A low-altitude navigation aircraft real-time monitoring method and system based on multi-source data fusion

Abstract

The application discloses a kind of based on multi-source data fusion's low-altitude navigation aircraft real-time monitoring method and system, belong to flight monitoring technical field, including the following steps: receiving aircraft target characteristic information sent by data link, after the validity verification of target characteristic information, extract target track information;Ground station receives the first track information of multiple groups sent by air traffic radar system, extract aircraft track information;Receive the second track information of multiple groups sent by multiple independent low-altitude monitoring stations, extract unmanned aerial vehicle track information;After time alignment of target track information, aircraft track information and unmanned aerial vehicle track information obtained by ground station, multi-source data fusion is carried out, and target precision information is generated.The application selects the data source closest to the aircraft and the signal quality optimal from the multiple radar tracks and low-altitude monitoring station tracks by using spherical distance as the visual field measurement, and solves the problem of multi-source information conflict.

Description

Technical Field

[0001] This invention relates to the field of flight surveillance technology, specifically to a real-time monitoring method and system for low-altitude general aviation aircraft based on multi-source data fusion. Background Technology

[0002] With the increasing prevalence of mixed operations of general aviation aircraft and drones in low-altitude airspace, existing low-altitude surveillance systems typically rely on a single data source for aircraft position monitoring, such as relying solely on air traffic control radar or solely on ADS-B data links. This makes it difficult to cope with scenarios where multiple types of aircraft coexist in complex low-altitude environments.

[0003] When multiple general aviation aircraft and multiple logistics drones are simultaneously operating in a certain area, the ground monitoring station needs to process multiple data streams from air traffic control radar, low-altitude monitoring stations, and aircraft self-reporting data links. Because the coverage, sampling frequency, and positioning accuracy of different data sources vary, and the timestamps of each data source are inconsistent, the ground station finds it difficult to determine which data source's track information should be used as the standard. This can easily lead to conflicting target location information, track jumps, or target loss, making accurate and continuous monitoring of low-altitude aircraft impossible and posing significant flight safety hazards. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention provides a method and system for real-time monitoring of low-altitude general aviation aircraft based on multi-source data fusion.

[0005] Therefore, the technical problem solved by the present invention is that existing methods are prone to causing target location information conflicts, track jumps, or target loss.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion, comprising the following steps: a ground station receives target characteristic information transmitted by the aircraft via a data link, verifies the validity of the target characteristic information, and extracts target trajectory information; the ground station receives multiple sets of first trajectory information transmitted by an air traffic control radar system, uses the spherical distance between the ground station and the aircraft as a visual field metric, selects the set with the smallest visual field distance from the multiple sets of first trajectory information, and extracts the aircraft trajectory information; the ground station receives multiple sets of second trajectory information transmitted by multiple independent low-altitude monitoring stations, uses the spherical distance between the independent low-altitude monitoring stations and the aircraft as a visual field metric, selects the set with the smallest visual field distance from the multiple sets of second trajectory information, and extracts UAV trajectory information; the ground station performs time alignment on the acquired target trajectory information, aircraft trajectory information, and UAV trajectory information, performs multi-source data fusion through hierarchical deviation judgment, and generates target accuracy information; the ground station evaluates the target flight status based on the target accuracy information, triggers early warning for abnormal states, and implements continuous monitoring.

[0007] As a preferred embodiment of the real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion described in this invention, the process of filtering the aircraft trajectory information includes: obtaining the latitude and longitude values ​​of the ground station, as well as the latitude and longitude values ​​of the aircraft corresponding to each group of first trajectory information; calculating the spherical distance between the aircraft corresponding to each group of first trajectory information and the ground station; arranging the spherical distances corresponding to all groups of first trajectory information in ascending order; selecting the group of first trajectory information with the smallest spherical distance, and sending its corresponding aircraft position information to the ground station as aircraft trajectory information.

[0008] As a preferred embodiment of the real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion described in this invention, the process of filtering UAV trajectory information includes: obtaining the latitude and longitude values ​​of each independent low-altitude monitoring station, as well as the latitude and longitude values ​​of the UAV corresponding to each group of second trajectory information; performing attribute judgment on the independent low-altitude monitoring stations and the target aircraft, and performing corresponding operations based on the judgment results.

[0009] As a preferred embodiment of the real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion described in this invention, the attribute determination step includes: when the independent low-altitude monitoring station and the target aircraft belong to the same platform, only the UAV track information sent by the independent low-altitude monitoring station is received; when the independent low-altitude monitoring station and the target aircraft do not belong to the same platform, the spherical distance between the UAV and the independent low-altitude monitoring station corresponding to each group of second track information is calculated; then the spherical distances corresponding to each group of second track information are arranged in ascending order; the group of second track information with the smallest spherical distance is selected, and its corresponding UAV position information is sent to the ground station as UAV track information.

[0010] As a preferred embodiment of the real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion described in this invention, the multi-source data fusion steps include: time alignment of target trajectory information, aircraft trajectory information, and UAV trajectory information, and uniform interpolation of the timestamps of each data source to the same moment; fusion of the longitude, latitude, and altitude values ​​of the target trajectory information with the corresponding components of the aircraft trajectory information to obtain a first fusion value; fusion of the longitude, latitude, and altitude values ​​of the target trajectory information with the corresponding components of the UAV trajectory information to obtain a second fusion value; fusion of the longitude, latitude, and velocity values ​​of the target trajectory information with the longitude, latitude, latitude, and velocity values ​​of the aircraft trajectory information to obtain a third fusion value; fusion of the longitude, latitude, and velocity values ​​of the target trajectory information with the longitude, latitude, and velocity values ​​of the UAV trajectory information to obtain a fourth fusion value; and outputting the first, second, third, and fourth fusion values ​​as target accuracy information.

[0011] As a preferred embodiment of the real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion described in this invention, the step of obtaining the first fused value includes: calculating the longitude deviation Δλ between the target trajectory information and the aircraft trajectory information; if ε is a set deviation threshold. The longitude value of the target track information is replaced with the longitude value of the aircraft track information to update the target track information. The updated target track information's longitude, latitude, and altitude values ​​are then multiplied sequentially by a first preset correction coefficient to obtain a first fusion value. If... If the original value of the target trajectory information is retained, it is directly multiplied by the first preset correction coefficient as the first fusion value, and the difference of the data group exceeds the limit.

[0012] As a preferred embodiment of the real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion described in this invention, the step of obtaining the second fused value includes: calculating the longitude deviation between the target trajectory information and the UAV trajectory information. ;like Then, the longitude value of the target trajectory information is replaced with the longitude value of the UAV trajectory information to update the target trajectory information. The updated target trajectory information's longitude, latitude, and altitude values ​​are then multiplied sequentially by a second preset correction coefficient to obtain the second fused value. If... If the original value of the target trajectory information is retained, it is directly multiplied by the second preset correction coefficient to obtain the second fusion value, and the difference of this group of data is marked as exceeding the limit.

[0013] As a preferred embodiment of the real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion described in this invention, the step of obtaining the third fusion value includes: calculating the deviation between the longitude value of the target trajectory information and the longitude value of the aircraft trajectory information respectively. The deviation between the latitude values ​​of the target trajectory information and the latitude values ​​of the aircraft trajectory information The deviation between the target trajectory information velocity value and the aircraft trajectory information velocity value ;when , , When both meet their respective deviation thresholds, the target trajectory information is directly replaced with the aircraft trajectory information to complete the update, and the updated value is multiplied by the first preset correction coefficient as the third fusion value; when , , If none of the deviation thresholds are met, the weighting coefficients are determined based on the relative magnitudes of the deviations of each component. and The third fusion value is obtained through weighted fusion processing:

[0014] ;

[0015] ;

[0016] ;

[0017] When the deviation only partially meets the deviation threshold, the component that meets the threshold is replaced and multiplied by the first preset correction coefficient, and the component that does not meet the threshold is weighted and fused. Each component is calculated independently and then combined into the third fused value.

[0018] As a preferred embodiment of the real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion described in this invention, the step of evaluating the target flight status includes: comparing the target accuracy information with the standard trajectory data in the preset flight plan; calculating the deviation between the actual flight parameters of the target aircraft and the standard trajectory data; when all the above deviations are within the preset normal range, the target flight status is determined to be normal, and periodic monitoring continues; when any deviation exceeds the preset normal range, the target flight status is determined to be abnormal, the abnormal information is recorded, and the monitoring frequency is increased.

[0019] This invention provides a real-time monitoring system for low-altitude general aviation aircraft based on multi-source data fusion.

[0020] To address the aforementioned technical problems, this invention provides the following technical solution: a real-time monitoring system for low-altitude general aviation aircraft based on multi-source data fusion, comprising: a data acquisition module for receiving target characteristic information transmitted by the aircraft via a data link and extracting target trajectory information; an aircraft trajectory information extraction module for receiving multiple sets of first trajectory information transmitted by an air traffic control radar system and extracting aircraft trajectory information using the spherical distance between the ground station and the aircraft as a visual field metric; a UAV trajectory information extraction module for receiving multiple sets of second trajectory information transmitted by multiple independent low-altitude monitoring stations and extracting UAV trajectory information using the spherical distance between the independent low-altitude monitoring stations and the aircraft as a visual field metric; and a calculation module for performing time alignment on the acquired target trajectory information, aircraft trajectory information, and UAV trajectory information, performing multi-source data fusion through hierarchical deviation judgment, and generating target accuracy information.

[0021] The beneficial effects of this invention are as follows: using spherical distance as the visible field of view metric, it automatically selects the data source closest to the aircraft and with the best signal quality from multiple sets of radar tracks and low-altitude surveillance station tracks, solving the problem of information conflict from multiple data sources and avoiding track jumps caused by insufficient accuracy of remote data sources. Furthermore, it constructs fusion channels for the position dimension (latitude, longitude, and altitude) and the dynamic dimension (latitude, longitude, and velocity) respectively. Through a three-level layering strategy, it marks and warns of data anomalies while ensuring fusion accuracy, thereby improving the accuracy and reliability of target track information. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 The above is a flowchart of a real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion, provided as an embodiment of the present invention.

[0024] Figure 2 This is a flowchart of a UAV trajectory screening method for real-time monitoring of low-altitude general aviation aircraft based on multi-source data fusion, provided as an embodiment of the present invention.

[0025] Figure 3 This is an overall structural diagram of a real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion, provided as an embodiment of the present invention. Detailed Implementation

[0026] To make the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0027] Example 1, referring to Figure 1 This is one embodiment of the present invention, which provides a real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion, comprising the following steps:

[0028] S1. The ground station receives the target characteristic information sent by the aircraft through the data link, verifies the validity of the target characteristic information, and extracts the target trajectory information.

[0029] S2. The ground station receives multiple sets of first track information sent by the air traffic control radar system. Using the spherical distance between the ground station and the aircraft as the visual field metric, the station selects the set with the smallest visual field distance from the multiple sets of first track information and extracts the aircraft track information.

[0030] S3. The ground station receives multiple sets of second track information sent by multiple independent low-altitude monitoring stations. Using the spherical distance between the independent low-altitude monitoring station and the aircraft as the visual field metric, the station selects the set with the smallest visual field distance from the multiple sets of second track information and extracts the UAV track information.

[0031] S4. After the ground station performs time alignment on the acquired target trajectory information, aircraft trajectory information and UAV trajectory information, it performs multi-source data fusion through hierarchical deviation judgment to generate target accuracy information.

[0032] S5. The ground station assesses the target's flight status based on the target accuracy information, triggers an early warning for abnormal states, and implements continuous monitoring.

[0033] It should be noted that the mixed operation of general aviation aircraft and drones in low-altitude airspace is becoming increasingly common. The low-altitude airspace environment is complex, and different types of aircraft use different data links, monitoring equipment, and signal systems. The track information provided by air traffic control radar, low-altitude surveillance stations, and aircraft self-reporting data links varies significantly in coverage, sampling frequency, and positioning accuracy, and the timestamps of each data source are difficult to align naturally. In typical scenarios where multiple general aviation aircraft and drones share a low-altitude corridor, if ground stations directly use a single data source for monitoring, it is highly susceptible to target position conflicts, track jumps, or even target loss due to blind spots in data source coverage, insufficient accuracy, or time inconsistencies, failing to meet the safety monitoring requirements of low-altitude mixed flight scenarios.

[0034] Therefore, to address the issue of multi-source data fusion monitoring in low-altitude general aviation scenarios, steps S1-S5 are used to automatically select the optimal data source using spherical distance as the visible field metric, resolving information conflicts between multiple data sources. Timestamp-based interpolation ensures time alignment of multi-source data, guaranteeing temporal consistency of the fused data. A hierarchical deviation judgment mechanism is employed to construct fusion channels for both position and dynamic dimensions, using a three-level fusion strategy of replacement, weighting, and independent component processing to generate target accuracy information. Finally, a pre-set standard flight path is combined to achieve graded assessment and real-time early warning of flight status, ensuring accurate and continuous monitoring of low-altitude aircraft by ground stations and guaranteeing flight safety in low-altitude mixed operation scenarios.

[0035] Example 2, refer to Figures 1-3 As an embodiment of the present invention, based on the previous embodiment, a real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion is provided, including:

[0036] S1. The ground station receives the target characteristic information sent by the aircraft through the data link, verifies the validity of the target characteristic information, and extracts the target trajectory information.

[0037] The aircraft continuously transmits target characteristic information to the ground station via a data link. This information includes the aircraft's position, speed, heading, and identification. Upon receiving this information, the ground station verifies its validity. This verification includes data integrity checks, timestamp validity checks, and signal source compliance assessments. Invalid data caused by signal interference or data packet loss is removed. Longitude, latitude, altitude, and speed values ​​are extracted and used as target trajectory information for subsequent processing.

[0038] For example, a general aviation aircraft reports target characteristic information to a ground station once per second via an ADS-B data link. The ground station performs a CRC check on the received data frame. If the check passes, the longitude value (116.45°E), latitude value (39.92°N), altitude value (1200m), and speed value (280km / h) in the frame are extracted as the target track information. If the check fails, the frame is discarded, the anomaly is recorded, and a data link anomaly alarm is triggered.

[0039] S2. The ground station receives multiple sets of first track information sent by the air traffic control radar system. Using the spherical distance between the ground station and the aircraft as the visual field metric, the station selects the set with the smallest visual field distance from the multiple sets of first track information and extracts the aircraft track information.

[0040] The process of filtering aircraft trajectory information includes S2.1 to S2.4:

[0041] S2.1 Obtain the latitude and longitude values ​​of the ground station, as well as the latitude and longitude values ​​of the aircraft corresponding to each group of first track information.

[0042] In this embodiment, three air traffic control radars cover a certain low-altitude surveillance area, denoted as radar stations R1, R2, and R3. Each radar station reports the first track information it detects. The ground station coordinates are... The coordinates of the three sets of first track information corresponding to the aircraft are as follows: R1 reported R2 reporting R3 reporting .

[0043] S2.2. Obtain the spherical distance between the aircraft and the ground station corresponding to the first track information of each group by calculation.

[0044] The calculation formula is expressed as follows:

[0045] ;

[0046] in, For the calculated spherical distance, The average radius of the Earth is taken as 6371 km. , These are the latitude and longitude values ​​of the ground station. , The latitude and longitude values ​​of the target aircraft are used, and all angle values ​​are converted to radians for calculation.

[0047] Taking the first track information reported by R1 as an example, , , , Substituting into the above formula, the spherical distance between the ground station and the corresponding spacecraft R1 is calculated. Similarly, the calculation yields... , .

[0048] S2.3 Arrange the spherical distances corresponding to the first track information of all groups in ascending order.

[0049] S2.4 Select the first track information with the smallest spherical distance and send its corresponding aircraft position information to the ground station as aircraft track information.

[0050] As shown in S2.3, d1 is the smallest. Therefore, the first track information reported by radar station R1 is selected, and its corresponding aircraft position information is sent to the ground station as the aircraft track information.

[0051] S3. The ground station receives multiple sets of second track information sent by multiple independent low-altitude monitoring stations. Using the spherical distance between the independent low-altitude monitoring station and the aircraft as the visual field metric, the station selects the set with the smallest visual field distance from the multiple sets of second track information and extracts the UAV track information.

[0052] Reference Figure 2 As shown, the process of filtering UAV trajectory information includes S3.1~S3.2:

[0053] S3.1 Obtain the latitude and longitude values ​​of each independent low-altitude monitoring station, as well as the latitude and longitude values ​​of the UAVs corresponding to each group of second flight track information.

[0054] For example, within a certain low-altitude surveillance area, there are three independent low-altitude surveillance stations, denoted as surveillance stations L1, L2, and L3, with coordinates as follows: L1 L2 L3 There is currently a target drone in the area. Three monitoring stations have reported their respective detected second flight paths, with the corresponding drone coordinates as follows: L1 reported... L2 reporting L3 reporting .

[0055] S3.2 Perform attribute judgment on independent low-altitude surveillance stations and target aircraft, and execute corresponding operations based on the judgment results.

[0056] The attribute determination steps include A1 and A2:

[0057] A1. When the independent low-altitude surveillance station and the target aircraft belong to the same platform, only the UAV track information sent by the independent low-altitude surveillance station will be received.

[0058] If the target drone and the monitoring station L2 belong to the same operating platform, the ground station directly uses the second track information reported by L2 to determine the corresponding drone location information. The data is sent to the ground station as drone flight path information, eliminating the need to filter and calculate data from other monitoring stations, thus simplifying the processing flow and ensuring the consistency of data sources.

[0059] A2. When the independent low-altitude surveillance station and the target aircraft do not belong to the same platform, the spherical distance between the UAV and the independent low-altitude surveillance station corresponding to each group of second track information is calculated.

[0060] Then arrange the spherical distances corresponding to each group of second track information in ascending order;

[0061] Select the second track information with the smallest spherical distance, and send the corresponding UAV position information to the ground station as UAV track information.

[0062] If the target drone and monitoring stations L1, L2, and L3 do not belong to the same platform, then the spherical distance between each monitoring station and its reported corresponding drone position is calculated sequentially. Taking monitoring station L1 as an example, the spherical distance is calculated as follows: , , , Substituting into the formula, the spherical distance between L1 and the reported drone position is calculated. Similarly, the calculation yields... , .

[0063] Arrange the three sets of spherical distances from smallest to largest. From the arrangement results, we can see... Since the second track information reported by monitoring station L2 is the smallest, its corresponding UAV location information is sent to the ground station as UAV track information for subsequent multi-source fusion processing.

[0064] It should be noted that the introduction of the attribute judgment mechanism allows the drone track information of the same platform to be used directly and preferentially, avoiding unnecessary distance calculation overhead; while for cases of different platforms, spherical distance filtering ensures that the drone track data used comes from the monitoring station with the best detection accuracy.

[0065] S4. After the ground station performs time alignment on the acquired target trajectory information, aircraft trajectory information and UAV trajectory information, it performs multi-source data fusion through hierarchical deviation judgment to generate target accuracy information.

[0066] The steps for multi-source data fusion include S4.1 to S4.6:

[0067] S4.1. Time-align the target trajectory information, aircraft trajectory information, and UAV trajectory information, and interpolate the timestamps of each data source to the same time.

[0068] For example, the timestamp of the target track information is T=10.0s, the timestamp of the aircraft track information is T=9.8s, and the timestamp of the UAV track information is T=10.3s, which is inconsistent. Using T=10.0s as the reference time, linear interpolation is performed on the aircraft track information and the UAV track information respectively, and their position and velocity data are uniformly aligned to the time T=10.0s, eliminating the impact of time asynchrony on fusion accuracy.

[0069] S4.2. The longitude, latitude and altitude values ​​of the target trajectory information are fused with the corresponding components of the aircraft trajectory information to obtain the first fused value.

[0070] The steps to obtain the first fusion value include B1~B3:

[0071] B1. Calculate the longitude deviation Δλ between the target trajectory information and the aircraft trajectory information.

[0072] In this embodiment, the longitude value of the target track information is 116.4500°E, and the longitude value of the aircraft track information is 116.4502°E. Therefore, the longitude deviation Δλ = 116.4502° - 116.4500° = 0.0002°.

[0073] B2, if ε is a set deviation threshold. Then, the longitude value of the target track information is replaced with the longitude value of the aircraft track information to update the target track information. The longitude, latitude and altitude values ​​of the updated target track information are then multiplied by the first preset correction coefficient in sequence to obtain the first fusion value.

[0074] First, set the deviation threshold ε=0.001°. Calculate Δλ=0.0002° from step B1, satisfying |Δλ|≤ε. Then replace the longitude value of the target track information with the longitude value of the aircraft track information, which is 116.4502°E. After the update, the longitude value of the target track information is 116.4502°E, the latitude value is 39.9200°N, and the altitude value is 1200m. Assume the first preset correction coefficient is 0.98. Then the first fused value is longitude = 116.4502°×0.98, latitude = 39.9200°×0.98, and altitude = 1200×0.98 = 1176m.

[0075] B3. If If the original value of the target trajectory information is retained, it is directly multiplied by the first preset correction coefficient as the first fusion value, and the difference of the data group exceeds the limit.

[0076] If the longitude value of the aircraft track information is 116.4600°E, then Δλ=0.0100°, which exceeds the threshold ε=0.001°. Therefore, the original longitude value of the target track information, 116.4500°E, is retained and directly multiplied by the first preset correction coefficient 0.98 to obtain the first fusion value. At the same time, the difference of this set of data is marked as exceeding the limit, prompting the operation and maintenance personnel to pay attention to the abnormal deviation between the two data sources.

[0077] S4.3. The longitude, latitude and altitude values ​​of the target trajectory information are fused with the corresponding components of the UAV trajectory information to obtain the second fused value.

[0078] The steps for obtaining the second fusion value include C1 to C3:

[0079] C1. Calculate the longitude deviation Δλ' between the target trajectory information and the UAV trajectory information.

[0080] In this embodiment, the longitude value of the target track information is 116.4500°E, and the longitude value of the UAV track information is 116.4503°E, so the longitude deviation Δλ' = 0.0003°.

[0081] C2. If |Δλ'|≤ε, then replace the longitude value of the target trajectory information with the longitude value of the UAV trajectory information to update the target trajectory information, and multiply the longitude, latitude and altitude values ​​of the updated target trajectory information by the second preset correction coefficient in sequence to obtain the second fusion value.

[0082] For example, if Δλ'=0.0003°, and |Δλ'|≤ε=0.001°, then the longitude value of the target track information is replaced with the longitude value of the UAV track information, which is 116.4503°E. After the update, the longitude value of the target track information is 116.4503°E, the latitude value is 39.9200°N, and the altitude value is 120m. If the second preset correction coefficient is 0.97, then the second fused value is longitude = 116.4503°×0.97, latitude = 39.9200°×0.97, and altitude = 120×0.97 = 116.4m.

[0083] C3. If |Δλ'|>ε, then retain the original value of the target track information and directly multiply it by the second preset correction coefficient as the second fusion value, and mark the data group as having exceeded the difference limit.

[0084] If the longitude value of the UAV track information is 116.4620°E, then Δλ'=0.0120°, which exceeds the threshold ε=0.001°. Therefore, the original longitude value of the target track information, 116.4500°E, is retained and directly multiplied by the second preset correction coefficient 0.97 to obtain the second fusion value. At the same time, the difference of this set of data is marked as exceeding the limit.

[0085] S4.4. The longitude, latitude, and speed values ​​of the target trajectory information are fused with the longitude, latitude, and speed values ​​of the aircraft trajectory information to obtain the third fused value.

[0086] The steps to obtain the third fusion value include D1~D4:

[0087] D1. Calculate the deviation between the longitude values ​​of the target trajectory information and the longitude values ​​of the aircraft trajectory information. The deviation between the latitude values ​​of the target trajectory information and the latitude values ​​of the aircraft trajectory information The deviation between the target trajectory information velocity value and the aircraft trajectory information velocity value .

[0088] In this embodiment, the target track information has a longitude of 116.4500°E, a latitude of 39.9200°N, and a speed of 280 km / h, while the aircraft track information has a longitude of 116.4502°E, a latitude of 39.9201°N, and a speed of 282 km / h. , , .

[0089] D2, when , , When all values ​​meet their respective deviation thresholds, the target trajectory information is directly replaced with the aircraft trajectory information to complete the update. The updated value is then multiplied by the first preset correction coefficient to obtain the third fusion value.

[0090] For example, let longitude deviation threshold be set. Latitude deviation threshold Speed ​​deviation threshold Calculated from step D1 , , If all three satisfy their respective thresholds, the target trajectory information is directly replaced with the aircraft trajectory information. After the update, the longitude value is 116.4502°E, the latitude value is 39.9201°N, and the speed value is 282km / h. Multiplying by the first preset correction coefficient of 0.98, the third fused value is obtained: longitude = 116.4502° × 0.98, latitude = 39.9201° × 0.98, speed = 282 × 0.98 = 276.36km / h.

[0091] D3, when , , If none of the deviation thresholds are met, the weighting coefficients are determined based on the relative magnitudes of the deviations of each component. and The third fusion value is obtained through weighted fusion processing:

[0092] ;

[0093] ;

[0094] .

[0095] In this embodiment, if , , If all three exceed their respective thresholds, then the weighting coefficients are determined based on the relative magnitudes of the deviations of each component. 0.6 If the value is 0.4, then the third fused value is: longitude = 0.6 × 116.4500° + 0.4 × 116.4502° = 116.4501°E, latitude = 0.6 × 39.9200° + 0.4 × 39.9201° = 39.9200°N, and speed = 0.6 × 280 + 0.4 × 282 = 280.8 km / h.

[0096] D4. When the deviation only partially meets the deviation threshold, the component that meets the threshold is replaced and multiplied by the first preset correction coefficient, and the component that does not meet the threshold is weighted and fused. Each component is calculated independently and then combined into the third fused value.

[0097] like Satisfy threshold, Not meeting the threshold If the threshold is met, the longitude and velocity components are replaced and multiplied by a correction factor of 0.98, and the latitude components are weighted and fused. Each component is calculated independently and then combined.

[0098] S4.5. The longitude, latitude, and speed values ​​of the target trajectory information are fused with the longitude, latitude, and speed values ​​of the UAV trajectory information to obtain the fourth fused value.

[0099] In this embodiment, the target track information has a longitude of 116.4500°E, a latitude of 39.9200°N, and a speed of 65 km / h, while the UAV track information has a longitude of 116.4501°E, a latitude of 39.9200°N, and a speed of 66 km / h. Referring to steps D1 to D4, the deviation of each component is calculated. , , If all three satisfy their respective deviation thresholds, the target trajectory information is directly replaced with the UAV trajectory information and multiplied by the second preset correction coefficient 0.97 to obtain the fourth fusion value: longitude = 116.4501° × 0.97, latitude = 39.9200° × 0.97, speed = 66 × 0.97 = 64.02 km / h.

[0100] S4.6. Output the first fusion value, the second fusion value, the third fusion value, and the fourth fusion value together as the target accuracy information.

[0101] It is important to know that the first and second fusion values ​​reflect the positional accuracy of the target aircraft, while the third and fourth fusion values ​​reflect the dynamic motion accuracy of the target aircraft.

[0102] S5. The ground station assesses the target's flight status based on the target accuracy information, triggers an early warning for abnormal states, and implements continuous monitoring.

[0103] The steps for assessing the target's flight status include S5.1 to S5.4:

[0104] S5.1 Compare the target accuracy information with the standard trajectory data in the preset flight plan.

[0105] For example, the preset flight plan standard track data for a general aviation aircraft is as follows: at time T=10.0s, the standard longitude is 116.4500°E, the standard latitude is 39.9200°N, the standard altitude is 1200m, and the standard speed is 280km / h. The target accuracy information output in step S4 shows that the actual longitude at that time is 116.4501°E, the actual latitude is 39.9201°N, the actual altitude is 1176m, and the actual speed is 276.36km / h. These actual flight parameters are then compared item by item with the standard track data.

[0106] S5.2 Calculate the deviation between the actual flight parameters of the target aircraft and the standard trajectory data.

[0107] Based on the comparison results in step S5.1, calculate the deviations of each parameter: longitude deviation = 116.4501° - 116.4500° = 0.0001°, latitude deviation = 39.9201° - 39.9200° = 0.0001°, altitude deviation = 1200 - 1176 = 24m, speed deviation = 280 - 276.36 = 3.64km / h.

[0108] S5.3 When all the above deviations are within the preset normal range, the target flight status is determined to be normal, and periodic monitoring continues.

[0109] The normal deviation ranges for each parameter are set as follows: longitude deviation threshold 0.005°, latitude deviation threshold 0.005°, altitude deviation threshold 50m, and speed deviation threshold 10km / h.

[0110] The calculated longitude deviation is 0.0001°, latitude deviation is 0.0001°, altitude deviation is 24m, and speed deviation is 3.64km / h. All four deviations are within the preset normal range, so the current flight status of the general aviation aircraft is determined to be normal. The ground station will continue to monitor the target according to the established cycle, with the monitoring cycle remaining at 1 time / second.

[0111] S5.4 When any deviation exceeds the preset normal range, the target flight status is determined to be abnormal, the abnormal information is recorded and the monitoring frequency is increased.

[0112] For example, at time T=25.0s, the target accuracy information output by step S4 shows that the actual altitude of the general aviation aircraft is 1080m. Compared with the standard altitude value of 1200m in the standard track data, the altitude deviation is 120m, which exceeds the preset altitude deviation threshold of 50m. The target flight status is determined to be abnormal.

[0113] The ground station immediately recorded the abnormal information, including the time of the abnormality (T=25.0s), the type of abnormal parameter (altitude deviation exceeding the limit), and the deviation amount (120m). At the same time, the monitoring frequency of the target was increased from 1 time / second to 5 times / second, triggering an early warning and pushing the warning information to the relevant management departments. The target was continuously tracked and monitored until the flight status returned to normal or the flight mission ended.

[0114] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for real-time monitoring of low-altitude general aviation aircraft based on multi-source data fusion, characterized in that, Includes the following steps: The ground station receives target characteristic information sent by the aircraft via data link, verifies the validity of the target characteristic information, and then extracts the target trajectory information. The ground station receives multiple sets of first track information sent by the air traffic control radar system. Using the spherical distance between the ground station and the aircraft as the visual field metric, the station selects the set with the smallest visual field distance from the multiple sets of first track information and extracts the aircraft track information. The ground station receives multiple sets of second track information sent by multiple independent low-altitude monitoring stations. Using the spherical distance between the independent low-altitude monitoring stations and the aircraft as the visual field metric, the station selects the set with the smallest visual field distance from the multiple sets of second track information and extracts the UAV track information. After the ground station performs time alignment on the acquired target trajectory information, aircraft trajectory information and UAV trajectory information, it performs multi-source data fusion through hierarchical deviation judgment to generate target accuracy information. The ground station assesses the target's flight status based on the target accuracy information, triggers early warnings for abnormal states, and implements continuous monitoring.

2. The real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion as described in claim 1, characterized in that, The process of filtering the aircraft flight track information includes: Obtain the latitude and longitude values ​​of the ground station, as well as the latitude and longitude values ​​of the aircraft corresponding to each group of first track information; The spherical distance between the aircraft and the ground station corresponding to the first track information of each group is obtained by calculation; Arrange the spherical distances corresponding to the first track information of all groups in ascending order; Select the first set of track information with the smallest spherical distance, and send the corresponding aircraft position information to the ground station as the aircraft track information.

3. The real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion as described in claim 2, characterized in that, The process of filtering the UAV flight path information includes: Acquire the latitude and longitude values ​​of each independent low-altitude monitoring station, as well as the latitude and longitude values ​​of the UAVs corresponding to each group of second flight track information; The system assesses the attributes of independent low-altitude surveillance stations and target aircraft, and executes corresponding operations based on the assessment results.

4. The real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion as described in claim 3, characterized in that, The steps for determining the attribute include: When the independent low-altitude surveillance station and the target aircraft belong to the same platform, only the UAV track information sent by the independent low-altitude surveillance station will be received. When the independent low-altitude surveillance station and the target aircraft do not belong to the same platform, the spherical distance between the UAV and the independent low-altitude surveillance station corresponding to each group of second track information is calculated. Then arrange the spherical distances corresponding to each group of second track information in ascending order; Select the second track information with the smallest spherical distance, and send the corresponding UAV position information to the ground station as UAV track information.

5. The real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion as described in claim 4, characterized in that, The steps of multi-source data fusion include: Time alignment is performed on target trajectory information, aircraft trajectory information and UAV trajectory information, and the timestamps of each data source are uniformly interpolated to the same time. The longitude, latitude, and altitude values ​​of the target trajectory information are fused with the corresponding components of the aircraft trajectory information to obtain the first fused value; The longitude, latitude, and altitude values ​​of the target trajectory information are fused with the corresponding components of the UAV trajectory information to obtain the second fused value; The longitude, latitude, and speed values ​​of the target trajectory information are fused with the longitude, latitude, and speed values ​​of the aircraft trajectory information to obtain a third fused value. The longitude, latitude, and velocity values ​​of the target trajectory information are fused with the longitude, latitude, and velocity values ​​of the UAV trajectory information to obtain a fourth fused value. The first fusion value, the second fusion value, the third fusion value, and the fourth fusion value are used together as the target accuracy information output.

6. The real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion as described in claim 5, characterized in that, The steps for obtaining the first fusion value include: Calculate the longitude deviation Δλ between the target trajectory information and the aircraft trajectory information; like ε is a set deviation threshold. Then, the longitude value of the target track information is replaced with the longitude value of the aircraft track information to update the target track information. The longitude, latitude and altitude values ​​of the updated target track information are then multiplied by the first preset correction coefficient in sequence to obtain the first fusion value. like If the original value of the target trajectory information is retained, it is directly multiplied by the first preset correction coefficient as the first fusion value, and the difference of the data group exceeds the limit.

7. The real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion as described in claim 6, characterized in that, The steps for obtaining the second fusion value include: Calculate the longitude deviation between the target trajectory information and the UAV trajectory information. ; like Then, the longitude value of the target trajectory information is replaced with the longitude value of the UAV trajectory information to update the target trajectory information. The longitude, latitude and altitude values ​​of the updated target trajectory information are then multiplied by the second preset correction coefficient in sequence to obtain the second fusion value. like If the original value of the target trajectory information is retained, it is directly multiplied by the second preset correction coefficient to obtain the second fusion value, and the difference of this group of data is marked as exceeding the limit.

8. The real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion as described in claim 7, characterized in that, The steps for obtaining the third fusion value include: Calculate the deviation between the longitude values ​​of the target trajectory information and the longitude values ​​of the aircraft trajectory information respectively. The deviation between the latitude values ​​of the target trajectory information and the latitude values ​​of the aircraft trajectory information The deviation between the target trajectory information velocity value and the aircraft trajectory information velocity value ; when , , When all of them meet their respective deviation thresholds, the target trajectory information is directly replaced with the aircraft trajectory information to complete the update, and the updated value is multiplied by the first preset correction coefficient as the third fusion value. when , , If none of the deviation thresholds are met, the weighting coefficients are determined based on the relative magnitudes of the deviations of each component. and The third fusion value is obtained through weighted fusion processing: ； ； ； When the deviation only partially meets the deviation threshold, the component that meets the threshold is replaced and multiplied by the first preset correction coefficient, and the component that does not meet the threshold is weighted and fused. Each component is calculated independently and then combined into the third fused value.

9. A real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion as described in claim 8, characterized in that, The steps for assessing the target's flight status include: The target accuracy information is compared with the standard trajectory data in the preset flight plan. Calculate the deviation between the actual flight parameters of the target aircraft and the standard flight path data; When all the above deviations are within the preset normal range, the target's flight status is determined to be normal, and periodic monitoring continues. When any deviation exceeds the preset normal range, the target flight status is determined to be abnormal, the abnormal information is recorded, and the monitoring frequency is increased.

10. A real-time monitoring system for low-altitude general aviation aircraft based on multi-source data fusion, employing the real-time monitoring method for low-altitude general aviation aircraft based on multi-source data fusion as described in any one of claims 1 to 9, characterized in that, include: The acquisition module is used to receive target characteristic information sent by the aircraft through the data link and extract target trajectory information; The aircraft trajectory information extraction module is used to receive multiple sets of first trajectory information sent by the air traffic control radar system and extract the aircraft trajectory information using the spherical distance between the ground station and the aircraft as the visual field metric. The UAV trajectory information extraction module is used to receive multiple sets of second trajectory information sent by multiple independent low-altitude monitoring stations, and extract UAV trajectory information by using the spherical distance between the independent low-altitude monitoring stations and the aircraft as the visual field metric. The calculation module is used to perform time alignment on the acquired target trajectory information, aircraft trajectory information, and UAV trajectory information, and to perform multi-source data fusion through hierarchical deviation judgment to generate target accuracy information.

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