Bird situation analysis method, system and device based on bird detection radar

Abstract

The present invention relates to the technical field of bird situation analysis, and specifically to a bird situation analysis method, system and equipment based on bird detection radar. In the present invention, a data acquisition module acquires bird detection radar data and performs trajectory analysis on it to obtain bird trajectory data, wherein the bird trajectory data includes birds, time points and positions; a dynamic time warping module performs similarity analysis on each bird in the bird trajectory data, and forms a similarity matrix between each bird by calculating the dynamic time warping distance; a group behavior analysis module calculates the local density of birds based on the similarity matrix, sets clustering centers, and distributes birds to the nearest clustering centers to form different clusters; and a bird situation analysis module selects the same birds with the largest number as the main birds in the clusters, calculates the average position of the main birds to obtain the main average trajectory, and analyzes the fluctuation index between clusters.

Description

Technical Field

[0001] The present invention relates to the technical field of bird situation analysis, and in particular to a bird situation analysis method, system and equipment based on bird detection radar. Background Art

[0002] Traditional bird-detecting radars face many technical problems in bird situation analysis, especially when dealing with bird dynamic trajectories and behavior analysis.

[0003] First, most traditional methods rely on static, average-based trajectory analysis, lacking the ability to capture the complex spatiotemporal dynamic patterns of birds. This type of analysis often ignores the flight speed, direction changes, and even trajectory changes of birds at different time points, and can only give a general idea of ​​the activity routes of bird groups, which is insufficient to reveal the subtle trajectory similarities between individuals. Secondly, traditional methods are difficult to effectively deal with the nonlinear and diverse movement patterns of bird groups during migration due to factors such as weather and terrain. In this context, relying solely on average trajectories or simple distance calculations can easily lead to misjudgments of the true behavior patterns of birds.

[0004] In addition, traditional methods lack effective clustering and classification methods for identifying the coordinated behaviors of different bird species and analyzing the trajectories of rare birds in large groups. The accuracy of the analysis results is often affected by the inability to reasonably measure the similarities between individuals. Finally, as the scale of data increases, traditional analysis methods also face bottlenecks in computational efficiency and lack comprehensive consideration of time series data, making them too simple and limited in modern research that requires simultaneous processing of large amounts of data and high precision. These technical problems limit the depth of application of traditional bird radar methods in ecological dynamics analysis and species conservation strategy formulation. Summary of the invention

[0005] The purpose of the present invention is to provide a bird situation analysis method, system and equipment based on bird detection radar to solve the problems raised in the above background technology.

[0006] To achieve the above-mentioned purpose, one of the purposes of the present invention is to provide a bird situation analysis system based on bird detection radar, comprising a data acquisition module, a dynamic time warping module, a group behavior analysis module and a bird situation analysis module, wherein:

[0007] The data acquisition module acquires bird detection radar data and performs trajectory analysis on it to obtain bird trajectory data, wherein the bird trajectory data includes the bird, time point and location;

[0008] The dynamic time warping module performs similarity analysis on each bird in the bird trajectory data, calculates the Euclidean distance of the position at different time points in each bird trajectory data, obtains a distance matrix, and calculates a cumulative distance matrix based on the minimum Euclidean distance in the distance matrix, and obtains a dynamic time warping distance based on the cumulative distance matrix, and forms a similarity matrix between each bird;

[0009] The group behavior analysis module calculates the local density of each bird according to the similarity matrix between each bird, sets the cluster center according to the local density of each bird, and assigns each bird to the nearest cluster center according to the size of the dynamic time warping distance between each bird and the cluster center to form different clusters, each cluster including different bird trajectory data;

[0010] The bird situation analysis module selects the main bird of the cluster with the largest number of identical birds according to the birds in the different bird trajectory data in the cluster, and calculates the average value of the position in the bird trajectory data corresponding to the main bird as the main average trajectory; by calculating the main average trajectory of each cluster, the fluctuation index between clusters is analyzed.

[0011] As a further improvement of the technical solution, the calculation process of the similarity matrix of the dynamic time warping module specifically includes:

[0012] For two bird trajectory data and , calculate their Euclidean distance ,in A bird track data At the point in time The location coordinates of Another bird track data At the point in time The location coordinates represent the longitude and latitude; by calculating the bird trajectory data and bird track data The Euclidean distances between each time point form a distance matrix;

[0013] Calculate the cumulative distance matrix based on the minimum Euclidean distance in the distance matrix ,in Indicates starting point To location The minimum cumulative distance is as follows:

[0014] , which is a dynamic programming formula used to determine the minimum cumulative distance from the starting point to the current location by selecting the path with the smallest cumulative distance among the three paths and adding the current Euclidean distance , gradually construct the optimal path from the starting point to the end point;

[0015] According to the cumulative distance matrix , and obtain the dynamic time warping distance ,in and Bird track data and bird track data The length of the pairwise calculation of the dynamic time warping distance between different birds , the distance is converted into similarity through the exponential function similarity measurement method, and the final similarity matrix is , similarity matrix Each element of the matrix describes the bird and birds The similarity value of .

[0016] As a further improvement of the technical solution, the specific process of the group behavior analysis module forming different clusters includes:

[0017] For Birds , calculate its local density , the local density is obtained through the similarity matrix The similarity value is summed up to achieve, where the formula is , which means birds The density with other birds; According to the similarity matrix between each bird, the local density of each bird is obtained;

[0018] Calculate the closest distance , which means that for birds , find all birds with higher density than it, and among them find the same bird The closest one and calculate the closest distance to ensure that it is discriminative in the calculation, where is the index of the midpoint of all birds;

[0019] according to The value of determines the cluster center and selects Greater than all birds The birds with the average value are taken as cluster centers. For each bird that is not a cluster center, its dynamic time warping distance with each cluster center is calculated. Each bird is assigned to the cluster to which the cluster center with the shortest dynamic time warping distance belongs. Each cluster center and its assigned birds together form a cluster group.

[0020] As a further improvement of the technical solution, the calculation process of the fluctuation index in the bird situation analysis module specifically includes:

[0021] In each cluster, the frequency of each bird species is counted, and the bird species with the highest number of occurrences is selected as the main bird species of the cluster;

[0022] For the main birds, their trajectory data, i.e., the position information at different time points, are collected. For each time point, the average value of each coordinate in the position data is calculated as the main average trajectory of the cluster;

[0023] By calculating the main average trajectory of each cluster, the fluctuation index between clusters is analyzed. The fluctuation index is used to measure the change of the main average trajectory between adjacent clusters. The Euclidean distance is used to represent this change. For two adjacent clusters and , volatility index Defined as:

[0024] ,in and Represents clusters The position coordinates corresponding to the main average trajectory of and Represents clusters The position coordinates corresponding to the main average trajectory;

[0025] Traverse all clusters, calculate the volatility index for each pair of adjacent clusters, and identify cluster pairs whose volatility index is higher than the average volatility index of all clusters.

[0026] The second object of the present invention is to provide a method for using a bird situation analysis system based on a bird detection radar, comprising the following method steps:

[0027] S1. Obtain bird detection radar data and perform trajectory analysis on it to obtain bird trajectory data, wherein the bird trajectory data includes the bird, time point and location;

[0028] S2, performing similarity analysis on each bird in the bird trajectory data, calculating the Euclidean distance of the position at different time points in each bird trajectory data, obtaining a distance matrix, and calculating a cumulative distance matrix according to the minimum Euclidean distance in the distance matrix, and obtaining a dynamic time warping distance according to the cumulative distance matrix, and forming a similarity matrix between each bird;

[0029] S3. Calculate the local density of each bird based on the similarity matrix between each bird, set the cluster center based on the local density of each bird, and assign each bird to the nearest cluster center based on the size of the dynamic time warping distance between each bird and the cluster center to form different clusters, each cluster including different bird trajectory data;

[0030] S4. According to the birds in the different bird trajectory data in the cluster, select the bird with the largest number of the same birds in the cluster as the main bird of the cluster, and calculate the average value of the position in the bird trajectory data corresponding to the main bird as the main average trajectory; by calculating the main average trajectory of each cluster, analyze the fluctuation index between clusters.

[0031] The third object of the present invention is to provide a bird situation analysis device based on a bird detecting radar, comprising: a memory and a processor; the memory is used to store program instructions; the processor is used to call and execute the program instructions in the memory.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The bird situation analysis method, system and device based on bird detection radar provide a method for accurately measuring the similarity of bird trajectories through the similarity matrix obtained by dynamic time warping distance calculation and the dynamic time warping distance between each bird and the cluster center; as an effective tool for processing time series data, the dynamic time warping distance allows fine-grained matching of birds at different time points, even if their flight speeds and directions are different; the similarity matrix formed by dynamic time warping can accurately identify birds with similar migration paths, so that subsequent cluster analysis can better capture the structural characteristics of the group, significantly improving the accuracy and reliability of clustering;

[0034] In addition, by calculating the dynamic time-warped distance between each bird and the cluster center, each bird is assigned to the cluster center that is most consistent with its trajectory, thereby forming clusters containing trajectory data of different birds in ecological research; this method not only improves the accuracy of data clustering, but also supports in-depth research on group behavior, helping to reveal the collaborative behavior patterns and potential ecological interactions of different bird species; the comprehensive use of dynamic time-warped distance provides a more accurate basis for bird ecological research and protection planning, which is of positive significance for predicting future changes in the ecosystem and responding to potential threats. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0036] Figure 2 It is a schematic diagram of the overall module of the present invention.

[0037] In the figure: 100, data acquisition module; 200, dynamic time warping module; 300, group behavior analysis module; 400, bird situation analysis module. DETAILED DESCRIPTION

[0038] The following will be combined with the accompanying drawings in 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] Next, see Figure 1-Figure 2 One of the purposes of this embodiment is to provide a bird situation analysis system based on a bird detection radar, including a data acquisition module 100, a dynamic time warping module 200, a group behavior analysis module 300 and a bird situation analysis module 400.

[0040] The data acquisition module 100 uses a bird detection radar to continuously scan a designated area, captures data of moving targets (birds) as bird detection radar data, processes the bird detection radar data, filters out noise and non-bird reflections (such as weather interference, terrain echoes), and uses a target detection algorithm to identify and track birds in the bird detection radar data, assigns a unique identifier to each detected target, ensures that all data points can be tracked to a specific bird in subsequent steps, and finally obtains bird trajectory data, wherein the bird trajectory data includes the bird, time point and location.

[0041] The dynamic time warping module 200 performs similarity analysis on each bird in the bird trajectory data, calculates the Euclidean distance of the position at different time points in each bird trajectory data, obtains a distance matrix, and calculates a cumulative distance matrix based on the minimum Euclidean distance in the distance matrix, and obtains a dynamic time warping distance based on the cumulative distance matrix, and forms a similarity matrix between each bird, specifically including:

[0042] For two bird trajectory data and , calculate their Euclidean distance ,in A bird track data At the point in time The location coordinates of Another bird track data At the point in time The location coordinates represent the longitude and latitude; by calculating the bird trajectory data and bird track data The Euclidean distances between each time point form a distance matrix;

[0043] Calculate the cumulative distance matrix based on the minimum Euclidean distance in the distance matrix ,in Indicates starting point To location The minimum cumulative distance is as follows:

[0044] , which is a dynamic programming formula used to determine the minimum cumulative distance from the starting point to the current location by selecting the path with the smallest cumulative distance among the three paths and adding the current Euclidean distance , gradually construct the optimal path from the starting point to the end point;

[0045] According to the cumulative distance matrix , and obtain the dynamic time warping distance ,in and Bird track data and bird track data The length of the pairwise calculation of the dynamic time warping distance between different birds , the distance is converted into similarity through the exponential function similarity measurement method, the purpose is to convert the smaller dynamic time warping distance The distance is converted into a higher similarity value, and the final similarity matrix is symmetric, the similarity matrix Each element of the matrix describes the bird and birds The similarity value of .

[0046] The group behavior analysis module 300 calculates the local density of each bird based on the similarity matrix between each bird, sets the cluster center based on the local density of each bird, and assigns each bird to the nearest cluster center based on the size of the dynamic time warping distance between each bird and the cluster center to form different clusters, each of which includes different bird trajectory data. The specific process includes:

[0047] For Birds , calculate its local density , the local density is obtained through the similarity matrix The similarity value is summed up to achieve, where the formula is , which means birds The density with other birds; According to the similarity matrix between each bird, the local density of each bird is obtained;

[0048] In order to identify those points that not only have high local density but are also spatially far away from other high-density points, because they are more likely to be the center of the cluster, for each bird, it is necessary to find the one with the closest dynamic time warping distance among all the birds with higher local density than it, so the closest distance is calculated , which means that for birds , find all birds with higher density than it, and among them find the same bird The closest one and calculate the closest distance to ensure that it is discriminative in the calculation, where is the index of the midpoint of all birds;

[0049] according to The value of determines the cluster center and selects Greater than all birds The birds with the average value are taken as cluster centers. For each bird that is not a cluster center, its dynamic time warping distance with each cluster center is calculated. Each bird is assigned to the cluster to which the cluster center with the shortest dynamic time warping distance belongs. Each cluster center and its assigned birds together form a cluster. The clusters reflect members of the bird group with similar behaviors and provide an understanding of the behavioral patterns of different birds.

[0050] The bird situation analysis module 400 selects the main bird of the cluster with the largest number of the same birds according to the birds in the different bird trajectory data in the cluster, and calculates the average value of the position in the bird trajectory data corresponding to the main bird as the main average trajectory; by calculating the main average trajectory of each cluster, the fluctuation index between clusters is analyzed, which specifically includes:

[0051] In each cluster, the frequency of each bird species is counted, and the bird species with the highest number of occurrences is selected as the main bird species of the cluster;

[0052] For the main birds, their trajectory data, i.e., the location information at different time points, are collected, and the average value of the location data is calculated over time. Specifically, for each time point, the average value of each coordinate in the location data is calculated respectively as the main average trajectory of the cluster;

[0053] By calculating the main average trajectory of each cluster, the fluctuation index between clusters is analyzed. The fluctuation index is used to measure the change of the main average trajectory between adjacent clusters. The Euclidean distance is used to represent this change. For two adjacent clusters and , volatility index Defined as:

[0054] ,in and Represents clusters The position coordinates corresponding to the main average trajectory of and Represents clusters The position coordinates corresponding to the main average trajectory;

[0055] Traverse all clusters, calculate the fluctuation index for each pair of adjacent clusters, traverse all clusters, calculate the fluctuation index for each pair of adjacent clusters, identify cluster pairs with fluctuation index higher than the average fluctuation index of all clusters, and this cluster pair marks the turning point or special behavior on the bird migration path.

[0056] The bird situation analysis module 400 analyzes the bird trajectory data in different clusters, identifies the main birds in each cluster, and calculates its main average trajectory, based on which the fluctuation index between clusters is analyzed. Specifically, the module first counts the birds that appear most frequently in each cluster as the main birds, and calculates the position average in the trajectory data of the main birds to form the main average trajectory; by comparing the Euclidean distance of the main average trajectories between adjacent clusters, the fluctuation index is calculated, which is used to measure the amplitude of the trajectory changes between clusters; through this process, the module can not only identify the significant change areas or turning points during the bird migration, but also reveal the potential bird behavior patterns, thereby providing strong support for bird behavior research and protection strategy formulation.

[0057] The second purpose of this embodiment is to provide a method for using a flying bird distance assessment system based on a bird detection radar, comprising the following method steps:

[0058] S1. Obtain bird detection radar data and perform trajectory analysis on it to obtain bird trajectory data, wherein the bird trajectory data includes the bird, time point and location;

[0059] S2, performing similarity analysis on each bird in the bird trajectory data, calculating the Euclidean distance of the position at different time points in each bird trajectory data, obtaining a distance matrix, and calculating a cumulative distance matrix according to the minimum Euclidean distance in the distance matrix, and obtaining a dynamic time warping distance according to the cumulative distance matrix, and forming a similarity matrix between each bird;

[0060] S3. Calculate the local density of each bird based on the similarity matrix between each bird, set the cluster center based on the local density of each bird, and assign each bird to the nearest cluster center based on the size of the dynamic time warping distance between each bird and the cluster center to form different clusters, each cluster including different bird trajectory data;

[0061] S4. According to the birds in the different bird trajectory data in the cluster, select the bird with the largest number of the same birds in the cluster as the main bird of the cluster, and calculate the average value of the position in the bird trajectory data corresponding to the main bird as the main average trajectory; by calculating the main average trajectory of each cluster, analyze the fluctuation index between clusters.

[0062] The third purpose of this embodiment is to provide a bird situation analysis device based on a bird detection radar, comprising: a memory and a processor; the memory is used to store program instructions; the processor is used to call and execute the program instructions in the memory.

[0063] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit 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 bird situation analysis system based on bird detection radar, characterized in that: The system comprises a data acquisition module (100), a dynamic time warping module (200), a group behavior analysis module (300) and a bird situation analysis module (400), wherein: The data acquisition module (100) acquires bird detection radar data and performs trajectory analysis on the data to obtain bird trajectory data, wherein the bird trajectory data includes the bird, time point and location; The dynamic time warping module (200) performs similarity analysis on each bird in the bird trajectory data, calculates the Euclidean distance of the position at different time points in each bird trajectory data, obtains a distance matrix, and calculates a cumulative distance matrix based on the minimum Euclidean distance in the distance matrix, and obtains a dynamic time warping distance based on the cumulative distance matrix, and forms a similarity matrix between each bird; The group behavior analysis module (300) calculates the local density of each bird based on the similarity matrix between each bird, sets a cluster center based on the local density of each bird, and assigns each bird to the nearest cluster center based on the size of the dynamic time warping distance between each bird and the cluster center, thereby forming different clusters, each cluster including different bird trajectory data; The bird situation analysis module (400) selects the bird with the largest number of identical birds in the cluster as the main bird of the cluster according to the birds in the different bird trajectory data in the cluster, and calculates the average value of the position in the bird trajectory data corresponding to the main bird as the main average trajectory; by calculating the main average trajectory of each cluster, the fluctuation index between clusters is analyzed.

2. The bird situation analysis system based on bird detection radar according to claim 1 is characterized in that: The calculation process of the similarity matrix of the dynamic time warping module (200) specifically includes: For two bird trajectory data and , calculate their Euclidean distance ,in A bird track data At the point in time The location coordinates of Another bird track data At the point in time The location coordinates represent the longitude and latitude; by calculating the bird trajectory data and bird track data The Euclidean distances between each time point form a distance matrix; Calculate the cumulative distance matrix based on the minimum Euclidean distance in the distance matrix ,in Indicates starting point To location The minimum cumulative distance is as follows: , which is a dynamic programming formula used to determine the minimum cumulative distance from the starting point to the current location by selecting the path with the smallest cumulative distance among the three paths and adding the current Euclidean distance , gradually construct the optimal path from the starting point to the end point; According to the cumulative distance matrix , and obtain the dynamic time warping distance ,in and Bird track data and bird track data The length of the pairwise calculation of the dynamic time warping distance between different birds , the distance is converted into similarity through the exponential function similarity measurement method, and the final similarity matrix is , similarity matrix Each element describes the bird and birds The similarity value of .

3. The bird situation analysis system based on bird detection radar according to claim 2 is characterized in that: The specific process of the group behavior analysis module (300) forming different clusters includes: For Birds , calculate its local density , the local density is obtained through the similarity matrix The similarity value is summed up to achieve, where the formula is , which means birds The density with other birds; According to the similarity matrix between each bird, the local density of each bird is obtained; Calculate the closest distance , which means that for birds , find all birds with higher density than it, and among them find the same bird The closest one and calculate the closest distance to ensure that it is discriminative in the calculation, where is the index of the midpoint of all birds; according to The value of determines the cluster center and selects Greater than all birds The birds with the average value are taken as cluster centers. For each bird that is not a cluster center, its dynamic time warping distance with each cluster center is calculated. Each bird is assigned to the cluster to which the cluster center with the shortest dynamic time warping distance belongs. Each cluster center and its assigned birds together form a cluster group.

4. The bird situation analysis system based on bird detection radar according to claim 3 is characterized in that: The calculation process of the fluctuation index in the bird situation analysis module (400) specifically includes: In each cluster, the frequency of each bird species is counted, and the bird species with the highest number of occurrences is selected as the main bird species of the cluster; For the main birds, their trajectory data, i.e., the location information at different time points, are collected. For each time point, the average value of each coordinate in the corresponding location information data is calculated as the main average trajectory of the cluster; By calculating the main average trajectory of each cluster, the fluctuation index between clusters is analyzed. The fluctuation index is used to measure the change of the main average trajectory between adjacent clusters. The Euclidean distance is used to represent this change. For two adjacent clusters and , volatility index Defined as: ,in and Represents clusters The position coordinates corresponding to the main average trajectory of and Represents clusters The position coordinates corresponding to the main average trajectory; Traverse all clusters, calculate the volatility index for each pair of adjacent clusters, and identify cluster pairs whose volatility index is higher than the average volatility index of all clusters.

5. A method for using the bird situation analysis system based on bird detection radar according to any one of claims 1 to 4, characterized in that: The method comprises the following steps: S1. Obtain bird detection radar data and perform trajectory analysis on it to obtain bird trajectory data, wherein the bird trajectory data includes the bird, time point and location; S2, performing similarity analysis on each bird in the bird trajectory data, calculating the Euclidean distance of the position at different time points in each bird trajectory data, obtaining a distance matrix, and calculating a cumulative distance matrix according to the minimum Euclidean distance in the distance matrix, and obtaining a dynamic time warping distance according to the cumulative distance matrix, and forming a similarity matrix between each bird; S3. Calculate the local density of each bird based on the similarity matrix between each bird, set the cluster center based on the local density of each bird, and assign each bird to the nearest cluster center based on the size of the dynamic time warping distance between each bird and the cluster center to form different clusters, each cluster including different bird trajectory data; S4. According to the birds in the different bird trajectory data in the cluster, select the bird with the largest number of the same birds in the cluster as the main bird of the cluster, and calculate the average value of the position in the bird trajectory data corresponding to the main bird as the main average trajectory; by calculating the main average trajectory of each cluster, analyze the fluctuation index between clusters.

6. A bird situation analysis device based on bird detection radar, characterized in that: include: Memory and processor; The memory is used to store program instructions; The processor is used to call and execute the program instructions in the memory to perform the method according to claim 5.

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