A ship safety monitoring system and method with Beidou positioning function

Abstract

The present invention relates to the field of ship positioning, and in particular to a ship safety monitoring system and method with Beidou positioning function. It includes: at every preset detection interval, the acceleration subsequence and angular velocity subsequence in the inertial navigation initial positioning information acquisition sequence are respectively subjected to positioning sequence autocorrelation detection processing to generate abnormal values; if there is any abnormal value less than the abnormal threshold, the inertial navigation system is subjected to positioning correction processing to generate the azimuth information and attitude information corresponding to the ship, and the ship is safely monitored. The abnormal values ​​corresponding to the acceleration subsequence and the abnormal values ​​corresponding to the angular velocity subsequence are generated by the above-mentioned characteristics, and the threshold comparison can be used to determine whether there is random noise in the sequence to be detected, and the correction processing of the inertial navigation positioning information is triggered by this, thereby ensuring the accuracy of the inertial navigation positioning information, and finally ensuring the normal operation of the ship safety monitoring function based on the positioning information and / or attitude information.

Description

Background Art

[0002] Ship safety monitoring is a complex and multi-dimensional process, covering many aspects from navigation safety, equipment status monitoring to environmental perception. In order to ensure the safe operation of ships under various conditions, modern ships are equipped with a variety of advanced monitoring systems and technologies, such as Electronic Chart Display and Information System (ECDIS), Automatic Identification System (AIS), Integrated Navigation System (INS) and equipment status monitoring system.

[0003] Among them, the integrated navigation system is a navigation technology that integrates data from multiple navigation sensors and systems to improve navigation accuracy, reliability and robustness. By combining different types of sensors (such as satellite navigation systems, inertial navigation systems (INS), geomagnetic sensors and visual sensors, etc.), it is possible to overcome the limitations of a single sensor and provide more accurate, continuous and reliable navigation information. Common integrated navigation methods are satellite navigation systems (such as GPS, GLONASS, Galileo and Beidou, etc.) plus inertial navigation systems. In this combination, although the satellite navigation system can provide high-precision global positioning services through navigation satellites, it is easily affected by signal shielding, multipath effects and external interference, and the positioning accuracy is reduced in some areas. Although the inertial navigation system can provide high-precision autonomous navigation in a short period of time through devices such as accelerometers and gyroscopes, and is not easily affected by external factors, the accuracy will decrease due to the accumulation of sensor errors during long-term use. Therefore, in order to overcome the above problems, in the existing integrated navigation system, it is usually necessary to turn on both navigation methods so that when one of the navigation methods has problems, another method can be used to continue navigation. At the same time, in order to improve the accuracy of navigation, it is also necessary to regularly use more accurate satellite positioning information to correct the positioning information of the inertial navigation system.

[0004] However, in actual use, since ships are affected by external factors such as waves, wind, engine vibration and complex electromagnetic environment at sea during navigation, it is easy for the sensors in the inertial navigation system to have random noise due to internal electronic noise, mechanical vibration and other factors, which in turn causes random errors in the collected positioning information. As a result, during the correction interval, the inertial navigation system may significantly reduce the accuracy of the inertial navigation positioning information due to the random noise that occurs. That is, the existing regular correction method cannot perform adaptive correction according to the error of the inertial navigation system in a timely manner, so that the accuracy of the inertial navigation positioning information during the correction interval cannot be guaranteed, which will affect the normal operation of the ship safety monitoring function based on positioning information and / or attitude information. Summary of the invention

[0005] In view of the above technical problems, the technical solution adopted by the present invention is:

[0006] According to one aspect of the present invention, a safety monitoring method for a ship with Beidou positioning function is provided, the method comprising the following steps:

[0007] At every preset detection interval, the acceleration subsequence and the angular velocity subsequence in the inertial navigation initial positioning information acquisition sequence are respectively subjected to positioning sequence autocorrelation detection processing to generate abnormal values ​​corresponding to the acceleration subsequence and the angular velocity subsequence respectively; the time length of the preset detection interval is less than the time length of the preset inertial navigation correction cycle;

[0008] If there is any abnormal value less than the abnormal threshold, the Beidou navigation information is used to perform positioning correction processing on the inertial navigation system to generate the corresponding orientation information and attitude information of the ship;

[0009] Conduct safety monitoring of the ship based on the ship's corresponding position information and attitude information;

[0010] The positioning sequence autocorrelation detection process includes:

[0011] intercepting the sequence to be detected corresponding to the acceleration subsequence or the angular velocity subsequence in the current detection interval;

[0012] The autocorrelation detection values ​​at different time lag steps in the sequence to be detected are obtained respectively; wherein the autocorrelation detection value R(i) at time lag step i satisfies the following conditions:

[0013] ;

[0014] Among them, μ is the mean of the samples collected in the sequence to be detected, x t is the tth sample value in the sequence to be detected, z is the total number of samples collected in the sequence to be detected, and i is a positive integer between 1 and z-1;

[0015] According to the autocorrelation detection value sequences corresponding to the acceleration subsequence and the angular velocity subsequence, the abnormal value P corresponding to the acceleration subsequence is generated respectively. v and the outlier value P corresponding to the angular velocity subsequence w ; Among them, P v and P w The following conditions are met respectively:

[0016] ;

[0017] Among them, vR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the acceleration subsequence, Avg(vR 0 ) is the autocorrelation detection value sequence corresponding to the acceleration subsequence vR0 The mean of the autocorrelation detection values ​​in the previous sequence; wR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the angular velocity subsequence, Avg(wR 0 ) is the autocorrelation detection value sequence corresponding to the angular velocity subsequence wR 0 The mean of the autocorrelation test values ​​in the previous series.

[0018] According to a second aspect of the present invention, there is also provided a ship safety monitoring system with Beidou positioning function, the system comprising:

[0019] The autocorrelation detection module is used to perform positioning sequence autocorrelation detection processing on the acceleration subsequence and angular velocity subsequence in the inertial navigation initial positioning information acquisition sequence at every preset detection interval, and generate abnormal values ​​corresponding to the acceleration subsequence and the angular velocity subsequence respectively; the time length of the preset detection interval is less than the time length of the preset inertial navigation correction cycle;

[0020] The correction trigger module is used to use Beidou navigation information to perform positioning correction processing on the inertial navigation system if any abnormal value is less than the abnormal threshold, and generate the corresponding orientation information and attitude information of the ship;

[0021] The ship safety monitoring module is used to monitor the safety of the ship according to the corresponding position information and attitude information of the ship;

[0022] The positioning sequence autocorrelation detection process includes:

[0023] intercepting the sequence to be detected corresponding to the acceleration subsequence or the angular velocity subsequence in the current detection interval;

[0024] The autocorrelation detection values ​​at different time lag steps in the sequence to be detected are obtained respectively; wherein the autocorrelation detection value R(i) at time lag step i satisfies the following conditions:

[0025] ;

[0026] Among them, μ is the mean of the samples collected in the sequence to be detected, x t is the tth sample value in the sequence to be detected, z is the total number of samples collected in the sequence to be detected, and i is a positive integer between 1 and z-1;

[0027] According to the autocorrelation detection value sequences corresponding to the acceleration subsequence and the angular velocity subsequence, the abnormal value P corresponding to the acceleration subsequence is generated respectively. v and the outlier value P corresponding to the angular velocity subsequence w ; Among them, P v and P w The following conditions are met respectively:

[0028] ;

[0029] Among them, vR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the acceleration subsequence, Avg(vR 0 ) is the autocorrelation detection value sequence corresponding to the acceleration subsequence vR 0 The mean of the autocorrelation detection values ​​in the previous sequence; wR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the angular velocity subsequence, Avg(wR 0 ) is the autocorrelation detection value sequence corresponding to the angular velocity subsequence wR 0 The mean of the autocorrelation test values ​​in the previous series.

[0030] The present invention has at least the following beneficial effects:

[0031] Since the sensor data acquisition frequency in the inertial navigation system is relatively high (usually 50Hz to 100Hz), and the appearance of random noise is usually short-lived and is an instantaneous phenomenon (such as between 1-3 seconds). Therefore, the sequence corresponding to the random noise in the collected acceleration subsequence and angular velocity subsequence is only a small continuous sequence. Based on this, the present invention also has a smaller detection interval in the preset inertial navigation correction cycle, so that the inertial navigation information sequence collected in an entire inertial navigation correction cycle can be divided into more fine-grained detection segments, and then the sequence corresponding to the random noise can be better divided.

[0032] In addition, the physical quantities measured by the sensors of the inertial navigation system (such as accelerometers and gyroscopes) under normal conditions should be continuous signals (such as linear acceleration and angular velocity) related to the actual movement of the ship, rather than random sequences. The random noise of the sensors of the inertial navigation system does not represent any physical quantity, and the various noise data are independent of each other and have no correlation. Based on this, an autocorrelation function can be used to perform autocorrelation detection on the sequence to be detected corresponding to the acceleration subsequence or angular velocity subsequence. Since the random noise sequence is relative to the normal sequence, when the time lag step is not equal to 0, the autocorrelation detection value should be close to 0 and fluctuate randomly around zero, and as the time lag step increases, the autocorrelation detection value rapidly decays to zero. The present invention generates an abnormal value P corresponding to the acceleration subsequence through the above-mentioned characteristics. v and the outlier value P corresponding to the angular velocity subsequence w By comparing the threshold, it can be determined whether there is random noise in the sequence to be detected, and this can trigger the correction processing of the inertial navigation positioning information, thereby ensuring the accuracy of the inertial navigation positioning information, and ultimately ensuring the normal operation of the ship safety monitoring function based on positioning information and / or attitude information. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0034] Figure 1 A flow chart of a safety monitoring method for ships with Beidou positioning function provided by an embodiment of the present invention.

[0035] Figure 2 A structural block diagram of a ship safety monitoring system with Beidou positioning function provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0037] As a possible embodiment of the present invention, Figure 1 As shown, a safety monitoring method for ships with Beidou positioning function is provided, the method comprising the following steps:

[0038] S100: Obtain the Beidou navigation information collection sequence of the ship in the current preset inertial navigation correction cycle. The Beidou navigation information collection sequence includes the positioning information of the ship acquired in sequence at multiple collection moments. The positioning information includes the latitude and longitude information, speed information and heading angle of the ship.

[0039] The preset inertial navigation correction period in this embodiment usually needs to be set according to the performance of the inertial navigation system, specifically, it is determined according to the speed of sensor error accumulation in the inertial navigation system and the movement speed of the ship, and is usually 10 to 200 seconds.

[0040] The Beidou navigation information collection sequence uses a receiver to receive Beidou positioning information, and then obtains it through solution. Professional Beidou receivers commonly used in aviation, navigation, high-precision measurement and other fields have a high information collection frequency and can obtain more satellite signals in a short time, thereby improving positioning accuracy and reliability. The collection frequency of such terminals is usually between 1Hz and 10Hz, or even higher. The Beidou navigation information collection sequence in this embodiment can be a sequence formed by the positioning information output by the Beidou receiver, or it can be a sequence formed by the positioning information received by the Beidou receiver.

[0041] S200: Acquire the inertial navigation initial positioning information acquisition sequence of the ship in the current preset inertial navigation correction cycle. The inertial navigation initial positioning information acquisition sequence includes the acceleration information and angular velocity information of the ship acquired in sequence at multiple acquisition moments. The data acquisition frequency corresponding to the Beidou navigation information acquisition sequence is less than the data acquisition frequency corresponding to the inertial navigation initial positioning information acquisition sequence.

[0042] According to the motion characteristics of the ship (slow-speed motion) and the application (integral calculation) requirements of the inertial navigation system, the data acquisition frequency of the ship's inertial navigation system is usually: 50 Hz to 200 Hz. This data acquisition frequency range is suitable for most civilian ships and commercial ships. Within this frequency range, the system can effectively capture the movement changes of the ship while maintaining a low computational burden and power consumption.

[0043] S300: performing positioning sequence autocorrelation detection processing on the acceleration subsequence and the angular velocity subsequence in the inertial navigation initial positioning information acquisition sequence at every preset detection interval, and generating abnormal values ​​corresponding to the acceleration subsequence and the angular velocity subsequence respectively.

[0044] The length of the preset detection interval is shorter than the length of the preset inertial navigation correction cycle. Specifically, the length can be determined according to actual needs, such as 1-2 seconds. Usually, the sequence generated by random noise is generally shorter, about 1 to 3 seconds, so this can also be used as a reference when setting.

[0045] The positioning sequence autocorrelation detection process includes:

[0046] S301: intercepting a sequence to be detected corresponding to an acceleration subsequence or an angular velocity subsequence in a current detection interval.

[0047] The corresponding sequence to be detected in this embodiment is the collection sequence generated in the current detection interval, which is the latest information generated, similar to using a sliding window determined by the detection interval to intercept the sequence to be detected. According to the data acquisition frequency of the above-mentioned inertial navigation system, it can be known that there are usually 50 to 400 sensor collection values ​​in the sequence to be detected. Since the inertial navigation system mainly includes accelerometers and gyroscopes, the corresponding collected information sequences are acceleration subsequences and angular velocity subsequences. Both sequences can use S302 to S303 in this embodiment to calculate the abnormal values ​​corresponding to the corresponding sequence to be detected, and the abnormal values ​​are used to determine whether there is a large amount of random noise in the current sequence to be detected.

[0048] S302: Obtain the autocorrelation detection values ​​at different time lag steps in the sequence to be detected respectively. The autocorrelation detection value R(i) at time lag step i satisfies the following conditions:

[0049] .

[0050] Among them, μ is the mean of the samples collected in the sequence to be detected, x t is the tth sample value in the sequence to be detected, z is the total number of samples collected in the sequence to be detected, and i is a positive integer between 1 and z-1. Specifically, if there is a large amount of random noise in the sequence to be detected, then the autocorrelation detection value at different time lag steps i is expressed as follows: when the time lag step is not equal to 0, the autocorrelation detection value should be close to 0, and fluctuate randomly around zero, and as the time lag step increases, the autocorrelation detection value decays rapidly to zero. Since the autocorrelation detection value decays rapidly to zero as the time lag step increases, the value of i can be reduced to all integers in the range of 1 to 10 in actual calculations.

[0051] In this step, during the calculation, the collected sample values ​​are subjected to mean removal processing, that is, the mean of the sequence is subtracted from each data point. The autocorrelation function after removing the mean can better reflect the volatility characteristics of the collected data rather than the overall level of the collected data, so as to eliminate trends or biases and help focus on the volatility characteristics of the data.

[0052] In this embodiment, R(i)∈[-1,1]. If R(i) is close to 1 or -1, it means that the sequence has a strong positive or negative correlation at lag i. If R(i) is close to 0, it means that the sequence has almost no correlation at lag i.

[0053] S303: Generate the abnormal value P corresponding to the acceleration subsequence according to the autocorrelation detection value sequence corresponding to the acceleration subsequence and the angular velocity subsequence respectively. v and the outlier value P corresponding to the angular velocity subsequence w Among them, Pv and P w The following conditions are met respectively:

[0054] .

[0055] Among them, vR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the acceleration subsequence, Avg(vR 0 ) is the autocorrelation detection value sequence corresponding to the acceleration subsequence vR 0 The mean of the autocorrelation detection values ​​in the previous sequence. wR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the angular velocity subsequence, Avg(wR 0 ) is the autocorrelation detection value sequence corresponding to the angular velocity subsequence wR 0 The mean of the autocorrelation test values ​​in the previous series.

[0056] Because the physical quantities measured by the sensors of the inertial navigation system (such as accelerometers and gyroscopes) under normal circumstances should be continuous signals related to the actual movement of the ship (such as linear acceleration and angular velocity), rather than random sequences. The random noise of the sensors of the inertial navigation system does not represent any physical quantity, and each noise data is independent of each other and has no correlation, that is, white noise. Based on this, an autocorrelation function can be used to perform autocorrelation detection on the sequence to be detected corresponding to the acceleration subsequence or angular velocity subsequence. Since the random noise sequence is relative to the normal sequence, when the time lag step is not equal to 0, the autocorrelation detection value should be close to 0, and fluctuate randomly around zero, and as the time lag step increases, the autocorrelation detection value rapidly decays to zero. The present invention generates an abnormal value P corresponding to the acceleration subsequence through the above-mentioned characteristics. v and the outlier value P corresponding to the angular velocity subsequence w By comparing the threshold, it can be determined whether there is random noise in the sequence to be detected, and this can trigger the correction processing of the inertial navigation positioning information, thereby ensuring the accuracy of the inertial navigation positioning information, and ultimately ensuring the normal operation of the ship safety monitoring function based on positioning information and / or attitude information.

[0057] S400: If there is any abnormal value that is smaller than the abnormal threshold, the Beidou navigation information is used to perform positioning correction processing on the inertial navigation system to generate the corresponding orientation information and attitude information of the ship.

[0058] Due to the characteristics of random noise at different time steps, the time lag step size when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence can indicate how fast the autocorrelation detection value decays to zero. 0 or wR 0The mean of the autocorrelation detection values ​​in the previous sequence can indicate whether the autocorrelation detection value is close to 0 and the magnitude of the fluctuation.

[0059] In addition, since random noise has another characteristic that when the time lag step is 0, the corresponding autocorrelation detection value R(0)=1, which means that the sequence is completely correlated with itself, in order to further improve the accuracy of the judgment, a judgment condition for judging whether R(0) is 1 can be added in S400.

[0060] The abnormal threshold is obtained according to the following steps:

[0061] S401: Acquire a normal sequence to be detected in acceleration subsequences and angular velocity subsequences corresponding to a plurality of historical detection intervals.

[0062] S402: performing autocorrelation detection processing on a plurality of normal sequences to be detected corresponding to the acceleration subsequence or the angular velocity subsequence, respectively, to generate a plurality of abnormal values.

[0063] S403: Taking the mean of the multiple abnormal values ​​as the corresponding abnormal threshold.

[0064] S403 includes:

[0065] S413: The average of the multiple abnormal values ​​generated corresponding to the acceleration subsequence is used as P v The corresponding abnormal threshold.

[0066] S423: The average of the multiple abnormal values ​​generated corresponding to the angular velocity subsequence is used as P v The corresponding abnormal threshold.

[0067] S500: Perform safety monitoring on the ship according to the corresponding position information and attitude information of the ship.

[0068] In this embodiment, the ship's position information may include longitude, latitude, and altitude, and the attitude information may include heading, pitch angle, roll angle, etc. After obtaining the above information, it can be applied in various ways in ship safety monitoring, real-time warning, and accident response.

[0069] Specifically, it can include the following aspects of security monitoring:

[0070] Navigation status monitoring: By continuously receiving the ship's position and attitude data, the ship's navigation status can be understood in real time, including whether it deviates from the scheduled route, whether there is abnormal tilt or shaking, etc.

[0071] Speed ​​and direction control: Based on the ship's speed and heading information, ensure that it travels according to the planned speed and path to avoid speeding or entering dangerous areas.

[0072] Equipment health monitoring: Combined with posture information, the working status of ship mechanical equipment, such as propellers and steering gear, can be evaluated to prevent safety hazards caused by mechanical failures.

[0073] Collision Warning: Uses Automatic Identification System (AIS), radar and other sensors to detect the position of surrounding vessels and predict potential collision risks. If a collision is detected, an alarm is immediately issued to the crew.

[0074] Tilt Angle Exceeding Limit Alarm: When the ship’s roll angle or pitch angle exceeds the safety threshold, the system will trigger an alarm to alert the crew and take corrective action.

[0075] After using Beidou navigation information to correct the positioning of the inertial navigation system, more accurate ship position information and attitude information can be obtained, and safety monitoring can be performed based on this, thereby improving accuracy. In the present invention, the correction processing of the inertial navigation positioning information is triggered by comparing the abnormal value with the threshold, thereby ensuring the accuracy of the inertial navigation positioning information, and ultimately ensuring the normal operation of the ship safety monitoring function based on the positioning information and / or attitude information.

[0076] As another embodiment of the present invention, the method further includes:

[0077] S600: If the abnormal values ​​corresponding to all detection intervals in any INS correction cycle are greater than or equal to the abnormal threshold, the INS initial positioning information acquisition sequence is integrated to obtain the INS verification navigation information acquisition sequence of the ship in the current preset INS correction cycle. The INS verification navigation information acquisition sequence includes the INS longitude and latitude information and the INS speed information corresponding to multiple acquisition moments. The acquisition moment of the INS verification navigation information acquisition sequence is the same as that of the Beidou navigation information acquisition sequence.

[0078] S700: If the latitude and longitude variance value and / or speed variance value in the inertial navigation verification navigation information collection sequence and the Beidou navigation information collection sequence is greater than a preset variance threshold, an abnormal alarm message of Beidou navigation is generated.

[0079] Specifically, the latitude and longitude variance value F jw The following conditions must be met:

[0080] .

[0081] Among them, J m g and W m g are the inertial navigation longitude and latitude information corresponding to the mth acquisition moment in the inertial navigation verification navigation information acquisition sequence. m b and W m bThey are the latitude and longitude information corresponding to the mth acquisition time in the Beidou navigation information acquisition sequence. n is the number of acquisition times in the inertial navigation verification navigation information acquisition sequence.

[0082] The inertial navigation verification navigation information acquisition sequence also includes inertial navigation heading angle information corresponding to multiple acquisition moments.

[0083] After acquiring the inertial navigation verification navigation information acquisition sequence of the ship in the current preset inertial navigation correction cycle, the method further includes:

[0084] S800: If the heading angle variance value in the inertial navigation verification navigation information collection sequence and the Beidou navigation information collection sequence is greater than a preset variance threshold, an abnormal alarm message of Beidou navigation is generated.

[0085] In this embodiment, inertial navigation information can be used to determine whether the Beidou navigation information is accurate. In some complex environments, the accuracy of the received Beidou positioning information may be reduced due to the influence of factors such as electromagnetic environment, multipath effect, atmospheric delay, signal shielding or deception. The inertial navigation system is usually not affected by the above factors. Therefore, in this embodiment, as long as the abnormal values ​​corresponding to all detection intervals in a whole inertial navigation correction cycle are greater than or equal to the abnormal threshold, that is, the inertial navigation system is not affected by random noise, the inertial navigation positioning information can be used to reversely check whether the Beidou positioning information is abnormal. In this way, the positioning accuracy of the entire combined navigation system can be further improved, and the robustness of the system can be improved.

[0086] As another embodiment of the present invention, Figure 2 As shown, a ship safety monitoring system with Beidou positioning function is also provided, and the system includes:

[0087] The autocorrelation detection module is used to perform positioning sequence autocorrelation detection processing on the acceleration subsequence and angular velocity subsequence in the inertial navigation initial positioning information acquisition sequence at every preset detection interval, and generate abnormal values ​​corresponding to the acceleration subsequence and angular velocity subsequence respectively. The time length of the preset detection interval is less than the time length of the preset inertial navigation correction cycle.

[0088] The correction trigger module is used to use the Beidou navigation information to perform positioning correction processing on the inertial navigation system if there is any abnormal value less than the abnormal threshold, and generate the corresponding azimuth information and attitude information of the ship.

[0089] The ship safety monitoring module is used to monitor the safety of the ship based on the corresponding position information and posture information of the ship.

[0090] The positioning sequence autocorrelation detection process includes:

[0091] The sequence to be detected corresponding to the acceleration subsequence or angular velocity subsequence in the current detection interval is intercepted.

[0092] The autocorrelation detection values ​​at different time lag steps in the sequence to be detected are obtained respectively. Among them, the autocorrelation detection value R(i) at time lag step i satisfies the following conditions:

[0093] .

[0094] Among them, μ is the mean of the samples collected in the sequence to be detected, x t is the tth sample value in the sequence to be detected, z is the total number of samples collected in the sequence to be detected, and i is a positive integer between 1 and z-1.

[0095] According to the autocorrelation detection value sequences corresponding to the acceleration subsequence and the angular velocity subsequence, the abnormal value P corresponding to the acceleration subsequence is generated respectively. v and the outlier value P corresponding to the angular velocity subsequence w Among them, P v and P w The following conditions are met respectively:

[0096] .

[0097] Among them, vR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the acceleration subsequence, Avg(vR 0 ) is the autocorrelation detection value sequence corresponding to the acceleration subsequence vR 0 The mean of the autocorrelation detection values ​​in the previous sequence. wR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the angular velocity subsequence, Avg(wR 0 ) is the autocorrelation detection value sequence corresponding to the angular velocity subsequence wR 0 The mean of the autocorrelation test values ​​in the previous series.

[0098] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0099] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0100] In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0101] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as a system, method or program product. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as a "circuit", "module" or "system".

[0102] The electronic device according to this embodiment of the present invention is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0103] The electronic device is presented in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: the at least one processor mentioned above, the at least one storage device mentioned above, and a bus connecting different system components (including storage devices and processors).

[0104] The storage stores program codes, which can be executed by the processor, so that the processor executes the steps according to various exemplary embodiments of the present invention described in the above “Exemplary Method” section of this specification.

[0105] The memory may include readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory, and may further include read only memory (ROM).

[0106] The storage may also include a program / utility having a set (at least one) of program modules, such program modules including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0107] The bus may represent one or more of several types of bus structures including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.

[0108] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may communicate with one or more devices that enable a user to interact with the electronic device, and / or may communicate with any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication may be performed through an input / output (I / O) interface. In addition, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter. The network adapter communicates with other modules of the electronic device through a bus. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0109] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0110] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present invention may also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present specification.

[0111] The program product may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0112] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0113] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0114] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0115] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0116] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0117] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A safety monitoring method for ships with Beidou positioning function, characterized in that: The method comprises the following steps: At every preset detection interval, the acceleration subsequence and the angular velocity subsequence in the inertial navigation initial positioning information acquisition sequence are respectively subjected to positioning sequence autocorrelation detection processing to generate abnormal values ​​corresponding to the acceleration subsequence and the angular velocity subsequence respectively; the time length of the preset detection interval is less than the time length of the preset inertial navigation correction cycle; If there is any abnormal value less than the abnormal threshold, and when the time lag step is 0, the corresponding autocorrelation detection value R(0)=1, the Beidou navigation information is used to perform positioning correction processing on the inertial navigation system to generate the corresponding azimuth information and attitude information of the ship; Performing safety monitoring on the ship according to the position information and attitude information corresponding to the ship; The positioning sequence autocorrelation detection process comprises: intercepting a sequence to be detected corresponding to the acceleration subsequence or angular velocity subsequence in a current detection interval; The autocorrelation detection values ​​at different time lag steps in the sequence to be detected are obtained respectively; wherein the autocorrelation detection value R(i) at time lag step i satisfies the following conditions: ； Among them, μ is the mean of the samples collected in the sequence to be detected, x t is the tth sample value in the sequence to be detected, z is the total number of samples collected in the sequence to be detected, and i is a positive integer between 1 and z-1; According to the autocorrelation detection value sequences corresponding to the acceleration subsequence and the angular velocity subsequence, respectively, the abnormal value P corresponding to the acceleration subsequence is generated. v and the abnormal value P corresponding to the angular velocity subsequence w ; Among them, P v and P w The following conditions are met respectively: ； Among them, vR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the acceleration subsequence, Avg(vR 0 ) is the vR in the autocorrelation detection value sequence corresponding to the acceleration subsequence 0 The mean of the autocorrelation detection values ​​in the previous sequence; wR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the angular velocity subsequence, Avg(wR 0 ) is the autocorrelation detection value sequence corresponding to the angular velocity subsequence wR 0 The mean of the autocorrelation test values ​​in the previous series.

2. The method according to claim 1, characterized in that Before performing positioning sequence autocorrelation detection processing on the acceleration subsequence and the angular velocity subsequence in the inertial navigation initial positioning information acquisition sequence, the method further includes: Acquire a Beidou navigation information acquisition sequence of a ship in a current preset inertial navigation correction cycle; the Beidou navigation information acquisition sequence includes positioning information of the ship acquired sequentially at multiple acquisition moments; An inertial navigation initial positioning information acquisition sequence of the ship in the current preset inertial navigation correction cycle is obtained; the inertial navigation initial positioning information acquisition sequence includes acceleration information and angular velocity information of the ship sequentially acquired at multiple acquisition moments.

3. The method according to claim 2, characterized in that The positioning information includes the latitude and longitude information, speed information and heading angle of the ship.

4. The method according to claim 1, characterized in that: The abnormal threshold is obtained according to the following steps: Obtain normal sequences to be detected in acceleration subsequences and angular velocity subsequences corresponding to multiple historical detection intervals; Performing autocorrelation detection processing on a plurality of normal sequences to be detected corresponding to the acceleration subsequence or the angular velocity subsequence, respectively, to generate a plurality of abnormal values; The mean of multiple outliers is used as the corresponding outlier threshold.

5. The method according to claim 4, characterized in that The mean of multiple outliers is used as the corresponding outlier threshold, including: The mean of multiple abnormal values ​​generated corresponding to the acceleration subsequence is taken as P v The corresponding abnormal threshold; The mean of the multiple outliers generated corresponding to the angular velocity subsequence is taken as P v The corresponding abnormal threshold.

6. The method according to claim 3, characterized in that The method further comprises: If the abnormal values ​​corresponding to all detection intervals in any inertial navigation correction cycle are greater than or equal to the abnormal threshold, the inertial navigation initial positioning information acquisition sequence is integrated to obtain the inertial navigation verification navigation information acquisition sequence of the ship in the current preset inertial navigation correction cycle; the inertial navigation verification navigation information acquisition sequence includes inertial navigation longitude and latitude information and inertial navigation speed information corresponding to multiple acquisition moments respectively; the acquisition time of the inertial navigation verification navigation information acquisition sequence is the same as that of the Beidou navigation information acquisition sequence; If the latitude and longitude variance value and / or speed variance value in the inertial navigation verification navigation information collection sequence and the Beidou navigation information collection sequence is greater than the preset variance threshold, an abnormal alarm message of Beidou navigation is generated.

7. The method according to claim 6, characterized in that The latitude and longitude variance value F jw The following conditions must be met: ； Among them, J m g and W m g are the inertial navigation longitude and latitude information corresponding to the mth acquisition moment in the inertial navigation verification navigation information acquisition sequence; J m b and W m b They are the latitude and longitude information corresponding to the mth collection moment in the Beidou navigation information collection sequence; n is the number of collection moments in the inertial navigation verification navigation information collection sequence.

8. The method according to claim 6, characterized in that The inertial navigation verification navigation information acquisition sequence also includes inertial navigation heading angle information corresponding to a plurality of acquisition moments respectively; After acquiring the inertial navigation verification navigation information acquisition sequence of the ship in the current preset inertial navigation correction cycle, the method further includes: If the heading angle variance value in the inertial navigation verification navigation information collection sequence and the Beidou navigation information collection sequence is greater than the preset variance threshold, an abnormal alarm message of Beidou navigation is generated.

9. The method according to claim 2, characterized in that: The data collection frequency corresponding to the Beidou navigation information collection sequence is less than the data collection frequency corresponding to the inertial navigation initial positioning information collection sequence.

10. A ship safety monitoring system with Beidou positioning function, characterized in that: The system comprises: An autocorrelation detection module is used to perform positioning sequence autocorrelation detection processing on the acceleration subsequence and the angular velocity subsequence in the inertial navigation initial positioning information acquisition sequence at every preset detection interval, and generate abnormal values ​​corresponding to the acceleration subsequence and the angular velocity subsequence respectively; the time length of the preset detection interval is less than the time length of the preset inertial navigation correction cycle; A correction trigger module is used to use Beidou navigation information to perform positioning correction processing on the inertial navigation system to generate the azimuth information and attitude information corresponding to the ship if there is any abnormal value less than the abnormal threshold and when the time lag step is 0, the corresponding autocorrelation detection value R(0)=1; A ship safety monitoring module, used to perform safety monitoring on the ship according to the position information and attitude information corresponding to the ship; The positioning sequence autocorrelation detection process comprises: intercepting a sequence to be detected corresponding to the acceleration subsequence or angular velocity subsequence in a current detection interval; The autocorrelation detection values ​​at different time lag steps in the sequence to be detected are obtained respectively; wherein the autocorrelation detection value R(i) at time lag step i satisfies the following conditions: ； Among them, μ is the mean of the samples collected in the sequence to be detected, x t is the tth sample value in the sequence to be detected, z is the total number of samples collected in the sequence to be detected, and i is a positive integer between 1 and z-1; According to the autocorrelation detection value sequences corresponding to the acceleration subsequence and the angular velocity subsequence, respectively, the abnormal value P corresponding to the acceleration subsequence is generated. v and the abnormal value P corresponding to the angular velocity subsequence w ; Among them, P v and P w The following conditions are met respectively: ； Among them, vR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the acceleration subsequence, Avg(vR 0 ) is the vR in the autocorrelation detection value sequence corresponding to the acceleration subsequence 0 The mean of the autocorrelation detection values ​​in the previous sequence; wR 0 is the time lag step when the autocorrelation detection value is reduced to 0 in the autocorrelation detection value sequence corresponding to the angular velocity subsequence, Avg(wR 0 ) is the autocorrelation detection value sequence corresponding to the angular velocity subsequence wR 0 The mean of the autocorrelation test values ​​in the previous series.

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