Low altitude perception system and trajectory fusion method thereof

Abstract

This invention discloses a low-altitude sensing system and its trajectory fusion method. The low-altitude sensing system includes a low-altitude management platform and a sensing base station system. The sensing base station system includes a baseband unit and an active antenna unit. The active antenna unit detects low-altitude flying targets and generates raw trajectory data containing the longitude, latitude, altitude, speed, and trajectory identifier of the detected targets. The baseband unit performs real-time correlation, deduplication, and trajectory fusion processing based on a multi-level cache queue on the raw trajectory data to obtain fused trajectory data, which is then reported to the low-altitude management platform. The low-altitude management platform visualizes the trajectory data reported by the baseband unit. This invention solves the problem of unstable and easily changing target trajectory identifiers (TrackId) under asynchronous sensing data from multiple AAUs. By using weighted election and a multi-level caching mechanism, this invention outputs a continuous, stable, and reliable unified trajectory, improving the accuracy and robustness of low-altitude target tracking.

Description

Technical Field

[0001] This invention relates to the low-altitude domain, and more particularly to a low-altitude sensing system and its trajectory fusion method. Background Technology

[0002] As wireless networks evolve from the Internet of Everything to the Intelligent Internet of Everything, integrated communication and sensing has become a key innovation direction for 5G-Advanced and future networks. Its core lies in utilizing the same wireless signals and network infrastructure to simultaneously achieve communication and environmental sensing functions (such as positioning, ranging, and speed measurement), thereby constructing a low-cost, high-precision, seamless, and ubiquitous intelligent network. In integrated communication and sensing networks, the MIMO-OFDM signals broadcast by sensing base stations are used as sensing sources, attracting significant attention due to their high resolution and anti-fading advantages. How to stably and continuously track multiple moving targets from these signals and form continuous trajectories (i.e., multi-target tracking and trajectory fusion) is the core challenge in achieving intelligent environmental sensing. Existing technical solutions have the following drawbacks:

[0003] 1. Traditional association algorithms (such as multiple hypothesis tracking (MHT) and joint probability data association (JPDA)) usually require prior knowledge of the number of targets and have extremely high computational complexity in real-world clutter environments, making them difficult to meet real-time processing requirements.

[0004] 2. The same target is assigned multiple temporary track IDs (TrackId), or the same ID is incorrectly associated with different targets at different times, causing track splitting, interruption or misassociation in the upper-level system. Summary of the Invention

[0005] The technical problem to be solved by the embodiments of the present invention is to provide a low-altitude sensing system and its trajectory fusion method to solve the problem of unstable and easily changing trajectory identification of targets.

[0006] To address the aforementioned technical problems, this invention proposes a low-altitude sensing system, comprising a low-altitude management platform and a sensing base station system. The sensing base station system includes a baseband unit and an active antenna unit. The active antenna unit detects low-altitude flying targets and generates raw trajectory data containing the longitude, latitude, altitude, speed, and trajectory identifier of the detected target. The trajectory identifier is a natural number incrementing from 1 and serves as the trajectory ID of the detected target. The baseband unit performs real-time correlation, deduplication, and trajectory fusion processing based on a multi-level cache queue on the raw trajectory data to obtain fused trajectory data, which is then reported to the low-altitude management platform.

[0007] The low-altitude management platform visualizes the trajectory data reported by the baseband unit.

[0008] Accordingly, embodiments of the present invention also provide a trajectory fusion method for a low-altitude sensing system, wherein the low-altitude sensing system includes a low-altitude management platform and a sensing base station system, the sensing base station system comprising a baseband unit and an active antenna unit, and the method includes:

[0009] Step 1: The active antenna unit detects low-altitude flying targets and generates raw trajectory data containing the longitude, latitude, altitude, speed and trajectory identifier of the detected target. The trajectory identifier is a natural number that is assigned incrementally starting from 1, and the trajectory identifier serves as the trajectory ID of the detected target.

[0010] Step 2: The baseband unit performs real-time correlation, deduplication, and trajectory fusion processing based on a multi-level cache queue on the original trajectory data to obtain the fused trajectory data and reports it to the low-altitude management platform;

[0011] Step 3: The low-altitude management platform visualizes the trajectory data reported by the baseband unit.

[0012] The beneficial effects of this invention are as follows:

[0013] 1. Strong continuity guarantee: By assigning higher election weight to historical data (high-level list) and considering the duration of track identifiers (TrackId), the system has a strong "inertia" to maintain existing TrackIds, which significantly reduces meaningless jumps in identifiers.

[0014] 2. Utilizing complete context: The election decision of this invention is not only based on the current batch data, but also integrates historical data that is in different processing stages and has been sent, making the decision more comprehensive and robust.

[0015] 3. Adapting to asynchronous data: The periodic processing and timeout mechanism of this invention can effectively handle track data from different AAUs that may have delays and asynchrony. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of a low-altitude sensing system according to an embodiment of the present invention.

[0017] Figure 2 This is a schematic diagram of a four-level cache queue constructed by the baseband unit in an embodiment of the present invention. Detailed Implementation

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] In this embodiment of the invention, directional indicators (such as up, down, left, right, front, back, etc.) are only used to explain the relative positional relationship and movement of each component in a specific posture (as shown in the figure). If the specific posture changes, the directional indicator will also change accordingly.

[0020] Furthermore, in this invention, descriptions involving "first," "second," etc., are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features.

[0021] Please refer to Figure 1 The low-altitude sensing system of this invention includes a low-altitude management platform and a sensing base station system.

[0022] The low-altitude management platform is a system platform for displaying the trajectories of low-altitude sensed targets. This platform receives stable trajectories from one or more sensing base stations and visualizes them based on trajectory data reported by the baseband unit. The low-altitude management platform receives trajectory data reported by the sensing base station system and presents the dynamic trajectories of low-altitude flying targets in real time through 3D electronic maps, timeline charts, and other methods, supporting the display of multiple targets.

[0023] The sensing base station system includes a baseband unit (BBU) and an active antenna unit (AAU), which can measure the distance, location, and speed of low-altitude flying targets (such as drones, birds, etc.).

[0024] The baseband unit (BBU) is responsible for data processing of the sensed target, deduplication of targets between cells within the station, and reporting of sensing results. The active antenna unit (AAU) is responsible for generating and transmitting the sensed signal and receiving and processing the echo signal. The active antenna unit detects low-altitude flying targets and generates raw trajectory data containing the longitude, latitude, altitude, speed, and trajectory identifier of the detected target. The active antenna unit (AAU) typically reports data every 1-6 seconds, reporting individual trajectory point data (even for the same target, the trajectory identifier of the reported trajectory point data may or may not change).

[0025] The baseband unit (BBU) has a built-in trajectory fusion processing module, which is responsible for real-time correlation, deduplication, and trajectory fusion processing based on multi-level cache queues of sensing data from multiple AAUs at this station, and then reporting the fused trajectory data to the low-altitude management platform.

[0026] In one implementation, each baseband unit (BBU) is equipped with three active antenna units (AAUs). Each AAU is deployed with an azimuth angle of 120° and an elevation angle of 60°. The three AAUs work together to achieve 360° low-altitude azimuth sensing coverage. The BBU is connected to the three AAUs via fiber optic cables. After the three AAUs and BBU are networked, they communicate with the low-altitude airspace management platform to transmit the final sensing data, forming a complete sensing system.

[0027] Preferably, a 60° pitch angle (i.e., downtilt angle) directs the AAU's main beam to an altitude range of 10–100 meters above the ground, precisely covering targets such as low-altitude aircraft, drones, and mobile terminals between urban buildings. This angle significantly reduces redundant energy radiated upwards, while enhancing penetration and signal-to-noise ratio against near-ground targets. Compared to the traditional 0°–30° pitch angle (used for ground coverage), 60° effectively avoids ground reflection interference and high-altitude signal waste, achieving precise resource projection.

[0028] Each sensing base station system comprises three AAUs. Each AAU detects low-altitude flying targets and generates raw trajectory data containing the target's longitude, latitude, altitude, speed, and TrackId (trajectory identifier). The longitude, latitude, and altitude are accurate to four decimal places. The speed is accurate to two decimal places. The TrackId is a natural number assigned incrementing from 1, serving as the target's trajectory ID.

[0029] Please refer to Figure 2 The BBU constructs a four-level cache queue and starts a periodic algorithm timer.

[0030] The periodic algorithm timer includes: an election timer (ET) and a transmission timer (ST).

[0031] The four-level cache queue includes:

[0032] First-level queue (raw fusion queue): Stores newly arrived raw data. The three AAUs attached to the BBU store the trajectory data detected by the same target at the current moment.

[0033] The second-level queue (election preparation queue) retrieves the track information from the first-level queue. This information represents the track information before the TrackId election. The TrackId election is triggered when the election timer (ET) times out.

[0034] The third-level queue (transmission preparation queue): retrieves the trajectory information after the TrackId election in the second-level queue. After the transmission period timer (ST) expires, the trajectory information to be transmitted is sent to the low-altitude management platform.

[0035] The fourth-level queue (historical cache queue) stores the trajectory information of the most recently sent events as a historical reference to enhance the continuity of the election.

[0036] As one implementation method, the baseband unit clusters the trajectory data reported by different active antenna units:

[0037] Store all trajectory points from the trajectory data in the first-level queue into the initial set P_List = {P1,...,P j , ...,P n}, where each trajectory point P j Includes its location information (x) j , y j , z j Temporary track identifier Tid j With speed V j ; j is the index of the P_List object, which is a natural number starting from 1; x j Representing longitude information, the y j Representing latitude information, the z j Represents height information; n is the total number of trajectory points in the initial set P_List;

[0038] Calculate the pairwise 3D Euclidean distance between all trajectory points in P_List. .

[0039] Trajectory points whose Euclidean distance in 3D space is less than a preset distance threshold D_MAX (the maximum spatial distance to be considered the same target) are grouped into the same cluster. Each cluster C k This represents a set of trajectory points initially identified as the same physical target; the resulting cluster set is C_List = {C1, ...,C}. k , ..., C Max_C}, where k is the index of any object in the cluster set, 1≤k≤Max_C; and Max_C is the maximum number of clusters in the C_List.

[0040] Then, a weighted election is performed on the trajectory identifiers of the trajectory points within the cluster:

[0041] Iterate through C_List and retrieve each cluster C in turn. k ;

[0042] Find cluster C k The different temporary trajectory identifiers carried by all trajectory points constitute the candidate set Tid_C k ={Tid1,...,Tid m , ...,Tid Max_T}, where m is Tid_C k The index of any object in the set, 1 ≤ m ≤ Max_T; where Max_T is the cluster set Tid_C. k The maximum number;

[0043] Calculate the candidate set Tid_C k Tid in each of the middle m The weight W_Tid m ,formula:

[0044] ;

[0045] Among them, W_L i Indicates Tid m The weight value of the i-th level queue (the i-th level queue has a Tid) m In the case of), the Indicates Tid m The sum of the hierarchical weights of the first to fourth level queues, 1≤i≤4;

[0046] Finally, select W_Tid. m maximum value of Ti m As cluster C k The final output trajectory identifier is used as the trajectory ID when the BBU sends it to the low-altitude management platform for display.

[0047] The trajectory fusion method of the low-altitude sensing system in this embodiment of the invention includes steps 1 to 3.

[0048] Step 1: The active antenna unit detects low-altitude flying targets and generates raw trajectory data containing the longitude, latitude, altitude, speed and trajectory identifier of the detected target. The trajectory identifier is a natural number that is assigned incrementally starting from 1, and the trajectory identifier serves as the trajectory ID of the detected target.

[0049] Each sensing base station system contains 3 AAUs. Each AAU detects low-altitude flying targets and generates raw trajectory data containing the longitude, latitude, altitude, speed, and TrackId of the detected targets.

[0050] Example: Figure 1 The raw trajectory data reported by AAU1 to the BBU for low-altitude target detection is {1**. **03, 3*. **86, 3*. **46, 3.80, 777}, which represent longitude 1**. **03, latitude 3*. **86, altitude 3*. **046 (unit: meters), speed 3.80 (meaning 3.80 meters / second), and TrackId 777, respectively.

[0051] Figure 1The raw trajectory data for low-altitude target detection reported by AAU2 to BBU is {1**. **05, 3*. **85, 3*. **11, 3.81, 774}, which represent longitude 1**. **05, latitude 3*. **85, altitude 3*. **11, speed 3.81 (meaning 3.81 m / s), and TrackId 774, respectively.

[0052] Figure 1 The raw trajectory data for low-altitude target detection reported by AAU3 to BBU is {1**. **06, 3*. **83, 3*. **21, 3.80, 771}, which represent longitude 1**. **06, latitude 3*. **83, altitude 3*. **21, speed 3.80 (meaning 3.80 m / s), and TrackId 771, respectively.

[0053] Step 2: The baseband unit performs real-time correlation, deduplication, and trajectory fusion processing based on a multi-level cache queue on the original trajectory data to obtain the fused trajectory data and reports it to the low-altitude management platform.

[0054] The BBU constructs a four-level cache queue and starts a periodic algorithm timer.

[0055] The periodic algorithm timer includes: an election timer (ET) and a transmission timer (ST).

[0056] The four-level cache queue includes:

[0057] First-level queue (raw fusion queue): Stores newly arrived raw data. The three AAUs attached to the BBU store the trajectory data detected by the same target at the current moment.

[0058] Second-level queue (election preparation queue): Retrieves track information from the first-level queue. This information represents the track information before TrackId election. The election of TrackId is triggered when the election timer (ET) times out.

[0059] The third-level queue (transmission preparation queue): retrieves the trajectory information after the TrackId election in the second-level queue. After the transmission period timer (ST) expires, the trajectory information to be transmitted is sent to the low-altitude management platform.

[0060] The fourth-level queue (historical cache queue): stores the most recently sent trajectory information as a historical reference to enhance the continuity of the election. For example, the user may configure it to store 300 previously sent trajectory information entries.

[0061] In one implementation, the cluster-weighted election decision of TrackId in step 2 includes the spatial clustering of trajectory points in step 21 and the intra-cluster weighted election of TrackId in step 22.

[0062] Step 21: The baseband unit clusters the trajectory data reported by different active antenna units. The purpose is to cluster the trajectory information reported by different AAUs and analyze which points are the trajectory information of the same target point detected by different AAUs.

[0063] Store all trajectory points in the first-level queue into the initial set P_List = {P1, ...,P j , ...,P n}, where each point P j Includes its location information (x) j , y j , z j ) and the Tid of the temporary TrackId j With speed V j .

[0064] Calculate the pairwise 3D Euclidean distance between all trajectory points in P_List. .

[0065] Set a distance threshold D_MAX (the maximum spatial distance that is considered to be the same target).

[0066] Perform clustering: group trajectory points whose Euclidean distance in 3D space is less than D_MAX into the same cluster. Each cluster C k This represents a set of trajectory points that are initially identified as the same physical target.

[0067] The clustered set C_List = {C1, ...,C k , ..., C Max_C}

[0068] k is the index of any object in the cluster set, 1 ≤ k ≤ Max_C. Max_C is the maximum number of clusters in the C_List.

[0069] Taking the data in the above example as an example, the trajectory information for AAU1, AAU2, and AAU3 are as follows:

[0070] {1**. **03,3*. **86,3*. **46,3.80,777},

[0071] {1**. **05,3*. **85,3*. **11,3.81,774},

[0072] {1**. **06, 3*. **83, 3*. **21, 3.80, 771} represents the trajectory point information stored after the initial detection in the first-level queue. Following the steps above, a three-dimensional spatial distance determination is performed. Taking the data from AAU1 and AAU2 as an example, with the user-set D_MAX = 2:

[0073] = 0.0035 < 2(D_MAX);

[0074] Subsequently, the three-dimensional spatial distances between AAU2 and AAU3, and between AAU3 and AAU1, were calculated separately (the calculation process is not detailed here; please refer to the calculation process for AAU1 and AAU2). It was found that all three distances were less than 2 (D_MAX). Therefore, the trajectories of these three points belong to the same detection target.

[0075] After the above process, we obtain the cluster set C_List = {C1} after clustering.

[0076] C1 = {{1**. **03, 3*. **86, 3*. **46, 3.80, 777},

[0077] {1**. **05,3*. **85,3*. **11,3.81,774},

[0078] {1**. **06,3*. **83,3*. **21,3.80,771}}.

[0079] Step 22, weighted election of trajectory identifiers for trajectory points within the cluster:

[0080] Iterate through C_List and retrieve each cluster C in turn. k .

[0081] Taking C_List = {C1} as an example, C_List contains only one object.

[0082] Find cluster C k The different temporary TrackIds carried by all trajectory points constitute the candidate set Tid_C k ={Tid1,...,Tid m , ...,Tid Max_T}. The m is Tid_C k The index of any object in the set, 1 ≤ m ≤ Max_T. Max_T is the cluster set Tid_C. k The maximum number of.

[0083] Taking C1 as an example, the candidate set Tid_C1 = {777, 774, 771} is formed.

[0084] Calculate the candidate set Tid_C k Tid in each of the middle m The weight W_Tid m ,formula:

[0085] ;

[0086] Among them, W_L i Indicates Tid m The weight value of the i-th level queue (the i-th level queue has a Tid) m (in the case of). Indicates Tid m The sum of the hierarchical weights of the first to fourth level queues, 1≤i≤4.

[0087] Select W_Tid m maximum value of Ti m As cluster C k The final output TrackId.

[0088] For example, set W_L1 = 0.1, W_L2 = 0.2, W_L3 = 0.4, and W_L4 = 0.5 for the first level.

[0089] Calculate the candidate set Tid_C k Tid in each of the middle m The weight W_Tid m The results are as follows:

[0090] ,

[0091] ,

[0092] .

[0093] After comparison, it was found that 1.68 × 10 −7 If the value is the largest among the three, the trajectory information ({1**. **06, 3*. **83, 3*. **21, 3.80, 771}) corresponding to TrackId (771) is selected and entered into the third-level queue (send preparation queue). After the send period timer (ST) expires, the trajectory information to be sent is sent to the low-altitude management platform.

[0094] By setting different weight values ​​for different levels, the higher the level, the higher the probability of being elected; similarly, the lower the TrackId value, the higher the probability of being elected. This design of the present invention considers the increasing pattern of TrackId allocation and the weight of historical TrackIds, reducing TrackId jumps and ensuring the continuity of trajectory processing.

[0095] Step 3: The low-altitude management platform visualizes the trajectory data reported by the baseband unit.

[0096] This invention solves the problem of unstable and easily changing target trajectory identifiers (TrackId) under asynchronous sensing data from multiple AAUs. By using a weighted election and multi-level caching mechanism, this invention outputs a continuous, stable, and reliable unified trajectory, thereby improving the accuracy and robustness of low-altitude target tracking.

[0097] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A low-altitude sensing system, comprising a low-altitude management platform and a sensing base station system, wherein the sensing base station system includes a baseband unit and an active antenna unit; the active antenna unit detects low-altitude flying targets and generates raw trajectory data containing the longitude, latitude, altitude, speed, and trajectory identifier of the detected target, wherein the trajectory identifier is a natural number incrementing from 1, and the trajectory identifier serves as the trajectory ID of the detected target; characterized in that, The baseband unit performs real-time correlation, deduplication, and trajectory fusion processing based on a four-level cache queue on the original trajectory data to obtain fused trajectory data and reports it to the low-altitude management platform. The baseband unit constructs a four-level buffer queue and starts a periodic algorithm timer; the periodic algorithm timer includes an election timer and a transmission timer; The four-level cache queue includes: First-level queue: Stores the raw trajectory data of newly detected targets, storing the trajectory data detected by the three active antenna units under the baseband unit for the same target at the current moment; Second-level queue: Retrieves trajectory data stored in the first-level queue. This trajectory data contains trajectory information before the trajectory identifier election. The election of trajectory identifiers is triggered when the election timer expires. Third-level queue: Obtain the trajectory information after the second-level queue trajectory identifier election, and send the elected trajectory information to the low-altitude management platform after the sending timer expires; The fourth-level queue stores historical trajectory information that has been sent to the low-altitude management platform, serving as a historical reference to enhance the continuity of the election. The low-altitude management platform provides a visual representation of the trajectory data reported by the baseband unit. The baseband unit clusters the trajectory data reported by different active antenna units: Store all trajectory points from the trajectory data in the first-level queue into the initial set P_List = {P1, ...,P j ,...,P n }, where each trajectory point P j Includes its location information (x) j , y j , z j Temporary track identifier Tid j With speed V j ; j is the index of the P_List object, which is a natural number starting from 1; x j Representing longitude information, the y j Representing latitude information, the z j Represents height information; n is the total number of trajectory points in the initial set P_List; Calculate the pairwise 3D Euclidean distance between all trajectory points in P_List, and group trajectory points whose 3D Euclidean distance is less than a preset distance threshold D_MAX into the same cluster, with each cluster C... k This represents a set of trajectory points initially identified as the same physical target; the resulting cluster set is C_List = {C1, ...,C}. k , ..., C Max_C }, where k is the index of any object in the cluster set, 1≤k≤Max_C; and Max_C is the maximum number of clusters in the C_List. Then, a weighted election is performed on the trajectory identifiers of the trajectory points within the cluster: Iterate through C_List and retrieve each cluster C in turn. k ; Find cluster C k The different temporary trajectory identifiers carried by all trajectory points constitute the candidate set Tid_C k ={Tid1,...,Tid m , ...,Tid Max_T }, where m is Tid_C k The index of any object in the set, 1 ≤ m ≤ Max_T; where Max_T is the cluster set Tid_C. k The maximum number; Calculate the candidate set Tid_C k Tid in each of the middle m The weight W_Tid m ,formula: ； Among them, W_L i Indicates Tid m The weight value of the i-th level queue, the Indicates Tid m The sum of the hierarchical weights of the first to fourth level queues, 1≤i≤4; Finally, select W_Tid. m maximum value of Ti m As cluster C k The final output trajectory identifier is used as the trajectory ID when the BBU sends it to the low-altitude management platform for display.

2. The low-altitude sensing system as described in claim 1, characterized in that, Each baseband unit of the sensing base station system is equipped with three active antenna units. Each active antenna unit is deployed with an azimuth angle of 120° and an elevation angle of 60°. The three active antenna units under the baseband unit together complete 360° low-altitude sensing coverage.

3. A trajectory fusion method for a low-altitude sensing system, the low-altitude sensing system comprising a low-altitude management platform and a sensing base station system, the sensing base station system comprising a baseband unit and an active antenna unit, characterized in that, The method includes: Step 1: The active antenna unit detects low-altitude flying targets and generates raw trajectory data containing the longitude, latitude, altitude, speed and trajectory identifier of the detected target. The trajectory identifier is a natural number that is assigned incrementally starting from 1, and the trajectory identifier serves as the trajectory ID of the detected target. Step 2: The baseband unit performs real-time correlation, deduplication, and trajectory fusion processing based on a four-level cache queue on the original trajectory data to obtain the fused trajectory data and reports it to the low-altitude management platform; In step 2, the baseband unit constructs a four-level buffer queue and starts a periodic algorithm timer; the periodic algorithm timer includes an election timer and a transmission timer; The four-level cache queue includes: First-level queue: Stores the raw trajectory data of newly detected targets, storing the trajectory data detected by the three active antenna units under the baseband unit for the same target at the current moment; Second-level queue: Retrieves trajectory data stored in the first-level queue. This trajectory data contains trajectory information before the trajectory identifier election. The election of trajectory identifiers is triggered when the election timer expires. Third-level queue: Obtain the trajectory information after the second-level queue trajectory identifier election, and send the elected trajectory information to the low-altitude management platform after the sending timer expires; The fourth-level queue stores historical trajectory information that has been sent to the low-altitude management platform, serving as a historical reference to enhance the continuity of the election. Step 3: The low-altitude management platform visualizes the trajectory data reported by the baseband unit; Step 2 includes: Step 21: The baseband unit clusters the trajectory data reported by different active antenna units: Store all trajectory points from the trajectory data in the first-level queue into the initial set P_List = {P1, ...,P j ,...,P n }, where each trajectory point P j Includes its location information (x) j , y j , z j Temporary track identifier Tid j With speed V j ; j is the index of the P_List object, which is a natural number starting from 1; x j Representing longitude information, the y j Representing latitude information, the z j Represents height information; n is the total number of trajectory points in the initial set P_List; Calculate the pairwise 3D Euclidean distance between all trajectory points in P_List, and group trajectory points whose 3D Euclidean distance is less than a preset distance threshold D_MAX into the same cluster, with each cluster C... k This represents a set of trajectory points initially identified as the same physical target; the resulting cluster set is C_List = {C1, ...,C}. k , ..., C Max_C }, where k is the index of any object in the cluster set, 1≤k≤Max_C; and Max_C is the maximum number of clusters in the C_List. Step 22, weighted election of trajectory identifiers for trajectory points within the cluster: Iterate through C_List and retrieve each cluster C in turn. k ; Find cluster C k The different temporary trajectory identifiers carried by all trajectory points constitute the candidate set Tid_C k ={Tid1,...,Tid m , ...,Tid Max_T }, where m is Tid_C k The index of any object in the set, 1 ≤ m ≤ Max_T; where Max_T is the cluster set Tid_C. k The maximum number; Calculate the candidate set Tid_C k Tid in each of the middle m The weight W_Tid m ,formula: ； Among them, W_L i Indicates Tid m The weight value of the i-th level queue, the Indicates Tid m The sum of the hierarchical weights of the first to fourth level queues, 1≤i≤4; Finally, select W_Tid. m maximum value of Ti m As cluster C k The final output trajectory identifier is used as the trajectory ID when the BBU sends it to the low-altitude management platform for display.

4. The trajectory fusion method for a low-altitude sensing system as described in claim 3, characterized in that, Each baseband unit of the sensing base station system is equipped with three active antenna units. Each active antenna unit is deployed with an azimuth angle of 120° and an elevation angle of 60°. The three active antenna units under the baseband unit together complete 360° low-altitude sensing coverage.

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