustic data is decoded to obtain a digital quantity acoustic signal.
In practical application, the hydrophone array is used for collecting acoustic signals of the current sea area. The hydrophone is a transducer which adopts piezoelectric ceramics as a transduction material and converts underwater acoustic signals into electric signals, and can output analog signals within +/-3V. Specifically, the original acoustic signals collected by the hydrophone array are subjected to real-time signal processing. The hydrophone array receives external acoustic signals including but not limited to ship target acoustic signals, marine environment background noise and marine organism noise.
Step S2: and preprocessing the digital quantity acoustic signal in a sliding window with a set window length to obtain the spectral energy of a specific frequency band.
S2 specifically includes:
step S21: performing Fourier transform on the digital quantity acoustic signal in a sliding window with a set window length to obtain an acoustic signal after Fourier transform; specifically, the preprocessed acoustic signal is subjected to short-time fourier transform using a sliding window of 2048-point size.
Step S22: and taking an absolute value of the sound signal after Fourier transform to obtain full-band spectral energy.
Step S23: and filtering the full-frequency-band spectrum energy to obtain the specific-frequency-band spectrum energy. Specifically, the spectral energy of a specific frequency band of 750 Hz-950 Hz is obtained by using band-pass filtering.
Step S3: and calculating the probability that the spectrum energy is larger than a preset threshold value within set time.
S3 specifically includes:
step S31: counting the times that the spectrum energy is larger than a preset threshold value within a set time and the total times of comparison between the spectrum energy and the preset threshold value; specifically, the spectral energy is compared with a preset threshold value, if the spectral energy is greater than the threshold value by 6dB, early warning is selected once, and if the spectral energy is not greater than the threshold value, energy detection is continued. And counting the early warning times within the set time to obtain the early warning probability.
As a specific embodiment, S31 specifically includes:
step S311: and judging whether the spectrum energy is larger than a preset threshold value or not.
Step S312: and when the spectrum energy is less than or equal to a preset threshold value, the total times are increased once.
Step S313: and when the spectrum energy is larger than a preset threshold value, increasing the frequency of the spectrum energy larger than the preset threshold value once, and increasing the total frequency once.
Step S32: and dividing the times of the spectrum energy being larger than a preset threshold value by the total times to obtain the probability of the spectrum energy being larger than the preset threshold value.
Specifically, the simplified passive sonar equation is expressed as:SL-NL>DT。
wherein,SLis the spectral energy of a specific frequency band (750-950 Hz),NLfor historical marine ambient background noise levels at the same frequency band resulting from historical data processing,DTthe minimum detection threshold is set to 6dB by the neman pearson criterion. If a ship target appears, the spectral energy in the frequency band can be increased rapidly, if the inequality is met, early warning is selected once, and if the inequality is not met, energy detection is continued. Because the abnormal condition may generate false alarm, the early warning times within 10 seconds are counted to obtain the early warning probability, and the early warning probability threshold is set as 80% without loss of generality. If the early warning probability within 10 seconds is greater than 80%, determining that ship targets exist in the surrounding sea area, and then adopting a platform obstacle avoidance scheme.
Step S4: when the probability is greater than the preset probability, estimating the spectral energy greater than a preset threshold value by adopting a conventional beam forming algorithm to obtain the direction of the ship target; specifically, if the early warning probability exceeds 80%, it is determined that ship targets exist in the surrounding sea area, and platform obstacle avoidance is performed based on an obstacle avoidance method of target course estimation. Furthermore, the obstacle avoidance method based on target course estimation estimates the target direction by using a direction estimation algorithm based on power spectrum energy detection, obtains the target course according to the energy change trend, and accordingly performs obstacle avoidance control on the wave glider.
And when a ship target is detected, performing conventional beam forming on acoustic signals acquired by the hydrophone array, and estimating the azimuth relationship between the target and the wave glider platform. Obtaining the target azimuth using the following equationθ * ：
θ * =argmax(w H (θ)E{x(t)x H (t)}w(θ))。
Has the meaning ofw H (θ)E{x(t)x H (t)}w(θ) Parameter corresponding to maximum timeθ * I.e. the desired target orientation. Whereinw(θ) In the form of an array manifold,w H (θ) In order to be a transpose of the same,x(t) For the acoustic signals received by the individual array elements,x H (t) Is a transpose thereof. The array manifold is determined by the array shape, and for an M-element uniform linear array, the array manifold is as follows:
w(θ)=[1,exp(jπsinθ),…,exp(jπ(M-1)sinθ)]。
here, a quaternary uniform linear array is used, and the array manifold is:
w(θ) * =[1,exp(jπsinθ),exp(j2πsinθ),exp(j3πsinθ)]。
step S5: and adjusting the course of the wave glider according to the change of the spectrum energy in the direction, and avoiding the obstacle of the ship target.
S5 specifically includes:
step S51: judging whether the spectral energy in the direction becomes large or not; specifically, whether the ship target is driving to the wave glider platform is judged by monitoring whether the signal energy on the azimuth is increased.
Step S52: when the spectral energy in the direction is increased, the wave glider sails along a course vertical to the ship target course; specifically, if the ship target drives towards the wave glider platform, an obstacle avoidance instruction is sent to the main control unit, and in consideration of actual conditions, the main control unit performs obstacle avoidance operation which is perpendicular to the course of the target and is far away from the sailing direction so as to avoid dangerous situations.
Step S53: when the spectral energy of the azimuth is not increased, the wave glider sails along a preset course; the preset course is a preset navigation route of the wave glider. Specifically, if the ship target is not heading toward the wave glider platform, the given course is maintained.
Furthermore, the method further comprises:
and sending the probability, the position of the ship target and the course of the wave glider to a shore base in real time. Specifically, if a ship target is detected, an obstacle avoidance instruction is sent to the master control system for obstacle avoidance operation, and meanwhile, the master control transmits the acquired obstacle avoidance instruction and the obstacle avoidance operation information back to the shore-based monitoring end through the satellite communication module.
As a specific implementation, as shown in fig. 2, the workflow of detecting the underwater sound of the ship target is as follows:
in the first step, a hydrophone array collects acoustic signals.
And secondly, applying a ship target detection algorithm.
And thirdly, judging whether the target is detected.
And fourthly, if the target is detected, executing the sixth step.
And step five, if the target is not detected, returning to the step one.
And sixthly, acquiring a target azimuth and returning the target azimuth through a satellite by applying a platform obstacle avoidance method based on target course estimation.
And seventhly, judging whether the energy on the direction is increased or not by applying a platform obstacle avoidance method based on target course estimation.
And step eight, if the azimuth energy is not increased, keeping the current heading, and returning to the step one.
And step nine, if the increase of the azimuth energy is detected, obstacle avoidance and navigation are carried out, and the satellite transmits back.
As a specific implementation, the ship target detection algorithm is shown in fig. 3, and specifically as follows:
first, data preprocessing is performed on original acoustic data.
And secondly, performing short-time Fourier transform on the preprocessed acoustic data.
And thirdly, filtering the acoustic data after short-time Fourier transform, and calculating spectral energy.
And fourthly, judging whether the spectrum energy is larger than a preset threshold value.
And fifthly, if the spectrum energy is larger than a preset threshold value, executing a seventh step.
And sixthly, if the spectrum energy is not larger than a preset threshold value, executing the first step.
And seventhly, sending out early warning.
And step eight, judging whether the early warning probability reaches a preset probability.
And ninthly, if the early warning probability reaches the preset probability, carrying out platform obstacle avoidance based on target course estimation.
And step ten, if the early warning probability does not reach the preset probability, executing the first step.
As a specific implementation manner, a flow chart of the platform obstacle avoidance algorithm based on target heading estimation of the present invention is shown in fig. 4, which is specifically as follows:
first, beamforming is applied to the raw acoustic data.
And secondly, estimating the orientation relation between the platform and the target according to the data obtained in the first step.
And thirdly, judging whether the energy in the direction is increased.
And fourthly, if the energy in the direction is increased, executing a sixth step.
And step five, if the energy in the direction is not increased, executing the step eight.
And sixthly, the master control platform avoids obstacles and walks.
And seventhly, returning the target information.
And eighthly, detecting the ship target.
And ninthly, judging whether the ship target is detected.
And tenth, if the ship target is detected, executing the first step.
And step eleven, if the ship target is not detected, executing the step eight.
The underwater sound detection, identification and obstacle avoidance method based on the wave glider provided by the invention is used for detecting a specific underwater sound target of a ship, guiding a platform to navigate and avoid obstacles according to a detection result, and improving the observation capability of the wave glider platform and the life cycle of equipment.
As shown in fig. 5, the underwater sound detection, identification and obstacle avoidance system based on the wave glider provided by the present invention is applied to the above-mentioned underwater sound detection, identification and obstacle avoidance method based on the wave glider, and the system includes:
the conversion module 1 is used for converting the acoustic signals detected by the hydrophone array into digital quantity acoustic signals.
And the spectral energy determining module 2 is used for preprocessing the digital quantity acoustic signal in a sliding window with a set window length to obtain the spectral energy of a specific frequency band.
And the probability determination module 3 is used for calculating the probability that the spectrum energy is greater than a preset threshold value within a set time.
And the direction determining module 4 is used for estimating the spectrum energy larger than the preset threshold value by adopting a conventional beam forming algorithm when the probability is larger than the preset probability to obtain the direction of the ship target.
And the course determining module 5 is used for adjusting the course of the wave glider according to the change of the spectral energy in the direction and avoiding the obstacle of the ship target.
Wherein the spectral energy determination module 2 comprises:
and the Fourier transform submodule is used for carrying out Fourier transform on the digital quantity acoustic signal in the sliding window with the set window length to obtain an acoustic signal after Fourier transform.
And the absolute value operation submodule is used for taking an absolute value of the sound signal after Fourier transform to obtain full-band spectrum energy.
And the filtering submodule is used for filtering the full-frequency-band spectrum energy to obtain the specific frequency-band spectrum energy.
Wherein the probability determination module 3 comprises:
and the counting submodule is used for counting the times that the spectrum energy is greater than a preset threshold value within set time and the total times of comparing the spectrum energy with the preset threshold value.
And the probability determination submodule is used for dividing the times of the spectrum energy being larger than a preset threshold value by the total times to obtain the probability of the spectrum energy being larger than the preset threshold value.
Wherein the heading determination module 5 comprises:
and the judgment submodule is used for judging whether the spectral energy in the direction is increased or not.
And the course adjusting submodule is used for sailing the wave glider along a course vertical to the ship target course when the spectral energy of the azimuth is increased.
The course recovery submodule is used for sailing the wave glider along a preset course when the spectral energy of the azimuth is not increased; the preset course is a preset sailing route of the wave glider.
Further, the system further comprises:
and the sending module is used for sending the probability, the orientation of the ship target and the course of the wave glider to a shore base in real time.
In long-term sea patrol observation, the wave glider can detect underwater targets by using underwater acoustic loads, and then returns results and guides the platform to avoid obstacles according to acoustic observation contents. The invention aims to realize the observation of the wave glider on the surrounding underwater acoustic environment, including the detection of specific underwater acoustic targets of ships, and guide the platform to navigate and avoid obstacles according to the detection result, thereby improving the observation capability of the wave glider platform and the life cycle of equipment. The underwater sound detection, identification and obstacle avoidance method and system based on the wave glider can also be expanded to other small-sized ocean mobile observation platforms similar to the wave glider detection principle.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. A wave glider-based underwater sound detection, identification and obstacle avoidance method is characterized by comprising the following steps:
converting the acoustic signal detected by the hydrophone array into a digital quantity acoustic signal;
preprocessing the digital quantity acoustic signal in a sliding window with a set window length to obtain the spectral energy of a specific frequency band;
calculating the probability that the spectrum energy is larger than a preset threshold value within a set time;
when the probability is greater than the preset probability, estimating the spectral energy greater than a preset threshold value by adopting a conventional beam forming algorithm to obtain the direction of the ship target;
adjusting the course of the wave glider according to the change of the spectrum energy in the direction, and avoiding the obstacle of the ship target;
according to the change of the spectrum energy in the position, the course of the wave glider is adjusted, and the ship target is kept away from the obstacle, and the method specifically comprises the following steps:
judging whether the spectral energy in the direction becomes large;
when the spectrum energy in the direction is increased, the wave glider sails along a course vertical to the target course of the ship;
when the spectral energy of the azimuth is not increased, the wave glider sails along a preset course; the preset course is a preset navigation route of the wave glider.
2. The method for detecting, identifying and avoiding obstacles based on the underwater sound of the wave glider as claimed in claim 1, wherein the pre-processing is performed on the digital quantity acoustic signal in the sliding window with a set window length to obtain the spectral energy of a specific frequency band, specifically comprising:
performing Fourier transform on the digital quantity acoustic signal in a sliding window with a set window length to obtain an acoustic signal after Fourier transform;
taking an absolute value of the sound signal after Fourier transform to obtain full-band spectrum energy;
and filtering the full-frequency-band spectrum energy to obtain the specific-frequency-band spectrum energy.
3. The method for detecting, identifying and avoiding obstacles based on the underwater sound of the wave glider as claimed in claim 1, wherein the calculating the probability that the spectral energy is greater than the preset threshold value within the set time specifically comprises:
counting the times that the spectrum energy is larger than a preset threshold value within a set time and the total times of comparison between the spectrum energy and the preset threshold value;
and dividing the times of the spectrum energy being larger than a preset threshold value by the total times to obtain the probability of the spectrum energy being larger than the preset threshold value.
4. The wave glider-based underwater acoustic detection and identification obstacle avoidance method according to claim 1, further comprising:
and sending the probability, the orientation of the ship target and the course of the wave glider to a shore base in real time.
5. The utility model provides an underwater acoustic detection discerns keeps away barrier system based on wave glider which characterized in that, the system includes:
the conversion module is used for converting the acoustic signals detected by the hydrophone array into digital quantity acoustic signals;
the spectrum energy determining module is used for preprocessing the digital quantity acoustic signal in a sliding window with a set window length to obtain the spectrum energy of a specific frequency band;
the probability determination module is used for calculating the probability that the spectrum energy is larger than a preset threshold value within set time;
the azimuth determination module is used for estimating the spectral energy which is greater than a preset threshold value by adopting a conventional beam forming algorithm when the probability is greater than a preset probability to obtain the azimuth of the ship target;
the course determining module is used for adjusting the course of the wave glider according to the change of the spectral energy in the direction and avoiding obstacles on the ship target;
the course determining module comprises:
the judging submodule is used for judging whether the spectral energy in the direction is increased;
the course adjusting submodule is used for sailing the wave glider along a course vertical to the ship target course when the spectral energy of the azimuth is increased;
the course recovery submodule is used for sailing the wave glider along a preset course when the spectral energy of the azimuth is not increased; the preset course is a preset sailing route of the wave glider.
6. The wave glider-based underwater acoustic detection identification obstacle avoidance system of claim 5, wherein the spectral energy determination module comprises:
the Fourier transform submodule is used for carrying out Fourier transform on the digital quantity acoustic signal in a sliding window with a set window length to obtain an acoustic signal after Fourier transform;
the absolute value operation submodule is used for taking an absolute value of the sound signal after Fourier transform to obtain full-band spectrum energy;
and the filtering submodule is used for filtering the full-frequency-band spectrum energy to obtain the specific frequency-band spectrum energy.
7. The wave glider-based underwater acoustic detection identification obstacle avoidance system of claim 5, wherein the probability determination module comprises:
the counting submodule is used for counting the times that the spectrum energy is larger than a preset threshold value within set time and the total times of comparing the spectrum energy with the preset threshold value;
and the probability determination submodule is used for dividing the times of the spectrum energy being larger than a preset threshold value by the total times to obtain the probability of the spectrum energy being larger than the preset threshold value.
8. The wave glider-based underwater acoustic detection, identification, and obstacle avoidance system of claim 5, further comprising:
and the sending module is used for sending the probability, the orientation of the ship target and the course of the wave glider to a shore base in real time.
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