A high-precision mobile target monitoring method based on static and dynamic clustering

Abstract

The present invention belongs to the technical field of computer Internet of Things. The present invention provides a high-precision mobile target monitoring method based on static and dynamic combined clustering, including: when a large correlation degree signal is generated, a monitoring correlation coefficient is obtained, all monitoring correlation coefficients are added and averaged to obtain a range adjustment coefficient, and a monitoring range TZ in a required monitoring area is calculated by a formula, and the monitoring range of the monitoring node in the monitoring area is adjusted, so that the monitoring range in the monitoring area is dynamically adjusted by real-time monitoring of the mobile target speed, thereby solving the problem of low monitoring and positioning accuracy of the mobile target in the monitoring area due to its speed.

Description

Technical Field

[0001] The invention belongs to the technical field of computer Internet of Things, and specifically is a high-precision mobile target monitoring method based on static and dynamic combined clustering. Background Art

[0002] By combining the stability of static clustering and the flexibility of dynamic clustering, building a reasonable network topology, and adopting advanced signal processing and data analysis technologies, real-time monitoring and precise positioning of mobile targets can be achieved.

[0003] In the prior art, usually only static clustering or dynamic clustering is used for single monitoring, which has certain limitations. Therefore, in the present application, first, a monitoring accuracy value is obtained, and the monitoring accuracy value is compared with the monitoring accuracy threshold to determine whether the position of the monitored mobile target in the monitoring area is accurate. Then, a monitoring correlation value is obtained, and the monitoring correlation value is compared with the monitoring correlation threshold. The reason affecting the positioning accuracy of the mobile target is further analyzed, which is the speed of the mobile target. The range adjustment coefficient is obtained to adjust the monitoring range in the monitoring area to solve the problem of low monitoring and positioning accuracy of the mobile target caused by its speed in the monitoring area.

[0004] To this end, the present invention provides a high-precision mobile target monitoring method based on static and dynamic combined clustering. Summary of the invention

[0005] In order to make up for the shortcomings of the prior art, the problem of low monitoring and positioning accuracy of moving targets in the monitoring area due to their speed proposed in the background technology is solved.

[0006] The technical solution adopted by the present invention to solve the technical problem is: a high-precision mobile target monitoring method based on static and dynamic combined clustering, comprising:

[0007] Step 1: Monitor the target moving area in real time and mark the target moving area as a monitoring area. In the monitoring area, a static cluster monitoring network is constructed, wherein the static cluster monitoring network includes a plurality of wireless sensor nodes, and the wireless sensor nodes are evenly distributed in the monitoring area.

[0008] Step 2: Based on the static cluster monitoring network in the monitoring area, a monitoring period is set, and within the monitoring period, target monitoring data is obtained, wherein the target monitoring data includes target coordinates, all target coordinates are connected with a smooth curve to obtain a target closed graph, and the target range area ratio and the target range perimeter ratio of the target closed graph are obtained to obtain the monitoring accuracy value;

[0009] Step 3: When the target coordinate range area is obtained, the monitoring accuracy value is compared with the monitoring accuracy threshold. If the monitoring accuracy value is greater than the monitoring accuracy threshold, a low mobile target positioning accuracy signal is generated;

[0010] Step 4: Based on the low signal of the moving target positioning accuracy, the monitoring deviation coefficient and the moving target speed coefficient are obtained, and the correlation between the monitoring deviation coefficient and the moving target speed coefficient is analyzed to obtain a monitoring correlation value, which is compared with the threshold. If the monitoring correlation value is less than or equal to the monitoring correlation threshold, a large signal of the monitoring correlation degree is generated;

[0011] Step 5: When a large correlation signal is generated, the range adjustment coefficient is obtained to complete the dynamic adjustment of the monitoring range within the monitoring area.

[0012] A further solution of the present invention: the monitoring accuracy value is obtained by:

[0013] Obtain the target range area ratio and target range perimeter ratio of the target closed figure, and substitute the target range area ratio and target range perimeter ratio into the formula: JC m =V m ×α+C m ×β, calculate the moving target monitoring value JC m , where V m Expressed as the target range area ratio, C m It is expressed as the target range perimeter ratio, and α and β are weight coefficients;

[0014] All the moving target monitoring values ​​are added and averaged to obtain the monitoring accuracy value.

[0015] A further solution of the present invention: the target coordinates are obtained as follows:

[0016] In the monitoring area, each wireless sensor node in the static cluster monitoring network is marked as a monitoring node;

[0017] Based on the monitoring nodes, each monitoring node in the static cluster monitoring network is taken as the monitoring origin, and the monitoring origin is taken as the origin of the coordinate system to obtain the monitoring coordinate system;

[0018] During the monitoring period, the monitoring period is divided into a number of monitoring time periods at equal time intervals;

[0019] During the monitoring period, the target coordinates in each monitoring coordinate system are obtained, and all target coordinates are integrated to obtain a target coordinate set P = {p1, p2, p3, ..., p n}.

[0020] A further solution of the present invention is to obtain the monitoring correlation value by:

[0021] All monitoring correlation coefficients are subjected to variance calculation to obtain monitoring correlation values.

[0022] A further solution of the present invention is to obtain the monitoring correlation coefficient by:

[0023] The monitoring deviation coefficient and the moving target speed coefficient are obtained, and the monitoring deviation coefficient in each monitoring time period is calculated by ratio with the corresponding moving target speed coefficient to obtain the monitoring correlation coefficient.

[0024] A further solution of the present invention is to obtain the monitoring deviation coefficient in the following manner:

[0025] Get the moving target monitoring value JC within the monitoring period m , the moving target monitoring value JC m Subtract the moving target monitoring threshold value to obtain the moving target monitoring deviation value;

[0026] The monitoring deviation coefficient is obtained by calculating the ratio of the moving target monitoring deviation value to the moving target monitoring threshold.

[0027] A further solution of the present invention is: the moving target speed coefficient is obtained as follows:

[0028] During the monitoring period, the moving target coordinates corresponding to the initial time node of the monitoring period and the moving target coordinates corresponding to the end time node of the monitoring period are obtained, and they are marked as the initial moving target coordinates and the end moving target coordinates respectively;

[0029] Obtain the distance between the initial moving target coordinates and the final moving target coordinates, and mark it as the moving target displacement value;

[0030] The displacement value of the moving target is calculated by ratio with the time length value corresponding to the monitoring time period to obtain the moving target speed;

[0031] The moving target speed is calculated by ratioing the moving target speed with the moving target speed threshold to obtain the moving target speed coefficient.

[0032] A further solution of the present invention: The process of adjusting the monitoring range of the monitoring nodes within the monitoring area is as follows:

[0033] Get the monitoring range within the current monitoring area through the formula: TZ = V d ×K, calculate the monitoring range TZ within the required monitoring area, V d is the monitoring range in the current monitoring area, and K is the range adjustment coefficient.

[0034] A further solution of the present invention: the range adjustment coefficient is obtained as follows:

[0035] Obtain the monitoring correlation coefficient, add up all the monitoring correlation coefficients and take the average value to obtain the range adjustment coefficient.

[0036] A high-precision mobile target monitoring system based on static and dynamic combined clustering, the system comprises:

[0037] Monitoring network construction module: real-time monitoring of the target moving area, marking the target moving area as the monitoring area, and building a static cluster monitoring network in the monitoring area, wherein the static cluster monitoring network includes multiple wireless sensor nodes, and the wireless sensor nodes are evenly distributed in the monitoring area;

[0038] Target monitoring and positioning module: Based on the static cluster monitoring network in the monitoring area, a monitoring period is set. During the monitoring period, target monitoring data is obtained, wherein the target monitoring data includes target coordinates. All target coordinates are connected with a smooth curve to obtain a target closed graph. The target range area ratio and target range perimeter ratio of the target closed graph are obtained to obtain the monitoring accuracy value.

[0039] Target monitoring and evaluation module: When the target coordinate range area is obtained, the monitoring accuracy value is compared with the monitoring accuracy threshold. If the monitoring accuracy value is greater than the monitoring accuracy threshold, a low mobile target positioning accuracy signal is generated;

[0040] Target monitoring and analysis module: Based on the low positioning accuracy signal of the moving target, the monitoring deviation coefficient and the moving target speed coefficient are obtained, and the correlation between the monitoring deviation coefficient and the moving target speed coefficient is analyzed to obtain the monitoring correlation value, and the value is compared with the threshold. If the monitoring correlation value is less than or equal to the monitoring correlation threshold, a large monitoring correlation signal is generated.

[0041] Target monitoring adjustment module: When a large correlation signal is generated, the range adjustment coefficient is obtained to complete the dynamic adjustment of the monitoring range within the monitoring area.

[0042] The beneficial effects of the present invention are as follows:

[0043] (1) The present invention monitors the target moving area in real time, and marks the target moving area as a monitoring area. In the monitoring area, a static cluster monitoring network is constructed, wherein the static cluster monitoring network includes multiple wireless sensor nodes, and the wireless sensor nodes are evenly distributed in the monitoring area. Based on the static cluster monitoring network in the monitoring area, target monitoring data is obtained to obtain a monitoring accuracy value, and the monitoring accuracy value is compared with a monitoring accuracy threshold. If the moving target monitoring value is greater than the moving target monitoring threshold, it means that the static cluster monitoring network has a low positioning accuracy for the moving target in the monitoring area, and a low moving target positioning accuracy signal is generated, thereby judging whether the position of the moving target monitored in the monitoring area is accurate. If it is inaccurate, it is necessary to further analyze the reasons affecting the positioning accuracy of the moving target, and adjust the multiple wireless sensor nodes in the monitoring area.

[0044] (2) When generating a low mobile target positioning accuracy signal, the present invention obtains a monitoring deviation coefficient and a mobile target speed, calculates the ratio of each monitoring deviation coefficient to the corresponding mobile target speed, obtains a monitoring correlation coefficient, calculates the variance of all monitoring correlation coefficients, obtains a monitoring correlation value, compares the monitoring correlation value with a monitoring correlation threshold, and generates a high monitoring correlation degree signal if the monitoring correlation value is less than or equal to the monitoring correlation threshold, thereby indicating that the mobile target speed has a greater impact on the mobile target position monitoring accuracy, and determining the cause of the low mobile target positioning accuracy in the monitoring area;

[0045] (3) When a large correlation signal is generated, the present invention obtains the monitoring correlation coefficient, adds all the monitoring correlation coefficients and takes the average value to obtain the range adjustment coefficient, and calculates the monitoring range TZ in the required monitoring area through a formula, thereby completing the work of adjusting the monitoring range of the monitoring nodes in the monitoring area, thereby dynamically adjusting the monitoring range in the monitoring area by real-time monitoring of the moving target speed, thereby solving the problem of low monitoring and positioning accuracy of the moving target in the monitoring area due to its speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The present invention will be further described below in conjunction with the accompanying drawings.

[0047] Figure 1 is a flowchart of the steps of Embodiment 1 of the present invention;

[0048] Figure 2 is a flowchart of the steps of Embodiment 2 of the present invention;

[0049] Figure 3 is a flowchart of the steps of Embodiment 3 of the present invention;

[0050] Figure 4 It is a system flow chart of embodiment 4 of the present invention. DETAILED DESCRIPTION

[0051] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0052] Example 1

[0053] like Figure 1 As shown, a high-precision mobile target monitoring method based on static and dynamic combined clustering according to an embodiment of the present invention includes:

[0054] Step 1: Monitor the target moving area in real time and mark the target moving area as a monitoring area. In the monitoring area, a static cluster monitoring network is constructed, wherein the static cluster monitoring network includes a plurality of wireless sensor nodes, and the wireless sensor nodes are evenly distributed in the monitoring area.

[0055] Step 2: Based on the static cluster monitoring network in the monitoring area, a monitoring period is set, and within the monitoring period, target monitoring data within the monitoring period is obtained to obtain a monitoring accuracy value;

[0056] In some embodiments, based on the static cluster monitoring network in the monitoring area, a monitoring period is set, and within the monitoring period, target monitoring data is obtained, wherein the target monitoring data includes target coordinates, all target coordinates are connected with a smooth curve to obtain a target closed figure, and the target range area ratio and the target range perimeter ratio of the target closed figure are obtained, and the target range area ratio and the target range perimeter ratio are substituted into the formula: JC m =V m ×α+C m ×β, calculate the moving target monitoring value JC m , where V m Expressed as the target range area ratio, C m It is expressed as the target range perimeter ratio, and α and β are weight coefficients;

[0057] All the moving target monitoring values ​​are added and averaged to obtain the monitoring accuracy value;

[0058] Exemplarily, the target coordinates are obtained as follows:

[0059] In the monitoring area, each wireless sensor node in the static cluster monitoring network is marked as a monitoring node;

[0060] Based on the monitoring nodes, each monitoring node in the static cluster monitoring network is taken as the monitoring origin, and the monitoring origin is taken as the origin of the coordinate system to obtain the monitoring coordinate system;

[0061] During the monitoring period, the monitoring period is divided into a number of monitoring time periods at equal time intervals;

[0062] During the monitoring period, the target coordinates in each monitoring coordinate system are obtained, and all target coordinates are integrated to obtain a target coordinate set P = {p1, p2, p3, ..., p n};

[0063] For example, p1 = (X1, Y1), p2 = (X2, Y2), p3 = (X3, Y3), p n =(X n , Y n );

[0064] It needs to be further explained that the meaning of the monitoring accuracy value is: the two key features (target range area and target range perimeter) of the closed figure formed by the mobile target in the monitoring area monitored by each monitoring node in the static cluster monitoring network, which reflects the monitoring accuracy of the static cluster monitoring network. If the monitoring accuracy value is large, it means that during the monitoring period, the target range area is large, the target range perimeter is large, and the static cluster monitoring network has low positioning accuracy for the mobile target in the monitoring area. If the monitoring accuracy value is small, it means that the target range area is small, the target range perimeter is small, and the static cluster monitoring network has high positioning accuracy for the mobile target in the monitoring area.

[0065] Step 3: Based on the monitoring accuracy value, compare it with the threshold value to generate a high or low signal of the mobile target positioning accuracy;

[0066] The moving target positioning accuracy high and low signals include a moving target positioning accuracy high signal or a moving target positioning accuracy low signal;

[0067] In some embodiments, when the target coordinate range area is obtained, the monitoring accuracy value is compared with the monitoring accuracy threshold, and the comparison process is as follows:

[0068] If the monitoring accuracy value is greater than the monitoring accuracy threshold, it means that the target range area is large, the target range perimeter is large, and the static cluster monitoring network has low positioning accuracy for the mobile target in the monitoring area, generating a low mobile target positioning accuracy signal;

[0069] If the mobile target monitoring value is less than or equal to the mobile target monitoring threshold, it means that the target range area is small, the target range perimeter is small, and the static cluster monitoring network has a high positioning accuracy for the mobile target in the monitoring area, generating a high mobile target positioning accuracy signal;

[0070] The specific implementation scheme of the embodiment of the present invention is as follows: real-time monitoring of the target moving area is performed, and the target moving area is marked as a monitoring area. In the monitoring area, a static cluster monitoring network is constructed, wherein the static cluster monitoring network includes multiple wireless sensor nodes, and the wireless sensor nodes are evenly distributed in the monitoring area. Based on the static cluster monitoring network in the monitoring area, target monitoring data is obtained to obtain a monitoring accuracy value, and the monitoring accuracy value is compared with a monitoring accuracy threshold. If the moving target monitoring value is greater than the moving target monitoring threshold, it means that the static cluster monitoring network has a low positioning accuracy for the moving target in the monitoring area, and a low moving target positioning accuracy signal is generated, thereby judging whether the position of the moving target monitored in the monitoring area is accurate. If it is inaccurate, it is necessary to further analyze the reasons affecting the positioning accuracy of the moving target, and adjust the multiple wireless sensor nodes in the monitoring area.

[0071] Example 2

[0072] like Figure 2 As shown, since the speed at which a moving target moves in a monitoring area will affect the accuracy of the position of the moving target monitored in the monitoring area, it is necessary to analyze the correlation between the moving target speed and the degree of monitoring deviation. A high-precision moving target monitoring method based on static and dynamic combined clustering according to an embodiment of the present invention includes:

[0073] Step 4: Based on the low positioning accuracy signal of the moving target, the monitoring deviation coefficient and the moving target speed coefficient are obtained, and the correlation between the monitoring deviation coefficient and the moving target speed coefficient is analyzed to obtain the monitoring correlation value, and the value is compared with the threshold value to generate a monitoring correlation degree signal;

[0074] The monitoring correlation degree signal includes a large monitoring correlation degree signal or a small monitoring correlation degree signal;

[0075] In some embodiments, when a low moving target positioning accuracy signal is generated, a monitoring deviation coefficient and a moving target speed coefficient are obtained, a ratio calculation is performed between the monitoring deviation coefficient in each monitoring time period and the corresponding moving target speed coefficient to obtain a monitoring correlation coefficient, variance calculation is performed on all monitoring correlation coefficients to obtain a monitoring correlation value, and the monitoring correlation value is compared with the monitoring correlation threshold value. The comparison process is as follows:

[0076] If the monitoring correlation value is greater than the monitoring correlation threshold, it means that in different monitoring time periods, the correlation between the monitoring deviation of the moving target and its movement speed is small, that is, in the entire monitoring period, the influence of the moving target speed on the monitoring accuracy of the moving target position is small, and a small signal of monitoring correlation is generated;

[0077] If the monitoring correlation value is less than or equal to the monitoring correlation threshold, it means that in different monitoring time periods, the correlation between the monitoring deviation of the moving target and its movement speed is relatively large, that is, in the entire monitoring period, the moving target speed has a greater impact on the monitoring accuracy of the moving target position, and a large monitoring correlation signal is generated;

[0078] Specifically, the monitoring deviation coefficient is obtained as follows:

[0079] Get the moving target monitoring value JC within the monitoring period m , the moving target monitoring value JC m Subtract the moving target monitoring threshold value to obtain the moving target monitoring deviation value;

[0080] The moving target monitoring deviation value is calculated by ratio with the moving target monitoring threshold value to obtain the monitoring deviation coefficient;

[0081] It can be understood that the monitoring deviation coefficient means that during the monitoring period, the moving target monitoring value JC m The relative deviation degree from the moving target monitoring threshold. Specifically, it is obtained by calculating the ratio of the moving target monitoring deviation value (i.e., the difference between the actual monitoring value and the monitoring threshold) to the monitoring threshold. If the monitoring deviation coefficient is large, it means that the moving target monitoring value JC in the monitoring period is m The relative deviation from the moving target monitoring threshold is large. If the monitoring deviation coefficient is small, it means that the moving target monitoring value JC within the monitoring time period is m The relative deviation from the moving target monitoring threshold is small;

[0082] The second specific method for obtaining the moving target speed coefficient is:

[0083] During the monitoring period, the moving target coordinates corresponding to the initial time node of the monitoring period and the moving target coordinates corresponding to the end time node of the monitoring period are obtained, and they are marked as the initial moving target coordinates and the end moving target coordinates respectively;

[0084] Obtain the distance between the initial moving target coordinates and the final moving target coordinates, and mark it as the moving target displacement value;

[0085] The displacement value of the moving target is calculated by ratio with the time length value corresponding to the monitoring time period to obtain the moving target speed;

[0086] Calculate the ratio of the moving target speed to the moving target speed threshold to obtain the moving target speed coefficient;

[0087] It can be understood that: the meaning of the moving target speed is: the average speed of the moving target when it moves from the initial position (represented by the initial moving target coordinates) to the final position (represented by the final moving target coordinates) during the monitoring period. This speed is calculated by dividing the displacement of the moving target during this period (i.e., the moving target displacement value) by the length of time experienced (i.e., the time length value corresponding to the monitoring period), reflecting the average speed of the moving target during the monitoring period.

[0088] Among them, it needs to be further explained that: the meaning represented by the monitoring correlation value is: within the monitoring period, by calculating the ratio between the monitoring deviation coefficient of the moving target and its corresponding moving target speed in each monitoring time period (i.e., the monitoring correlation coefficient), and further performing variance calculation on these monitoring correlation coefficients to obtain a statistic, this monitoring correlation value reflects the degree of correlation between the monitoring deviation of the moving target and its movement speed in the entire monitoring period, if the monitoring correlation value is large, it means that in different monitoring time periods, the correlation between the monitoring deviation of the moving target and its movement speed is small, that is, in the entire monitoring period, the influence of the moving target speed on the monitoring accuracy of the moving target position is small, on the contrary, if the monitoring correlation value is small, it means that in different monitoring time periods, the correlation between the monitoring deviation of the moving target and its movement speed is large, that is, in the entire monitoring period, the influence of the moving target speed on the monitoring accuracy of the moving target position is large;

[0089] The specific implementation scheme of the embodiment of the present invention is as follows: when a low signal of positioning accuracy of a moving target is generated, a monitoring deviation coefficient and a moving target speed are obtained, a ratio calculation is performed on each monitoring deviation coefficient and a corresponding moving target speed to obtain a monitoring correlation coefficient, variance calculation is performed on all monitoring correlation coefficients to obtain a monitoring correlation value, and the monitoring correlation value is compared with a monitoring correlation threshold value. If the monitoring correlation value is less than or equal to the monitoring correlation threshold value, a high signal of monitoring correlation is generated, thereby indicating that the moving target speed has a greater influence on the monitoring accuracy of the moving target position, and determining the cause of the low positioning accuracy of the moving target in the monitoring area;

[0090] Example 3

[0091] like Figure 3 As shown, when a large correlation signal is generated, it means that the correlation between the moving target speed and the monitoring deviation degree is large. Therefore, it is necessary to adjust the monitoring range in the monitoring area. The high-precision moving target monitoring method based on static and dynamic combined clustering according to an embodiment of the present invention includes:

[0092] Step 5: Based on the large signal of correlation degree, obtain the range adjustment coefficient and dynamically adjust the monitoring range within the monitoring area;

[0093] In some embodiments, when a large correlation degree signal is generated, a range adjustment coefficient is obtained to complete the dynamic adjustment of the monitoring range within the monitoring area;

[0094] The range adjustment coefficient is obtained as follows:

[0095] Obtain the monitoring correlation coefficient, add up all the monitoring correlation coefficients and take the average value to obtain the range adjustment coefficient;

[0096] The process of adjusting the monitoring range of monitoring nodes within the monitoring area is as follows:

[0097] Get the monitoring range within the current monitoring area through the formula: TZ = V d ×K, calculate the monitoring range TZ within the required monitoring area, V d is the monitoring range in the current monitoring area, and K is the range adjustment coefficient;

[0098] The specific implementation scheme of the embodiment of the present invention is as follows: when a large correlation signal is generated, a monitoring correlation coefficient is obtained, all monitoring correlation coefficients are added together to obtain an average value, and a range adjustment coefficient is obtained, and the formula: TZ = V d ×K, calculate the monitoring range TZ in the required monitoring area, complete the adjustment of the monitoring range of the monitoring nodes in the monitoring area, so as to dynamically adjust the monitoring range in the monitoring area by real-time monitoring of the moving target speed, thereby solving the problem of low monitoring and positioning accuracy of the moving target in the monitoring area due to its speed;

[0099] Example 4

[0100] like Figure 4 As shown, a high-precision mobile target monitoring system based on static and dynamic combined clustering, the system includes:

[0101] Monitoring network construction module: real-time monitoring of the target moving area, marking the target moving area as the monitoring area, and building a static cluster monitoring network in the monitoring area, wherein the static cluster monitoring network includes multiple wireless sensor nodes, and the wireless sensor nodes are evenly distributed in the monitoring area;

[0102] Target monitoring and positioning module: Based on the static cluster monitoring network in the monitoring area, a monitoring period is set. During the monitoring period, target monitoring data is obtained, wherein the target monitoring data includes target coordinates. All target coordinates are connected with a smooth curve to obtain a target closed graph. The target range area ratio and target range perimeter ratio of the target closed graph are obtained to obtain the monitoring accuracy value.

[0103] Target monitoring and evaluation module: When the target coordinate range area is obtained, the monitoring accuracy value is compared with the monitoring accuracy threshold. If the monitoring accuracy value is greater than the monitoring accuracy threshold, a low mobile target positioning accuracy signal is generated;

[0104] Target monitoring and analysis module: Based on the low positioning accuracy signal of the moving target, the monitoring deviation coefficient and the moving target speed coefficient are obtained, and the correlation between the monitoring deviation coefficient and the moving target speed coefficient is analyzed to obtain the monitoring correlation value, which is compared with the threshold to generate a monitoring correlation degree signal;

[0105] The monitoring correlation degree signal includes a large monitoring correlation degree signal or a small monitoring correlation degree signal;

[0106] Target monitoring adjustment module: When a large correlation signal is generated, the range adjustment coefficient is obtained to complete the dynamic adjustment of the monitoring range within the monitoring area.

[0107] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A high-precision mobile target monitoring method based on static and dynamic clustering, characterized in that: include: Step 1: Monitor the target moving area in real time and mark the target moving area as a monitoring area. In the monitoring area, a static cluster monitoring network is constructed, wherein the static cluster monitoring network includes a plurality of wireless sensor nodes, and the wireless sensor nodes are evenly distributed in the monitoring area. Step 2: Based on the static cluster monitoring network in the monitoring area, a monitoring period is set, and within the monitoring period, target monitoring data is obtained, wherein the target monitoring data includes target coordinates, all target coordinates are connected with a smooth curve to obtain a target closed graph, and the target range area ratio and the target range perimeter ratio of the target closed graph are obtained to obtain the monitoring accuracy value; Step 3: When the target coordinate range area is obtained, the monitoring accuracy value is compared with the monitoring accuracy threshold. If the monitoring accuracy value is greater than the monitoring accuracy threshold, a low mobile target positioning accuracy signal is generated; Step 4: Based on the low signal of the moving target positioning accuracy, the monitoring deviation coefficient and the moving target speed coefficient are obtained, and the correlation between the monitoring deviation coefficient and the moving target speed coefficient is analyzed to obtain a monitoring correlation value, which is compared with the threshold. If the monitoring correlation value is less than or equal to the monitoring correlation threshold, a large signal of the monitoring correlation degree is generated; Step 5: When a large correlation signal is generated, the range adjustment coefficient is obtained to complete the dynamic adjustment of the monitoring range within the monitoring area.

2. The high-precision mobile target monitoring method based on static and dynamic combined clustering according to claim 1 is characterized by: The monitoring accuracy value is obtained as follows: Obtain the target range area ratio and target range perimeter ratio of the target closed figure, and substitute the target range area ratio and target range perimeter ratio into the formula: JC m =V m ×α+C m ×β, calculate the moving target monitoring value JC m , where V m Expressed as target range area ratio, C m It is expressed as the target range perimeter ratio, and α and β are weight coefficients; All the moving target monitoring values ​​are added together and averaged to obtain the monitoring accuracy value.

3. The high-precision mobile target monitoring method based on static and dynamic combined clustering according to claim 1 is characterized by: The target coordinates are obtained as follows: In the monitoring area, each wireless sensor node in the static cluster monitoring network is marked as a monitoring node; Based on the monitoring nodes, each monitoring node in the static cluster monitoring network is taken as the monitoring origin, and the monitoring origin is taken as the origin of the coordinate system to obtain the monitoring coordinate system; During the monitoring period, the monitoring period is divided into a number of monitoring time periods at equal time intervals; During the monitoring period, the target coordinates in each monitoring coordinate system are obtained, and all target coordinates are integrated to obtain a target coordinate set P = {p1, p2, p3, ..., p n }.

4. The high-precision mobile target monitoring method based on static and dynamic combined clustering according to claim 1 is characterized in that: The monitoring association value is obtained as follows: All monitoring correlation coefficients are subjected to variance calculation to obtain monitoring correlation values.

5. The high-precision mobile target monitoring method based on static and dynamic combined clustering according to claim 1 is characterized in that: The monitoring correlation coefficient is obtained as follows: The monitoring deviation coefficient and the moving target speed coefficient are obtained, and the monitoring deviation coefficient in each monitoring time period is calculated by ratio with the corresponding moving target speed coefficient to obtain the monitoring correlation coefficient.

6. The high-precision mobile target monitoring method based on static and dynamic combined clustering according to claim 5 is characterized by: The monitoring deviation coefficient is obtained as follows: Get the moving target monitoring value JC within the monitoring period m , the moving target monitoring value JC m Subtract the moving target monitoring threshold value to obtain the moving target monitoring deviation value; The monitoring deviation coefficient is obtained by calculating the ratio of the moving target monitoring deviation value to the moving target monitoring threshold.

7. The high-precision mobile target monitoring method based on static and dynamic combined clustering according to claim 5 is characterized by: The moving target speed coefficient is obtained as follows: During the monitoring period, the moving target coordinates corresponding to the initial time node of the monitoring period and the moving target coordinates corresponding to the end time node of the monitoring period are obtained, and they are marked as the initial moving target coordinates and the end moving target coordinates respectively; Obtain the distance between the initial moving target coordinates and the final moving target coordinates, and mark it as the moving target displacement value; The displacement value of the moving target is calculated by ratio with the time length value corresponding to the monitoring time period to obtain the moving target speed; The moving target speed is calculated by ratioing the moving target speed with the moving target speed threshold to obtain the moving target speed coefficient.

8. The high-precision mobile target monitoring method based on static and dynamic combined clustering according to claim 1 is characterized by: The process of adjusting the monitoring range of monitoring nodes within the monitoring area is as follows: Get the monitoring range within the current monitoring area through the formula: TZ = V d ×K, calculate the monitoring range TZ within the required monitoring area, V d is the monitoring range in the current monitoring area, and K is the range adjustment coefficient.

9. The high-precision mobile target monitoring method based on static and dynamic combined clustering according to claim 1 is characterized by: The range adjustment coefficient is obtained as follows: Obtain the monitoring correlation coefficient, add up all the monitoring correlation coefficients and take the average value to obtain the range adjustment coefficient.

10. A high-precision mobile target monitoring system based on static and dynamic clustering, characterized in that: The system includes: Monitoring network construction module: real-time monitoring of the target moving area, marking the target moving area as the monitoring area, and building a static cluster monitoring network in the monitoring area, wherein the static cluster monitoring network includes multiple wireless sensor nodes, and the wireless sensor nodes are evenly distributed in the monitoring area; Target monitoring and positioning module: Based on the static cluster monitoring network in the monitoring area, a monitoring period is set. During the monitoring period, target monitoring data is obtained, wherein the target monitoring data includes target coordinates. All target coordinates are connected with a smooth curve to obtain a target closed graph. The target range area ratio and target range perimeter ratio of the target closed graph are obtained to obtain the monitoring accuracy value. Target monitoring and evaluation module: When the target coordinate range area is obtained, the monitoring accuracy value is compared with the monitoring accuracy threshold. If the monitoring accuracy value is greater than the monitoring accuracy threshold, a low mobile target positioning accuracy signal is generated; Target monitoring and analysis module: Based on the low positioning accuracy signal of the moving target, the monitoring deviation coefficient and the moving target speed coefficient are obtained, and the correlation between the monitoring deviation coefficient and the moving target speed coefficient is analyzed to obtain the monitoring correlation value, and the value is compared with the threshold. If the monitoring correlation value is less than or equal to the monitoring correlation threshold, a large monitoring correlation signal is generated. Target monitoring adjustment module: When a large correlation signal is generated, the range adjustment coefficient is obtained to complete the dynamic adjustment of the monitoring range within the monitoring area.

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