CN115903006B - A ship underwater acoustic monitoring method based on joint detection of line spectrum and autocorrelation - Google Patents
A ship underwater acoustic monitoring method based on joint detection of line spectrum and autocorrelationInfo
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Abstract
本发明涉及一种线谱和自相关联合检测的船舶水声监测方法。充分利用船舶辐射噪声线谱和自相关检测两种不同方法各自的优点，采集信号后首先利用线谱检测实现是否有船只目标航行的识别，然后利用自相关检测实现目标确认及其运动状态变化的判别，实现是否有船舶航行到海底管线附近停泊或作业的准确识别。进而实现了对海管附近船舶活动情况的可靠安全监测，有效提升海管安防的水平。
The present invention relates to a ship underwater acoustic monitoring method using combined line spectrum and autocorrelation detection. Leveraging the respective advantages of both line spectrum and autocorrelation detection methods, after signal acquisition, line spectrum detection is first used to identify the presence of a target vessel. Autocorrelation detection is then used to identify the target and its motion state changes, enabling accurate identification of vessels anchored or operating near submarine pipelines. This enables reliable and safe monitoring of vessel activity near submarine pipelines, effectively improving pipeline security.
Description
Technical Field
The invention relates to the technical field of passive monitoring of underwater targets, in particular to a ship underwater sound monitoring method for line spectrum and autocorrelation combined detection.
Background
The national life of the submarine oil (gas) pipeline is related, and the safety of the submarine pipeline is ensured. In recent years, various measures are tried to be taken for protecting offshore pipes at home and abroad, and warning buoys are mainly distributed along the paths of the offshore pipes to prevent ships from being anchored or operated near the lines of the offshore pipes, but the protection effect is not obvious, and the omnibearing monitoring of the area to be protected is lacking. Therefore, it is imperative to establish a set of sea pipe security system for underwater and water surface omnibearing three-dimensional monitoring.
As shown in fig. 1, in a submarine oil (gas) pipeline safety monitoring system, a buoy-based underwater sound measurement and on-shore radar and video measurement combined automatic monitoring scheme is adopted, firstly, the characteristic that the underwater sound passive measurement can work for a long time is utilized, the acoustic monitoring and automatic identification of ships along the submarine pipeline are realized through a plurality of sonar buoys distributed along the submarine pipeline, whether targets exist or not and the target state are judged, whether the ship stays for a long time or the operation exists near a monitoring point or not is judged according to different frequency spectrums of ship navigation, operation and the like, and if the danger exists, alarm information is sent to a station control center machine room through Beidou data transmission equipment. The host computer of the station control center machine room utilizes the short-term active scanning of the shore radar to acquire accurate parameters of a suspicious target on the water surface, and the video monitoring equipment is used for the supplementary measurement of a radar near-end monitoring blind area. The processing flow of the underwater sound monitoring is as follows:
(1) The acoustic monitoring equipment on each buoy monitors underwater noise for a long time, if a ship sails or parks nearby, the acoustic equipment carries out intelligent analysis according to the time domain and frequency domain characteristics of the underwater noise, and judges whether the underwater noise forms a threat;
(2) If a threat is detected (the ship sails to berth or work near the sea pipe), the result of the underwater acoustic analysis is returned to the station control center. The station control center host further analyzes and confirms the returned information;
(3) The underwater sound monitoring system is designed according to the highest unattended requirement, no matter whether a ship is monitored or not, the underwater sound equipment can regularly return buoy state information every day, a host can monitor the buoy state, if the central control does not receive corresponding information, the host can send out an alarm of equipment failure.
The key technology of ship underwater sound recognition is characterized in that feature extraction, which is a valid feature capable of reflecting the essential feature of a target and meeting the requirement of remote detection in water, is extracted from ship radiation noise signals due to the complexity of marine environment and the specificity of underwater sound channels, and is always a difficult problem in the field. In general, a line spectrum detection method is adopted for ship target identification, as shown in fig. 2, when a ship sails, obvious line spectrum characteristics exist in the radiation noise, and the target identification is realized through line spectrum characteristic extraction (frequency, amplitude, line spectrum number and the like), but the change of the target motion state is difficult to accurately judge.
The line spectrum characteristics of the ships are different under different conditions such as ship type, navigational speed, tonnage, approach or departure, activities of a plurality of ships and the like, and in the military field, the line spectrum characteristics of certain specific ships are usually measured and a database is built so as to realize monitoring and early warning. But the situations that needs to be prevented are more when common people use the sea pipe, and a database covering all situations cannot be accurately built, so that whether the sea pipe is threatened cannot be accurately judged based on line spectrum structure detection through line spectrum feature extraction.
Disclosure of Invention
The invention provides a ship underwater sound monitoring method for combined detection of line spectrum and autocorrelation, which is characterized in that whether a ship sails or not is judged by the line spectrum detection method, the change of a target state is further confirmed and judged by the autocorrelation detection method, whether the ship stays or works for a long time near a sea pipe is judged, and the sea pipe safety underwater sound monitoring is realized. In particular, the object of the invention is achieved in that:
A ship underwater sound monitoring method for combined detection of line spectrum and autocorrelation comprises the following steps:
s1, signal receiving and sampling, namely sampling signals received by a hydrophone on buoy underwater sound detection equipment to obtain time domain signals;
Carrying out FFT (fast Fourier transform) on the signal data to obtain a frequency domain signal for subsequent use;
S3, setting a threshold value, counting the number of line spectrums exceeding an amplitude threshold, and confirming whether a ship target exists or not;
S4, performing autocorrelation calculation, namely preparing to perform autocorrelation calculation on the received signal if a ship target exists;
s5, confirming target detection based on autocorrelation, setting an effective threshold value, and confirming the ship target on the basis of autocorrelation operation;
S6, identifying a target state based on the correlation transient change, and judging the motion state change of the target, namely whether the ship stays near, approaches or moves away from the submarine pipeline or not through the correlation transient change detection;
s7, self-adaptive threshold, wherein reliable receiving and detecting of the signal are ensured through self-adaptive threshold setting due to fluctuation of the amplitude of the received signal;
S8, timing control, namely detecting and judging the received signal in a certain time, and giving an alarm to a system host if the ship stays near the sea pipe or approaches the sea pipe for a period of time;
and S9, comprehensively judging communication interaction, namely comprehensively judging whether a ship stays near a sea pipe for a long time or approaches by using two methods of line spectrum and autocorrelation, sending alarm information to a system host through Beidou communication interaction, and continuously monitoring.
Further, the step S3 includes the following procedures:
S3.1, setting a system working frequency range according to the spectral characteristics of ship radiation noise and environmental noise, and calculating the amplitude of each line spectrum in the set system working frequency range;
s3.2, judging whether the amplitude of the line spectrum is larger than a set line spectrum threshold value in the effective frequency range, if so, setting the mark of the corresponding line spectrum to be effective, otherwise, setting the mark to be ineffective;
s3.3, counting accumulated effective time or effective times of each spectral line in target confirmation time, and then respectively judging whether each spectral line is an effective line spectrum or not;
s3.4, counting the number of the effective line spectrums in the target confirmation time, and judging whether the number of the effective line spectrums is larger than the number of the line spectrums required by the target effectiveness;
s3.5, if the number of the effective line spectrums is larger than the number of the line spectrums required by the effective target, firstly recording the time for finding the target, adding 1 to the continuous effective times of the target, then comparing the time with a set threshold, if so, considering that the target is found to be effective, and placing the target in parallel, otherwise, setting 0 to the continuous effective times of the target, and then further judging whether the target is invalid;
S3.6, counting the number of invalid line spectrums in the target confirmation time, and judging whether the number of the invalid line spectrums is larger than the number of line spectrums required by target invalidation;
S3.7, if the number of invalid line spectrums is larger than the number of line spectrums required by invalidating the target, adding 1 to the number of continuous invalidations of the target, comparing the number of continuous invalidations of the target with a set threshold, if the number of continuous invalidations of the target is larger than the set threshold, considering that the target is actually lost, and setting the target as invalid, and if the number of continuous invalidations of the target is not larger than the set threshold, setting the number of continuous invalidations of the target as 0.
Further, the step S5 includes the following steps:
s5.1, filtering or windowing is carried out on the output of the FFT according to the set frequency range;
s5.2, selecting relevant data segments to perform relevant calculation according to the set relevant time, and storing new relevant copies;
S5.3, performing low-pass filtering on the related output, comparing the related output with a set target effective threshold, and if the related output is larger than the set target effective threshold, entering a step S5.4, and if the related output is not larger than the set target effective threshold, entering a step S5.5;
S5.4, firstly adding 1 to the continuous effective times of the target, then comparing the continuous effective times with the effective confirmation times of the target, and if the continuous effective times of the target are larger than the confirmation times, judging the state of the target to be effective;
S5.5, clearing 0' for the continuous effective times of the target, comparing the related output with a threshold that the target is invalid, and if the related output is larger than the threshold that the target is invalid, entering step S5.6, and if the related output is not larger than the threshold that the target is invalid, entering step S5.7;
s5.6, adding 1 to the continuous invalid times of the target, comparing the continuous invalid times with the invalid confirmation times of the target, if the continuous invalid times are larger than the invalid confirmation times, recording the time as the time of losing the target, and entering a step S5.8 self-adaptive threshold processing, otherwise, directly entering the step S5.8 self-adaptive threshold processing;
S5.7, clearing '0' of continuous invalid times of the target, and then entering step S5.8 of self-adaptive threshold processing;
s5.8, the target state is not modified, and the self-adaptive threshold processing is carried out.
Further, the square sum of the correlation outputs of one time is performed in the step S5.3 and is used as a correlation output point, and the correlation output is 1024 points.
Further, the step S6 includes the following steps:
S6.1, if the current target state is valid and the last target state is valid, recording the current time as the time when the target is valid to determine the time when the target is found last time;
S6.2, if the current target state is valid and the last target state is invalid, recording the current time as the time for finding the target for the first time;
s6.3, if the current target state is invalid and the last target state is invalid, directly returning;
S6.4, if the current target state is invalid and the last target state is valid, firstly recording the current time as the time of target loss so as to determine whether the target is stopped or far away, then calculating the transition time from last valid to invalid, comparing with the set stopping time, if the transition time is greater than the last valid to invalid, judging that the target is far away, otherwise, considering that the target is stopped near the buoy, and giving parking alarm information.
The working principle of the invention is as follows:
The invention provides a ship underwater sound monitoring method based on line spectrum and autocorrelation combined detection, which utilizes line spectrum detection to realize the identification of whether a ship is sailed or not. And the target confirmation and the judgment of the motion state change are realized by utilizing the autocorrelation detection, and the accurate identification of whether the ship sails to the vicinity of the submarine pipeline or the operation is realized.
As shown in FIG. 4, the monitoring flow is as follows, ① samples the signal received by the hydrophone on the buoy to obtain a time domain signal, ② carries out FFT conversion to detect the line spectrum of the signal in the signal frequency domain, ③ carries out statistics to the number of the line spectrums exceeding the amplitude threshold to determine whether a ship target exists, ④ carries out autocorrelation calculation to the received signal next, ⑤ carries out ship target confirmation on the basis of autocorrelation calculation, ⑥ judges the motion state change of the target through correlation transient change detection, namely whether the ship stays near a submarine pipeline or is far away, ⑦ ensures reliable receiving and detecting of the signal through self-adaptive threshold setting due to fluctuation of the amplitude of the received signal, ⑧ timing control is used for detecting and judging the received signal in a certain time, and gives an alarm to a system host if the ship stays near the submarine pipeline in a certain time, ⑨ comprehensively judges communication interaction, judges whether the ship stays near the submarine pipeline for a long time through the two methods of the line spectrums and gives alarm information to the system host through Beidou communication interaction, and simultaneously carries out monitoring.
By the combined application of the two methods, accurate identification of whether a ship sails to berth or work near a submarine pipeline is realized.
The autocorrelation receiver is used for detecting the time correlation of a signal and can reflect different states of a target at different moments. A schematic block diagram of a time domain implementation of autocorrelation reception is shown in fig. 3. In order to increase the operation speed and reduce the operation amount, the fast operation method of FFT is fully utilized to perform the autocorrelation operation in the frequency domain.
The invention has the following beneficial effects:
The invention provides a ship underwater sound monitoring method by combining line spectrum and autocorrelation, which fully utilizes the respective advantages of two different methods of ship radiation noise line spectrum and autocorrelation detection, firstly uses line spectrum detection to realize the identification of whether a ship target sails near a sea pipe, then uses autocorrelation detection to realize the further identification of the target and the discrimination of the motion state change of the target, realizes the accurate identification of whether the ship sails near a submarine pipeline for berthing or operation, further realizes the reliable safety monitoring of the ship activity condition near the sea pipe, and effectively improves the safety and protection level of the sea pipe.
Drawings
FIG. 1 is a schematic diagram of a combined monitoring scheme for targets in water according to the background art of the invention;
FIG. 2 is a schematic diagram of a line spectrum of a ship during voyage according to the background art of the invention;
FIG. 3 is a schematic block diagram of a time domain implementation of the autocorrelation reception in accordance with the present invention;
FIG. 4 is a flow chart of a ship underwater sound monitoring method based on the combined detection of line spectrum and autocorrelation according to an embodiment of the present invention
A program chart;
FIG. 5 is a flowchart of a line spectrum based object detection according to an embodiment of the present invention;
FIG. 6 is a flowchart of an embodiment of the invention for determining target detection based on autocorrelation;
fig. 7 is a flowchart of target state recognition based on correlation transient changes according to an embodiment of the invention.
Detailed Description
In order to make the technical means, the creation characteristics and the achievement of the purposes of the invention easy to understand, the technical scheme of the invention is further described below by combining one embodiment and a specific implementation mode of the ship underwater sound monitoring method for combined detection of line spectrum and autocorrelation.
As shown in fig. 1-7, the specific examples given for the present invention are as follows:
A ship water sound monitoring method based on combined detection of line spectrum and autocorrelation includes such steps as sampling the signal received by hydrophone on buoy to obtain time-domain signal, FFT transforming ② to obtain line spectrum, detecting the line spectrum in signal frequency domain, counting ③ to determine if there is ship target, ④ to perform autocorrelation calculation on the received signal, ⑤ to determine ship target on the basis of autocorrelation calculation, ⑥ to determine if the ship is in close proximity to submarine pipeline by transient change detection of correlation, ⑦ to ensure reliable receiving and detection of signal by adaptive threshold setting due to fluctuation of received signal amplitude, ⑧ timing control to detect and determine the received signal in a certain time, giving alarm to system host if ship is still in close proximity to submarine pipeline in a certain time, ⑨ to comprehensively determine communication interaction, determining if there is ship in close proximity to submarine pipeline for a long time by two methods, giving alarm information by Beidou communication interaction, and monitoring. By the combined application of the two methods, accurate identification of whether a ship sails to berth or work near a submarine pipeline is realized.
The line spectrum characteristic is an inherent characteristic of the moving ship, and the detection of whether the moving ship exists or not can be performed by detecting the line spectrum characteristic of the ship, namely, step ③, and the specific content is as follows as shown in fig. 5:
(1) And calculating the amplitude of each line spectrum within a set system working frequency range (set according to the spectral characteristics of ship radiation noise and environmental noise).
(2) Judging whether the amplitude of the line spectrum is larger than a set line spectrum threshold value or not in the effective frequency range;
If the amplitude of the line spectrum is larger than the threshold, the mark of the corresponding line spectrum is set to be effective, otherwise, the mark is set to be ineffective.
(3) And counting the accumulated effective time (or effective times) of each spectral line in the target confirmation time, and then respectively judging whether each spectral line is an effective line spectrum or not.
(4) And counting the number of the effective line spectrums in the target confirmation time, and judging whether the number of the effective line spectrums is larger than the number of the line spectrums required by the target effectiveness.
(5) If the number of the effective line spectrums is larger than the number of the line spectrums required by the effective object, firstly recording the time for finding the object, adding 1 to the continuous effective times of the object, then judging whether the continuous effective times of the object are larger than a set threshold, if so, actually finding the object, juxtaposing the object as effective, and if not, judging whether the object is effective.
(6) If the number of valid line spectrums is not greater than the number of line spectrums required by the target to be valid, the number of continuous valid times of the target is set to 0, and then whether the target is invalid is further judged.
(7) And counting the number of the invalid line spectrums in the target confirmation time, and judging whether the number of the invalid line spectrums is larger than the number of the line spectrums required by target invalid effect.
(8) If the number of invalid line spectrums is larger than the number of line spectrums required by invalidating the target, adding 1 to the number of continuous invalidations of the target, then judging whether the number of continuous invalidations of the target is larger than a set threshold, if so, considering that the target is actually lost, setting the target as invalid, and if not, setting the number of continuous invalidations of the target as 0, and then judging whether the target is valid or not.
The autocorrelation is an effective method for detecting the similarity of two signals, and after obtaining the correlation output of the signals, the target is further confirmed, i.e. step ⑤, and the specific content is as follows in fig. 6:
(1) Filtering (or windowing) the output of the FFT according to the set frequency range;
(2) Selecting relevant data segments to perform relevant calculation according to the set relevant time, and storing new relevant copies;
(3) Square summing the correlation outputs of one time (1024 points) as one correlation output point;
(4) And (3) filtering the related output, comparing the filtered related output with a set target effective threshold, if the filtered related output is larger than the set target effective threshold, continuing the step (5), and if the filtered related output is not larger than the set target effective threshold, continuing the step (6).
(5) Firstly, adding 1 to the continuous effective times of the target, then comparing the continuous effective times of the target with the effective confirmation times of the target, if the continuous effective times of the target are larger than the effective confirmation times, judging the state of the target to be effective, otherwise, directly entering the self-adaptive threshold processing (9) without modifying the state of the target.
(6) The target continuously valid times clear 0, then the comparison of the related output and the threshold with invalid target is carried out, if the result is larger than the threshold, the step (7) is carried out, and if the result is not larger than the threshold, the step (8) is continued.
(7) Firstly, adding '1' to the continuous invalidation times of the target, then comparing the continuous invalidation times of the target with the invalid confirmation times of the target, if the continuous invalidation times of the target are larger than the invalid confirmation times, recording the moment as the time of losing the target, entering the self-adaptive threshold processing, and otherwise, directly entering the self-adaptive threshold processing.
(8) The target continuously invalidates times and clears '0', and then enters adaptive threshold processing.
(9) The target state is not modified and directly enters the self-adaptive threshold processing (9)
A more important step after determining whether the target is valid is the identification of the target motion state transition. Based on the relevant object transformation identification process, i.e. step ⑥, the specific content is as follows as shown in fig. 7:
(1) If the current target state is valid and the last target state is valid, recording the current time as the time when the target was valid (so as to determine the time when the target was found last time);
(2) If the current target state is valid and the last target state is invalid, recording the current time as the time for finding the target for the first time;
(3) If the current target state is invalid and the last target state is invalid, directly returning;
(4) If the current target state is invalid and the last target state is valid, firstly recording the current time as the lost time of the target (so as to determine whether the target is parked or walked away), then calculating the transition time from the last valid to the invalid, comparing with the set parking time, if the comparison result is larger than the set parking time, judging that the target is far away, otherwise, considering that the target is parked nearby the buoy, and giving parking alarm information.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explanation of the principles of the present invention and are in no way limiting of the invention. Accordingly, any modification, equivalent replacement, improvement, etc. made without departing from the spirit and scope of the present invention should be included in the scope of the present invention. Furthermore, the appended claims are intended to cover all such changes and modifications that fall within the scope and boundary of the appended claims, or equivalents of such scope and boundary.
Claims (5)
1. The ship underwater sound monitoring method for the combined detection of line spectrum and autocorrelation is characterized by comprising the following steps of:
s1, signal receiving and sampling, namely sampling signals received by a hydrophone on buoy underwater sound detection equipment to obtain time domain signals;
S2, FFT calculation, namely performing FFT conversion on signal data to obtain a frequency domain signal for subsequent use, S3, setting a threshold value, and counting the number of line spectrums exceeding an amplitude threshold to confirm whether a ship target exists or not based on target detection of a line spectrum structure;
S4, performing autocorrelation calculation, namely preparing to perform autocorrelation calculation on a received signal if a ship target exists, S5 performing target detection confirmation based on autocorrelation, setting an effective threshold value, and performing ship target confirmation based on autocorrelation operation;
S6, identifying a target state based on the correlation transient change, judging the motion state change of the target, namely whether a ship stays near, approaches or moves away from a submarine pipeline or not through the correlation transient change detection, S7, and ensuring the reliable receiving and detecting of the signal through the self-adaptive threshold setting due to fluctuation of the amplitude of the received signal;
S8, timing control, namely detecting and judging the received signal in a certain time, and giving an alarm to a system host if the ship stays near the sea pipe or approaches the sea pipe for a period of time;
and S9, comprehensively judging communication interaction, namely comprehensively judging whether a ship stays near a sea pipe for a long time or approaches by using two methods of line spectrum and autocorrelation, sending alarm information to a system host through Beidou communication interaction, and continuously monitoring.
2. The ship underwater sound monitoring method of combined line spectrum and autocorrelation detection as set forth in claim 1, wherein said step S3 comprises the following steps:
S3.1, setting a system working frequency range according to the spectral characteristics of ship radiation noise and environmental noise, and calculating the amplitude of each line spectrum in the set system working frequency range;
s3.2, judging whether the amplitude of the line spectrum is larger than a set line spectrum threshold value in the effective frequency range, if so, setting the mark of the corresponding line spectrum to be effective, otherwise, setting the mark to be ineffective;
s3.3, counting accumulated effective time or effective times of each spectral line in target confirmation time, and then respectively judging whether each spectral line is an effective line spectrum or not;
s3.4, counting the number of the effective line spectrums in the target confirmation time, and judging whether the number of the effective line spectrums is larger than the number of the line spectrums required by the target effectiveness;
s3.5, if the number of the effective line spectrums is larger than the number of the line spectrums required by the effective target, firstly recording the time for finding the target, adding 1 to the continuous effective times of the target, then comparing the time with a set threshold, if so, considering that the target is found to be effective, and placing the target in parallel, otherwise, setting 0 to the continuous effective times of the target, and then further judging whether the target is invalid;
S3.6, counting the number of invalid line spectrums in the target confirmation time, and judging whether the number of the invalid line spectrums is larger than the number of line spectrums required by target invalidation;
S3.7, if the number of invalid line spectrums is larger than the number of line spectrums required by invalidating the target, adding 1 to the number of continuous invalidations of the target, comparing the number of continuous invalidations of the target with a set threshold, if the number of continuous invalidations of the target is larger than the set threshold, considering that the target is actually lost, and setting the target as invalid, and if the number of continuous invalidations of the target is not larger than the set threshold, setting the number of continuous invalidations of the target as 0.
3. The ship underwater sound monitoring method of combined line spectrum and autocorrelation detection as set forth in claim 1, wherein said step S5 comprises the following steps:
s5.1, filtering or windowing the output of the FFT according to a set frequency range, S5.2, selecting relevant data segments to perform relevant calculation according to a set relevant time, and storing new relevant copies;
S5.3, performing low-pass filtering on the related output, comparing the related output with a set target effective threshold, and if the related output is larger than the set target effective threshold, entering a step S5.4, and if the related output is not larger than the set target effective threshold, entering a step S5.5;
S5.4, firstly adding 1 to the continuous effective times of the target, then comparing the continuous effective times with the effective confirmation times of the target, and if the continuous effective times of the target are larger than the confirmation times, judging the state of the target to be effective;
S5.5, clearing 0' for the continuous effective times of the target, comparing the related output with a threshold that the target is invalid, and if the related output is larger than the threshold that the target is invalid, entering step S5.6, and if the related output is not larger than the threshold that the target is invalid, entering step S5.7;
s5.6, adding 1 to the continuous invalid times of the target, comparing the continuous invalid times with the invalid confirmation times of the target, if the continuous invalid times are larger than the invalid confirmation times, recording the time as the time of losing the target, and entering a step S5.8 self-adaptive threshold processing, otherwise, directly entering the step S5.8 self-adaptive threshold processing;
s5.7, the continuous invalid times of the target are cleared to be 0, then the self-adaptive threshold processing is carried out in the step S5.8, the state of the target is not modified in the step S5.8, and the self-adaptive threshold processing is carried out.
4. A ship underwater sound monitoring method based on line spectrum and autocorrelation detection as set forth in claim 3, wherein the square sum of the correlation outputs of one time is used as a correlation output point in the step S5.3, and the correlation output is 1024 points.
5. The ship underwater sound monitoring method of combined line spectrum and autocorrelation detection as set forth in claim 1, wherein said step S6 comprises the following steps:
S6.1, if the current target state is valid and the last target state is valid, recording the current time as the time when the target is valid to determine the time when the target is found last time;
S6.2, if the current target state is valid and the last target state is invalid, recording the current time as the time for finding the target for the first time;
S6.3, if the current target state is invalid and the last target state is invalid, returning directly, S6.4, if the current target state is invalid and the last target state is valid, firstly recording the current time as the lost time of the target so as to determine whether the target is stopped or far away, then calculating the transition time from last valid to invalid, comparing with the set stopping time, if the transition time is greater than the set stopping time, judging that the target is far away, otherwise, considering that the target is stopped near the buoy, and giving parking alarm information.
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