A ship underwater acoustic monitoring method based on joint detection of line spectrum and autocorrelation

Abstract

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

[0001] The present invention relates to the technical field of passive monitoring of underwater targets, and in particular to a ship underwater acoustic monitoring method using line spectrum and autocorrelation joint detection. Background Art

[0002] Submarine oil and gas pipelines are crucial to national economy and livelihoods, and ensuring their safety is of paramount importance. Faced with the increasingly prominent challenge of underwater pipeline security, various measures have been attempted in recent years, both domestically and internationally, to protect nearshore sections of these pipelines. These measures primarily involve deploying warning buoys along pipeline routes to prevent vessels from anchoring or operating near them. However, these measures have been ineffective, lacking comprehensive monitoring of the protected areas. Therefore, establishing a comprehensive, three-dimensional underwater and surface monitoring system for pipeline security is imperative.

[0003] like Figure 1 As shown, a joint automatic monitoring scheme using buoy-based hydroacoustic measurement combined with shore radar and video measurement is adopted in a submarine oil (gas) pipeline safety monitoring system. First, the long-term working characteristics of passive hydroacoustic measurement are utilized to realize acoustic monitoring and automatic identification of ships along the pipeline through multiple sonar buoys deployed along the pipeline to determine the presence and status of targets; based on different frequency spectra such as ship navigation and operation, it is determined whether there are any dangers such as ships staying or operating for a long time near the monitoring point; if there is any danger, an alarm message is sent to the station control center computer room through the Beidou data transmission equipment. The main computer in the station control center computer room then uses the short-term active scanning of the shore-based radar to obtain the accurate parameters of suspicious targets on the water surface, and the video monitoring equipment is used for supplementary measurement of the radar's near-end monitoring blind spot. The processing flow of its hydroacoustic monitoring is as follows:

[0004] (1) The acoustic monitoring equipment on each buoy monitors underwater noise over a long period of time. If a ship is detected sailing or anchored nearby, the acoustic equipment will perform intelligent analysis based on the time and frequency domain characteristics of the underwater noise to determine whether it poses a threat.

[0005] (2) If a threat is detected (a ship is anchored or operating near the sea pipe), the hydroacoustic analysis results are transmitted back to the station control center. The host computer at the station control center further analyzes and confirms the returned information;

[0006] (3) The underwater acoustic monitoring system is designed according to the highest requirements of unmanned operation. Regardless of whether a ship is detected or not, the underwater acoustic equipment will regularly send back buoy status information every day. The host can monitor the buoy status. If the central control does not receive the corresponding information, the host will issue an equipment failure warning.

[0007] The key technology of ship underwater acoustic recognition lies in feature extraction. Due to the complexity of the ocean environment and the particularity of the underwater acoustic channel, extracting an effective feature from the ship radiation noise signal that can both reflect the essential characteristics of the target and meet the requirements of long-range underwater detection has always been a difficult problem in this field. Usually, ship target recognition uses line spectrum detection methods, such as Figure 2 As shown in the figure, when a ship is sailing, its radiated noise has obvious line spectrum characteristics; target recognition is achieved by extracting line spectrum characteristics (frequency, amplitude, number of line spectra, etc.), but it is difficult to accurately judge the changes in the target's motion state.

[0008] Line spectrum characteristics vary depending on vessel type, speed, tonnage, approaching or departing, and the activity of multiple vessels. In the military, the line spectrum characteristics of specific vessels are typically measured and a database is established to monitor and warn of these situations. However, civilian use requires more precautions, and it is impossible to accurately establish a comprehensive database. Therefore, simply extracting line spectrum characteristics and detecting line spectrum structures alone cannot accurately determine whether a subsea pipeline is under threat. Summary of the Invention

[0009] The present invention proposes a ship underwater acoustic monitoring method that combines line spectrum and autocorrelation detection. Line spectrum detection is used to determine whether a ship is sailing, while autocorrelation detection is used to further confirm and identify changes in target status, thereby determining whether a ship has been stationary or operating near a subsea pipeline for an extended period of time. This method enables underwater acoustic monitoring of subsea pipeline safety. Specifically, the present invention achieves this objective by:

[0010] A ship underwater acoustic monitoring method using line spectrum and autocorrelation joint detection comprises the following steps:

[0011] S1 signal reception sampling: sampling the signal received by the hydrophone on the buoy hydroacoustic detection equipment to obtain a time domain signal;

[0012] S2 FFT calculation: the signal data is transformed by FFT to obtain the frequency domain signal for subsequent use;

[0013] S3 is based on target detection of line spectrum structure; set the threshold value, count the number of line spectra exceeding the amplitude threshold, and confirm whether there is a ship target;

[0014] S4 autocorrelation calculation: if there is a ship target, prepare to perform autocorrelation calculation on the received signal;

[0015] S5: Target detection and confirmation based on autocorrelation; set the effective threshold value and confirm the ship target based on the autocorrelation operation;

[0016] S6: Target state recognition based on correlation transient changes; by detecting correlation transient changes, it determines the target's motion state changes, i.e., whether the ship is staying near, approaching, or moving away from the submarine pipeline;

[0017] S7 adaptive threshold: Due to the fluctuation of the received signal amplitude, the adaptive threshold setting ensures reliable signal reception and detection;

[0018] S8 timing control: detects and identifies received signals within a certain period of time, and sends an alarm to the system host if the ship remains near or approaches the sea pipe within a certain period of time;

[0019] S9 comprehensive judgment communication interaction: It uses line spectrum and autocorrelation methods to comprehensively judge whether there are ships staying near or approaching the sea pipe for a long time, and sends an alarm message to the system host through Beidou communication interaction, while continuing to implement monitoring.

[0020] Furthermore, step S3 includes the following process:

[0021] S3.1 Set the system operating frequency range based on the spectrum characteristics of the ship's radiated noise and ambient noise, and calculate the amplitude of each line spectrum within the set system operating frequency range;

[0022] S3.2: Within the effective frequency range, determine whether the amplitude of the line spectrum is greater than the set line spectrum threshold value; if the line spectrum amplitude is greater than the threshold, the flag of the corresponding line spectrum is set to valid; otherwise, it is set to invalid;

[0023] S3.3 Within the target confirmation time, count the cumulative effective time or effective number of each spectrum line, and then determine whether each spectrum line is a valid line spectrum;

[0024] S3.4 Within the target confirmation time, count the number of valid line spectra and determine whether the number of valid line spectra is greater than the number of line spectra required for target validity;

[0025] S3.5 If the number of valid spectra is greater than the number of spectra required for the target to be valid, first record the time the target was found and add "1" to the number of consecutive valid target times. Then compare it with the set threshold. If it is greater than the threshold, it is considered that the target was found and the target is set to valid. Otherwise, the number of consecutive valid target times is set to "0", and then further determine whether the target is invalid.

[0026] S3.6 Count the number of invalid line spectra within the target confirmation time, and determine whether the number of invalid line spectra is greater than the number of line spectra required to invalidate the target;

[0027] S3.7 If the number of invalid line spectra is greater than the number of line spectra required for the target to be invalid, the number of times the target is continuously invalid is added to "1"; then it is compared with the set threshold; if it is greater, it is considered that the target is indeed lost and the target is set to invalid; if it is not greater, the number of times the target is continuously invalid is first set to "0".

[0028] Furthermore, step S5 includes the following steps:

[0029] S5.1 filters or window the FFT output according to the set frequency range;

[0030] S5.2 Select relevant data segments for relevant calculations based on the set relevant time, and store new relevant copies;

[0031] S5.3 performs low-pass filtering on the relevant output and compares it with the set target effective threshold. If it is greater than the target effective threshold, the process proceeds to step S5.4; if it is not greater than the target effective threshold, the process proceeds to step S5.5;

[0032] S5.4 first adds "1" to the target's consecutive valid times, and then compares it with the target's valid confirmation times. If it is greater than the target's valid status, the target status is determined to be valid; otherwise, it directly enters step S5.8 for adaptive threshold processing;

[0033] S5.5 First, the number of consecutive valid target times is cleared to "0", and then the correlation output is compared with the target invalid threshold. If the correlation output is greater than the target invalid threshold, the process proceeds to step S5.6; if not, the process proceeds to step S5.7;

[0034] S5.6 adds "1" to the number of consecutive target invalidation times, and then compares it with the number of target invalidation confirmations. If it is greater than the number, this moment is recorded as the time when the target is lost, and the process proceeds to step S5.8 adaptive threshold processing; otherwise, the process proceeds directly to step S5.8 adaptive threshold processing;

[0035] S5.7 The number of consecutive invalid targets is cleared to "0", and then the process goes to step S5.8 for adaptive threshold processing;

[0036] S5.8 The target state is not modified and enters the adaptive threshold processing.

[0037] Furthermore, in step S5.3, the square sum of the correlation outputs is performed to form a correlation output point; the correlation output is 1024 points.

[0038] Furthermore, step S6 includes the following process:

[0039] S6.1 If the current target status is valid and the previous target status was valid, record the current time as the target valid time to determine the last time the target was found;

[0040] S6.2 If the current target status is valid and the previous target status was invalid, record the current time as the time when the target was first discovered;

[0041] S6.3 If the current target state is invalid and the previous target state is invalid, return directly;

[0042] S6.4 If the current target status is invalid and the previous target status is valid, first record the current time as the time when the target is lost in order to determine whether the target is stopped or moving away; then calculate the transition time from the last valid to invalid time and compare it with the set stop time. If it is greater, the target is judged to be moving away; otherwise, it is considered that the target has stopped near the buoy and a stop alarm message is given.

[0043] The working principle of the present invention is as follows:

[0044] This invention proposes a ship underwater acoustic monitoring method that combines line spectrum and autocorrelation detection. Line spectrum detection is used to identify the presence of a target ship. Autocorrelation detection is used to identify the target and its motion state changes, enabling accurate identification of whether a ship is anchored or operating near a submarine pipeline.

[0045] like Figure 4 As shown in Figure 1, the monitoring process is as follows: ① The signal received by the hydrophone on the buoy is sampled to obtain a time domain signal; ② After FFT transformation, its line spectrum is detected in the signal frequency domain; ③ The number of line spectra exceeding the amplitude threshold is counted to confirm whether there is a ship target; ④ The received signal is then autocorrelated; ⑤ The ship target is confirmed based on the autocorrelation operation; ⑥ The target's motion state change is determined by detecting transient changes in the correlation, that is, whether the ship is staying near or moving away from the submarine pipeline; ⑦ Due to the fluctuations in the amplitude of the received signal, an adaptive threshold is set to ensure reliable signal reception and detection; ⑧ Timing control is used to detect and determine the received signal within a certain period of time. If the ship still stays near the submarine pipeline within a period of time, an alarm is issued to the system host; ⑨ Comprehensive judgment and communication interaction are carried out. The line spectrum and autocorrelation methods are used to comprehensively determine whether a ship has stayed near the submarine pipeline for a long time. An alarm message is sent to the system host through Beidou communication interaction, and monitoring continues.

[0046] By combining the two methods, it is possible to accurately identify whether a ship is moored or operating near a submarine pipeline.

[0047] The autocorrelation receiver is used to detect the time correlation of a signal, which can reflect the different states of the target at different times. The time domain implementation principle block diagram of the autocorrelation receiver is as follows: Figure 3 In order to increase the operation speed and reduce the amount of calculation, the fast operation method of FFT is fully utilized to perform autocorrelation operation in the frequency domain.

[0048] The beneficial effects of the present invention are as follows:

[0049] The present invention proposes a ship underwater acoustic monitoring method using a combined line spectrum and autocorrelation detection method. This method fully utilizes the respective advantages of the two different methods, line spectrum detection of ship radiation noise and autocorrelation detection. Line spectrum detection is first used to identify whether a ship target is sailing near a submarine pipeline. Then, autocorrelation detection is used to further confirm the target and discriminate changes in its motion state. This method accurately identifies whether a ship is anchored or operating near a submarine pipeline, thereby enabling reliable and safe monitoring of ship activities near the submarine pipeline and effectively improving the level of submarine pipeline security. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a schematic diagram of the joint monitoring solution for underwater targets described in the background technology of the present invention;

[0051] Figure 2 This is a schematic diagram of the line spectrum of a ship sailing as described in the background technology of the present invention;

[0052] Figure 3 This is a block diagram of the time domain implementation principle of the autocorrelation reception of the present invention;

[0053] Figure 4 The method for ship underwater acoustic monitoring using line spectrum and autocorrelation joint detection according to the embodiment of the present invention is as follows:

[0054] Program map;

[0055] Figure 5 This is a flow chart of target detection based on line spectrum according to an embodiment of the present invention;

[0056] Figure 6 This is a flowchart of target detection and confirmation based on autocorrelation according to an embodiment of the present invention;

[0057] Figure 7 This is a flow chart of target state recognition based on transient changes in correlation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] In order to make the technical means, creative features and objectives achieved by the present invention easy to understand, the technical solution of the present invention is further explained below in combination with one of the embodiments and specific implementation methods of a ship underwater acoustic monitoring method for joint detection of line spectrum and autocorrelation given by the present invention.

[0059] like Figure 1-7 As shown, the specific embodiments given for the present invention are as follows:

[0060] A ship underwater acoustic monitoring method based on line spectrum and autocorrelation joint detection, such as Figure 4The process shown includes the following: ① Sampling the signal received by the hydrophone on the buoy to obtain a time domain signal; ② After FFT transformation, the signal's line spectrum is detected in the frequency domain; ③ The number of line spectra exceeding the amplitude threshold is counted to confirm the presence of a vessel target; ④ Next, autocorrelation is performed on the received signal; ⑤ Based on the autocorrelation calculation, the vessel target is confirmed; ⑥ Transient changes in the correlation are detected to determine whether the target's motion state changes, that is, whether the ship is lingering near or moving away from the submarine pipeline; ⑦ Due to fluctuations in the received signal amplitude, an adaptive threshold is set to ensure reliable signal reception and detection; ⑧ Timing control is used to detect and identify the received signal within a certain period of time. If the ship remains near the submarine pipeline within a certain period of time, an alarm is issued to the system host; ⑨ Comprehensive judgment and communication interaction are used to determine whether a ship has remained near the submarine pipeline for an extended period of time using both line spectrum and autocorrelation methods. An alarm is then issued to the system host through Beidou communication interaction, while monitoring continues. The combined application of these two methods enables accurate identification of whether a ship has sailed near the submarine pipeline for anchoring or operating.

[0061] Line spectrum characteristics are inherent characteristics of moving ships. By detecting the line spectrum characteristics of ships, we can detect whether there is a moving ship, which is step ③. The specific content is as follows: Figure 5 As shown below:

[0062] (1) Calculate the amplitude of each line spectrum within the set system operating frequency range (set according to the spectrum characteristics of ship radiation noise and environmental noise).

[0063] (2) Within the effective frequency range, determine whether the amplitude of the line spectrum is greater than the set line spectrum threshold;

[0064] If the line spectrum amplitude is greater than the threshold, the flag of the corresponding line spectrum is set to valid; otherwise, it is set to invalid.

[0065] (3) Within the target confirmation time, the cumulative effective time (or effective times) of each spectrum line is counted, and then each spectrum line is judged to be a valid line spectrum.

[0066] (4) Within the target confirmation time, count the number of valid line spectra and determine whether the number of valid line spectra is greater than the number of line spectra required for the target to be valid.

[0067] (5) If the number of valid line spectra is greater than the number of line spectra required for the target to be valid, first record the time when the target is found, and add "1" to the number of times the target is continuously valid; then judge whether the number of times the target is continuously valid is greater than the set threshold; if it is greater, it is considered that the target is indeed found and the target is set to be valid; if it is not greater, no judgment is made on whether the target is valid.

[0068] (6) If the number of valid line spectra is not greater than the number of line spectra required for the target to be valid, the number of times the target is continuously valid is set to "0", and then further judgment is made as to whether the target is invalid.

[0069] (7) Within the target confirmation time, count the number of invalid line spectra and determine whether the number of invalid line spectra is greater than the number of line spectra required for target invalidation.

[0070] (8) If the number of invalid line spectra is greater than the number of line spectra required for the target to be invalid, the number of times the target is continuously invalid is added by "1"; then it is determined whether the number of times the target is continuously invalid is greater than the set threshold; if it is greater, it is considered that the target is indeed lost and the target is set to invalid; if it is not greater, the number of times the target is continuously invalid is first set to "0", and then no judgment is made on whether the target is valid.

[0071] Autocorrelation is an effective method to detect the similarity between two signals. After obtaining the signal correlation output, the first step is to further confirm the target, which is step ⑤. The specific content is as follows: Figure 6 As shown below:

[0072] (1) Filter (or window) the FFT output according to the set frequency range;

[0073] (2) Select relevant data segments for relevant calculations based on the set relevant time, and store new relevant copies;

[0074] (3) Take the square sum of the correlation output (1024 points) as a correlation output point;

[0075] (4) Filter the relevant output and compare it with the set target effective threshold. If it is greater than the target effective threshold, continue to step (5); if it is not greater than the target effective threshold, continue to step (6).

[0076] (5) First, add "1" to the target continuous valid times, then compare the target continuous valid times with the target valid confirmation times. If they are greater, the target state is determined to be valid; otherwise, the target state is not modified and the adaptive threshold processing (9) is directly entered.

[0077] (6) First, the number of consecutive valid target times is cleared to "0", and then the "related output" is compared with the "threshold for invalid target". If it is greater than, proceed to step (7); if not, continue to step (8).

[0078] (7) First, add "1" to the number of consecutive invalid targets, and then compare the number of consecutive invalid targets with the number of confirmations that the target is invalid. If it is greater, this moment is recorded as the time when the target is lost and enters the adaptive threshold processing; otherwise, it directly enters the adaptive threshold processing.

[0079] (8) The number of consecutive invalid targets is cleared to “0”, and then the adaptive threshold processing is started.

[0080] (9) The target state is not modified and directly enters the adaptive threshold processing (9)

[0081] After determining whether the target is valid, the more important step is to identify the target's motion state transition. The target transition identification process is based on the relevant step ⑥, and the specific content is as follows: Figure 7 As shown below:

[0082] (1) If the current target state is valid and the previous target state was valid, record the current time as the target valid time (in order to determine the last time the target was found);

[0083] (2) If the current target state is valid and the previous target state is invalid, then record the current time as the time when the target was first discovered;

[0084] (3) If the current target state is invalid and the previous target state is invalid, return directly;

[0085] (4) If the current target state is invalid and the previous target state is valid, first record the current time as the time when the target is lost (in order to determine whether the target is parked or moving away); then calculate the transition time from the last valid to invalid time and compare it with the set parking time. If the comparison result is greater than, the target is judged to be far away; otherwise, it is considered that the target has stopped near the buoy and a parking alarm message is given.

[0086] It should be understood that the above-described specific embodiments of the present invention are merely illustrative or illustrative of the principles of the present invention and do not constitute limitations of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included within the scope of protection of the present invention. In addition, the appended claims are intended to cover all variations and modifications that fall within the scope and metes and bounds of the appended claims, or equivalents thereof.

Claims

1. A ship underwater acoustic monitoring method using line spectrum and autocorrelation joint detection, characterized in that: The following steps are involved: S1 signal reception sampling; Sampling the signal received by the hydrophone on the buoy hydroacoustic detection device to obtain a time domain signal; S2 FFT calculation: the signal data is transformed by FFT to obtain the frequency domain signal for subsequent use; S3 target detection based on line spectrum structure; Set the threshold value and count the number of line spectra exceeding the amplitude threshold to confirm whether there is a ship target; S4 autocorrelation calculation; if there is a ship target, prepare to perform autocorrelation calculation on the received signal; S5 target detection and confirmation based on autocorrelation; Set effective threshold value and confirm ship target based on autocorrelation calculation; S6: Target state recognition based on correlation transient changes; by detecting correlation transient changes, it can determine the target's motion state changes, that is, whether the ship is staying near, approaching, or moving away from the submarine pipeline; S7: Adaptive threshold; due to fluctuations in the received signal amplitude, the adaptive threshold setting ensures reliable signal reception and detection; S8 timing control: detects and identifies received signals within a certain period of time, and sends an alarm to the system host if the ship remains near or approaches the sea pipe within a certain period of time; S9 comprehensive judgment communication interaction: It uses line spectrum and autocorrelation methods to comprehensively judge whether there are ships staying near or approaching the sea pipe for a long time, and sends an alarm message to the system host through Beidou communication interaction, while continuing to implement monitoring.

2. The method for ship underwater acoustic monitoring using line spectrum and autocorrelation joint detection according to claim 1, characterized in that: The step S3 includes the following process: S3.1 Set the system operating frequency range based on the spectrum characteristics of the ship's radiated noise and ambient noise, and calculate the amplitude of each line spectrum within the set system operating frequency range; S3.2 Within the effective frequency range, determine whether the amplitude of the line spectrum is greater than the set line spectrum threshold; If the line spectrum amplitude is greater than the threshold, the flag of the corresponding line spectrum is set to valid; otherwise, it is set to invalid; S3.3 Within the target confirmation time, count the cumulative effective time or effective number of each spectrum line, and then determine whether each spectrum line is a valid line spectrum; S3.4 Within the target confirmation time, count the number of valid line spectra and determine whether the number of valid line spectra is greater than the number of line spectra required for target validity; S3.5 If the number of valid spectra is greater than the number of spectra required for the target to be valid, first record the time the target was found and add "1" to the number of consecutive valid target times. Then compare it with the set threshold. If it is greater than the threshold, it is considered that the target was found and the target is set to valid. Otherwise, the number of consecutive valid target times is set to "0", and then further determination is made whether the target is invalid. S3.6 Count the number of invalid line spectra within the target confirmation time, and determine whether the number of invalid line spectra is greater than the number of line spectra required to invalidate the target; S3.7 If the number of invalid lines is greater than the number of lines required to invalidate the target, the number of consecutive target invalidations is incremented by 1; this is then compared with the set threshold; if it is greater, the target is deemed to have been lost and the target is invalidated. If it is not greater than, the number of times the target is continuously invalid is set to "0".

3. The method for ship underwater acoustic monitoring using line spectrum and autocorrelation joint detection according to claim 1, characterized in that: Described step S5 comprises the following process: S5.1 filters or window the FFT output according to the set frequency range; S5.2 selects the relevant data segment for correlation calculation based on the set correlation time and stores the new correlation copy; S5.3 performs low-pass filtering on the relevant output and compares it with the set target effective threshold. If it is greater than the target effective threshold, the process proceeds to step S5.4; if it is not greater than the target effective threshold, the process proceeds to step S5.5; S5.4 first adds "1" to the number of consecutive valid target times, and then compares it with the number of target valid confirmation times. If it is greater, the target status is determined to be valid; otherwise, it directly enters step S5.8 adaptive threshold processing; Step S5.5: First, the number of consecutive valid target times is reset to "0". Then, the correlation output is compared with the target invalid threshold. If the correlation output is greater than the target invalid threshold, the process proceeds to step S5.

6. If not, proceed to step S5.7; S5.6 adds "1" to the number of consecutive target invalid times, and then compares it with the number of target invalid confirmations. If it is greater than this, this moment is recorded as the time when the target is lost, and the process goes to step S5.8 for adaptive threshold processing; Otherwise, directly proceed to step S5.8 adaptive threshold processing; S5.7 The number of consecutive target invalid times is cleared to "0", and then the process proceeds to step S5.8 adaptive threshold processing; S5.8 The target state is not modified, and the process proceeds to adaptive threshold processing.

4. The method for ship underwater acoustic monitoring using line spectrum and autocorrelation joint detection according to claim 3, characterized in that: In step S5.3, the square sum of the correlation outputs is performed once to form a correlation output point; the correlation output is 1024 points.

5. The method for ship underwater acoustic monitoring using line spectrum and autocorrelation joint detection according to claim 1, characterized in that: The step S6 includes the following process: S6.1 If the current target status is valid and the previous target status was valid, record the current time as the target valid time to determine the last time the target was found; S6.2 If the current target status is valid and the previous target status was invalid, record the current time as the time when the target was first discovered; S6.3 If the current target status is invalid and the previous target status is invalid, return directly; S6.4 If the current target status is invalid and the previous target status is valid, first record the current time as the time when the target is lost in order to determine whether the target is stopped or moved away; then calculate the transition time from the last valid to invalid time and compare it with the set stop time. If it is greater, the target is judged to be far away; otherwise, it is considered that the target has stopped near the buoy and a stop alarm message is given.

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