CN115168787B - Flight trajectory associated tracking method based on speculative calculation - Google Patents
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Abstract
The invention discloses a flight path correlation tracking method based on speculative calculation, which is used for judging that the track points of a tracked original flight object which does not receive track point information for more than the preset time are lost; and estimating the track point of the original flying object after the track point is lost, comparing the received track point information of the new flying object with the estimated track point, if the correlation index between the estimated track point of the original flying object and the track point of the new flying object is within the correlation threshold range, correlating the new flying object to the original flying object with the lost track point, taking the original flying object as the tracked flying object to track, and updating the flying track in real time according to the received track point information of the new flying object. The track point automatic prediction is carried out on the discontinuous track information, and the automatic correlation judgment is carried out through the correlation threshold based on the prediction information and the new information point, so that the organic combination of track prediction and track correlation is realized, and the continuous and stable tracking of the target under the condition that the track point is lost is ensured.
Description
Technical Field
The invention relates to trajectory tracking, in particular to a flight trajectory correlation tracking method based on speculative calculation.
Background
The flight environment in modern geographic space is complex, especially under severe environments such as rescue and relief work, mechanical failure and the like, the guarantee means such as radar, communication and the like are limited, the track points of the flight object are easy to lose, and the tracking of the flight object is often ineffective. Meanwhile, nowadays when unmanned aerial vehicles are widely used, tracking management of unmanned aerial vehicle flight is increasingly important, and the condition that the track points of flying objects are lost in the tracking process often occurs under the influence of factors such as detection means, artificial avoidance and the like. In this case, it is difficult to achieve trajectory correlation of the flying object and maintain continuous tracking of the flying object.
The traditional flight trajectory association tracking method generally aims at target trajectory information acquired by a sensor, and realizes continuous tracking of a flight trajectory under an interference condition through means of trajectory prediction, trajectory association and the like. In the aspect of trajectory prediction, methods such as filtering algorithm estimation, motion model-based estimation, machine learning method-based estimation, and the like are generally adopted. Methods such as filtering algorithm estimation and motion model estimation based need to establish an aircraft kinematics or dynamics model, are high in computational complexity, and cannot meet the real-time requirement. Estimating that the vehicle is in a starting stage based on a machine learning method, wherein the prediction time and the precision of the vehicle are to be verified; in the aspect of track association, methods such as track association based on motion information and track association based on feature information are included. The method models the motion process of the target or models the association probability of the multi-feature information, and the association process is complex and has low timeliness.
The method is complex in calculation, and does not organically combine the track prediction with the track association, so that an operator needs to participate in manual judgment to perform manual association, the operation complexity is increased, the tracking timeliness is influenced, and errors exist in manual judgment.
Disclosure of Invention
The purpose of the invention is as follows: in view of the above disadvantages, the present invention provides a flight trajectory correlation tracking method based on speculative calculation, which automatically correlates a new trajectory after trajectory prediction.
The invention also provides a system for correlating and tracking the flight trajectory based on the speculative calculation.
The technical scheme is as follows: in order to solve the problems, the invention adopts a flight path correlation tracking method based on the speculative calculation, which comprises the following steps:
(1) Receiving track point information of the tracked original flying object, and if the track point information of the tracked original flying object is not received within a preset time, judging that the track point of the original flying object is lost;
(2) Presume the presumed track point of the original flight object after the track point loses, and search for the original flight object in real time;
(3) Receiving the track point information of the new flying object, and calculating the association index between the presumed track point and the track point of the new flying object according to the received track point information of the new flying objectI c ：
Wherein, the first and the second end of the pipe are connected with each other,
is the spatial distance, delta, between the trajectory point of the new flying object and the presumed trajectory point of the original flying objectTIs the difference value between the current moment and the original flying object track point loss moment,k'the presumed heading of the original flying object at the current moment,v'for the presumed velocity of the original flying object at the present moment,k N the heading of the new flying object at the current moment,v N for the velocity of the new flying object at the present moment,v m is the maximum flying speed of the original flying object,ω m is the maximum steering speed of the original flying object,a m is the maximum acceleration of the original flying object,w 1 is the position error weight of the track point,w 2 Is the heading error weight,w 3 As a velocity error weight, havew 1 > 0、w 2 > 0、w 3 >0 andw 1 +w 2 +w 3 =1；
(4) Setting an association thresholdI mc If at allI c ≤I mc And then, associating the new flying object with the original flying object with the lost track point, taking the new flying object as the tracked original flying object for tracking, and taking the received flying track of the new flying object as the flying track of the original flying object.
Further, the track point information received in the step (1) includes the number, coordinates, heading and speed of the flying object. The preset time adopts duration t or n track point information updating cycles.
Further, in the step (2), if the preset flight scheme of the tracked original flying object is known, after the track point of the original flying object is lost, assuming that the original flying object still flies in the original flight scheme, and obtaining the presumed track point of the original flying object after the track point is lost; if the flight scheme of the tracked original flying object is unknown, the uniform linear motion of the flying object is presumed according to the flight track parameters when the track point of the original flying object is lost, and the presumed track point of the original flying object after the track point is lost is obtained.
Further, in the step (2), for the original flying object with the known preset flying scheme, the calculation of the estimation after the loss of the tracking track point includes straight line extrapolation at a constant speed or a uniform speed, extrapolation of a turn at a constant speed, and extrapolation of an intersection point of a crossing straight line segment and a turn segment.
Further, in the step (4), a threshold is associatedI mc The setting is 0.8 to 0.9.
The invention also adopts a flight track association tracking system based on the speculative calculation, which comprises the following components:
the track loss judging module is used for judging that the track points of the original flying object which does not receive the track point information beyond the preset time are lost according to the received track point information of the tracked original flying object;
the track presumption module is used for presuming the track points of the original flying object after the track points are lost;
the correlation index calculation module is used for calculating a correlation index between the presumed track point of the original flying object and the track point of the new flying object;
and the association module is used for associating the new flying object with the association index smaller than the association threshold with the original flying object to be used as the original flying object for tracking.
Has the advantages that: compared with the prior art, the invention has the following remarkable advantages:
(1) The method has the advantages that the discontinuous track information is automatically predicted, automatic correlation judgment is carried out through a correlation threshold based on the prediction information and the new information points, track prediction and track correlation are organically combined, and continuous and stable tracking of the target under the condition that track points are lost is guaranteed.
(2) In the process of track prediction and association, a complex kinematics or dynamics model does not need to be established, complex association calculation does not need to be carried out, and track association tracking timeliness is high.
Drawings
FIG. 1 is a flow chart of a flight trajectory correlation tracking method of the present invention.
FIG. 2 is a schematic diagram of the calculation of the constant or uniform linear extrapolation.
FIG. 3 is a schematic diagram of the present invention for uniform velocity turn extrapolation calculation.
FIG. 4 is a schematic diagram of the extrapolation calculation across the junction of a straight segment and a curved segment in accordance with the present invention.
FIG. 5 is a schematic diagram of a known flight plan trajectory correlation in the present invention.
FIG. 6 is a schematic diagram of the correlation of unknown flight plan trajectories in the present invention.
Detailed Description
As shown in fig. 1, a method for tracking a flight trajectory based on speculative calculation in this embodiment includes the following steps:
step 1) a user sets a tracked original flying object, continuously receives track point information of the original flying object, and generates a flying track of the original flying object according to the received track point information. The track point information comprises the number of the flying objectFIDNortheast coordinate (C)x,y,h) Course of the vehiclekSpeed of the motorvAnd the like.
And step 2) the system does not receive the tracked original flight object track point information within a certain time, and the original flight object track point loss is judged. The certain time for judging the loss of the track points of the flying object is judged by adopting duration t or an updating period n, the updating period takes the updating period of the track points of the tracked flying object received by the system as reference, the time for not receiving the track point information is usually set to last 10 seconds or 3 updating periods of the track points, and the time can be manually set according to the actual condition.
Step 3) when the track point of the original flying object is judged to be lost, starting a track point presumption algorithm by the system, presuming the track point of the original flying object after the track point is lost, searching the original flying object, if a preset flying scheme established by the original flying object is known, presuming that the original flying object still flies according to the original flying scheme after the track point of the original flying object is lost, and presuming calculation of the track point of the original flying object according to the flying scheme to obtain the presumed track point of the original flying object after the track point is lost; if the flight scheme of the original flying object is unknown, the original flying object is presumed to move linearly at a constant speed, and the presumed track point is obtained by presumption calculation according to the track parameter when the flight path disappears.
Step 3.1) for the known situation of the established flight scheme, the state (including flight altitude, speed, course, turning point position, time and the like) of the whole flight process is described in the flight scheme, and the current time is compared with the current timeTComparing with the flight scheme time, judging the flight stage of the current flight object in the flight scheme, and explaining straight line extrapolation at constant speed or uniform speed variation, straight line extrapolation at constant speed turning extrapolation, and extrapolation of the intersection point of crossing straight line segment and turning segment in detail by combining the attached drawings 2, 3 and 4.
And 3.1.1) if the tracked flying object is in the straight flying section when the track point disappears and the flying object is still in the straight flying section at the current moment, performing uniform speed or uniform speed change straight line extrapolation. As shown in FIG. 2, the radar is last before the trace point is lostT 0 The target position of the time report is（x 0 ,y 0 ) Course of coursek 0 At a speed ofv 0 Acceleration ofa 0 The current time isTRecord of deltaT = T - T 0 Then the current time guesses the position (x',y') and the estimated heighth', estimation of headingk', estimated speedv' is calculated as follows:
and 3.1.2) if the flying object is in the constant-speed turning section when the track point disappears and the flying object is still in the constant-speed turning section at the current moment, carrying out constant-speed turning extrapolation. As shown in FIG. 3, the radar is last before the trace point is lostT 0 The time to report the target position is: (x 0 ,y 0 ) Course of coursek 0 At a speed ofv 0 The flying object following a circular arc
FromMPoint is moved toM The center of the arc of the turn isO ', the turning gradient isθThe current time isTRecord of deltaT = T - T 0 Then time period ΔTDistance of flying arc of inner flying objectS= v 0 ·ΔT. At this time, the turning radius of the flying objectRThe calculation formula of (c) is as follows:
the current time guess location (x',y') and the estimated heighth', estimation of headingk', estimated speedv' is calculated as follows:
wherein, the first and the second end of the pipe are connected with each other,nindicating turning direction, left turnn = -1, right turnn =1。
And 3.1.3) if the flying object enters the uniform speed turning section from the linear flying section or changes from the uniform speed turning section to the linear flying section within the presumed time, carrying out extrapolation on the intersection point of the crossing straight line section and the turning section. As shown in FIG. 4, known flight solutions include a turning arc segment
To arrive atNThe time of the spot should bet 1 To arrive atQAt a time oft 2 The disappearance time isT 0 The current time isT。
When in useT 0 < t 1 And ist 1 ≤T< t 2 When the flying object is predicted to enter the uniform speed turning section from the straight flying section within the time, if the straight line extrapolation is carried out according to the step 3.1.1), the prediction is carried outM 'Point' and scheme to positionM ' an error exists. Note deltat=t 1 -T 0 Can be measured according to step 3.1.1) for ΔtPerforming straight line extrapolation to obtain the position of the turning intersection point, and starting from the position point, performing turning extrapolation according to step 3.1.2)T- t 1 The distance in time, this error is eliminated.
When in uset 1 < T 0 < t 2 And is provided witht 2 ≤TIn time, the flying object is supposed to be changed from the constant speed turning section to the straight flying section within the time. If the curve extrapolation according to step 3.1.2) is to be inferredP '' corresponding to the scheme to the positionP ' an error exists. Note deltat= t 2 -T 0 Can be according to step 3.1.2) for ΔtPerforming turn extrapolation to obtain the position of a turn intersection point, and performing straight line extrapolation according to the step 3.1.1) from the position pointT- t 2 The distance in time, this error is eliminated.
Step 3.2) for the situation of unknown established flight scheme, according to the trajectory parameter when the trajectory point of the flight object is lostAnd d, performing extrapolation on the straight line with the estimated motion trend being the uniform speed in detail. As shown in FIG. 2, the radar is last before the trace point is lostT 0 The time report target position is (x 0 ,y 0 ) At a height ofh 0 Course of the flightk 0 At a speed ofv 0 The current time isTRecord of deltaT = T - T 0 Then the current time guesses the position (x',y') and the estimated heighth', estimated coursek', estimated speedvThe calculation formula of' is as follows:
by associating indicatorsI c The estimation error of the estimated track point of the unknown flight scheme flight object obtained by directly using uniform straight line extrapolation can be reduced to a certain extent.
And 4) receiving the newly appeared track points of the flying object by the system, and carrying out correlation judgment on the track points through parameters such as the number of the flying object, the northeast coordinate, the course, the speed and the like.
By calculating the correlation index between the new track point and the presumed track pointI c And performing association judgment. Assuming new flight object track point flight object numberFID N Northeast coordinate (C)x N ,y N ,h N ) Course, coursek N Speed, velocityv N The following is a correlation indexI c The calculation steps are explained in detail.
Step 4.1) calculating the associated index according to the information of the position, the speed and the like of the newly appeared track pointI c The calculation formula is as follows:
wherein the content of the first and second substances,
is the spatial distance, delta, between the trajectory point of the new flying object and the presumed trajectory point of the original flying objectTIs the difference value between the current moment and the original flying object track point loss moment,k'the presumed heading of the original flying object at the current moment,v'for the presumed velocity of the original flying object at the present moment,k N the heading of the new flying object at the current moment,v N the velocity of the new flying object at the current moment,v m the maximum flying speed of the original flying object is,ω m the maximum steering speed of the original flying object is,a m is the maximum acceleration of the original flying object,w 1 is the position error weight of the track point,w 2 Is the heading error weight,w 3 As a velocity error weight, havew 1 > 0、w 2 > 0、w 3 >0 andw 1 +w 2 +w 3 =1。
step 5) if the locus point of the newly appeared flying object and the correlation index of the presumed locus pointI c At a certain correlation thresholdI mc In, i.e.I c ≤I mc Then a correlation is automatically made to associate the newly emerging flying object to the tracked flying object. Will generally beI mc The setting is 0.8 to 0.9.
And 6) continuously updating the flight track by using the new flight object track point information through the system, and automatically and continuously tracking.
As shown in fig. 5, the tracked flying object is known as a flying object with the number CA8001, and the flying scheme is as follows:
table 1 flying object flight plan with number CA8001
The system receives the target northeast coordinates of number CA8001 from radar at 13330.0km, 98.0km,8000m) Course of the flight0.78radAt a speed of900 km/h. In comparison to the flight scenario of Table 1, the aircraft is in the straight flight segment 2. And after 10 seconds, the system does not receive the update of the target track point, judges that the track point is lost, and starts track point speculation.
13.
13, 35 to 46, and comparing the flight schedule of table 1, the aircraft enters the constant velocity turnaround section 2, and the system performs extrapolation across the intersection of the straight line section and the turnaround section in step 3.1.3) to form the presumed trajectory point as shown in fig. 5.
The system receives target track point data of 3 newly-appeared flying objects reported by a radar near the presumed track point at the following steps of 13: target flying object number L2001, northeast coordinates ((r))505.0km,150.0km,8000m) Course of the flight0.1radAt a speed of900 km/h(ii) a Target flying object number L2002, northeast coordinates ((s))480.0km,85.0km, 8000m) Course of course-0.5radAt a speed of900 km/h(ii) a Target, northeast coordinates of number L2003 ((ii))520.0km,220.0km, 8000m) Course of the flight0.1radAt a speed of850km/h. And automatically associating the target with the number L2001 according to the presumed track, and realizing continuous tracking of the target.
As shown in fig. 6, the tracked flying object is known as a flying object with the number CA8001, but the flying scheme of the flying object is unknown.
The system receives the target northeast coordinate of number CA8001 reported by the radar at 13330.0km, 98.0km,8000m) Course of the flight0.78radAt a speed of900 km/h. And after 10 seconds, the system does not receive the update of the target track point, judges that the track point is lost, presumes that the flying object moves linearly at a constant speed, and starts track point presumption.
13.
The system receives 2 pieces of target track point data reported by a radar near the presumed track point at 13: target, northeast coordinates of number L2001: (345.0km,113.0km,8000m) Course of the flight0.35radAt a speed of800 km/h(ii) a Target number L2002, northeast coordinates: (322.0km,110.0km,8000m) Course of the flight0At a speed of900 km/h. The system automatically associates the target with the number L2001 according to the presumed track, and realizes continuous tracking of the target.
Claims (9)
1. A flight path correlation tracking method based on speculative calculation is characterized in that,
the method comprises the following steps:
(1) Receiving track point information of the tracked original flying object, and if the track point information of the tracked original flying object is not received within a preset time, judging that the track point of the original flying object is lost;
(2) Presume the presumed track point of the original flight object after the track point loses, and search for the original flight object in real time;
(3) Receiving the track point information of the new flying object, and calculating the association index between the presumed track point and the track point of the new flying object according to the received track point information of the new flying objectI c ：
Wherein the content of the first and second substances,
is the spatial distance, delta, between the trajectory point of the new flying object and the presumed trajectory point of the original flying objectTIs the difference value between the current moment and the loss moment of the track point of the original flying object,k'the presumed heading of the original flying object at the current moment,v'for the original flight at the current momentThe presumed speed of the line object is,k N the heading of the new flying object at the current moment,v N the velocity of the new flying object at the current moment,v m the maximum flying speed of the original flying object is,ω m is the maximum steering speed of the original flying object,a m is the maximum acceleration of the original flying object,w 1 is the position error weight of the track point,w 2 Is the heading error weight,w 3 As the velocity error weight, havew 1 > 0、w 2 > 0、w 3 >0 andw 1 +w 2 +w 3 =1；
(4) Setting an association thresholdI mc If at allI c ≤I mc And then, associating the new flying object with the original flying object with the lost track point, taking the new flying object as the tracked original flying object for tracking, and taking the received flying track of the new flying object as the flying track of the original flying object.
2. The flight trajectory correlation tracking method according to claim 1, characterized in that the trajectory point information received in step (1) comprises the number, coordinates, heading and speed of the flying object.
3. The flight trajectory correlation tracking method according to claim 1, wherein the preset time is duration t or n track point information updating cycles.
4. The associated tracking method for the flight trajectory according to claim 1, characterized in that in the step (2), if the preset flight scheme of the tracked original flying object is known, after the track point of the original flying object is lost, the presumed track point of the original flying object after the track point is lost is obtained assuming that the original flying object still flies according to the original flight scheme; if the flight scheme of the tracked original flying object is unknown, the uniform linear motion of the flying object is presumed according to the flight track parameters when the track point of the original flying object is lost, and the presumed track point of the original flying object after the track point is lost is obtained.
5. The flight trajectory correlation tracking method according to claim 4, wherein in the step (2), for the original flying object with the known preset flight plan, the calculation of the inference after the loss of the tracking trajectory point comprises straight line extrapolation at constant speed or even variation speed, straight line extrapolation at constant speed turning extrapolation, extrapolation across the intersection point of the straight line segment and the turning segment.
6. The flight trajectory correlation tracking method according to claim 1, wherein in the step (4), a correlation threshold is setI mc The setting is 0.8 to 0.9.
7. A system for applying the conjecture-calculation-based flight trajectory correlation tracking method of claim 1, comprising:
the track loss judging module is used for judging the loss of the original flying object track points of which the track point information is not received within the preset time according to the received track point information of the tracked original flying object;
the track presumption module is used for presuming the track points of the original flying object after the track points are lost;
the correlation index calculation module is used for calculating a correlation index between the presumed track point of the original flying object and the track point of the new flying object;
and the association module is used for associating the new flying object with the association index smaller than the association threshold with the original flying object to be used as the original flying object for tracking.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method of any one of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104596544A (en) * | 2015-01-23 | 2015-05-06 | 北京航空航天大学 | Method for predicting airborne navigation performances under ionospheric scintillation |
| CN110017838A (en) * | 2019-02-13 | 2019-07-16 | 浩亚信息科技有限公司 | Schedule flight trajectory predictions method, equipment, medium and system |
| CN110032710A (en) * | 2019-02-27 | 2019-07-19 | 中国人民解放军空军工程大学 | A kind of improved JPDA plot-track Association Algorithm |
| CN110060281A (en) * | 2019-03-25 | 2019-07-26 | 同济大学 | A kind of ship and over-water floats trajectory track system |
| CN110135314A (en) * | 2019-05-07 | 2019-08-16 | 电子科技大学 | A kind of multi-object tracking method based on depth Trajectory prediction |
| CN110596694A (en) * | 2019-09-20 | 2019-12-20 | 吉林大学 | Complex environment radar multi-target tracking and road running environment prediction method |
| CN111316127A (en) * | 2018-12-29 | 2020-06-19 | 深圳市大疆创新科技有限公司 | Target track determining method, target tracking system and vehicle |
| CN111983601A (en) * | 2020-07-17 | 2020-11-24 | 北京理工大学 | Group target tracking track starting method based on Bayesian principle |
| CN112509032A (en) * | 2020-11-24 | 2021-03-16 | 江苏大学 | Design method of front sensing module based on automobile distributed sensing platform |
| CN112946626A (en) * | 2021-03-11 | 2021-06-11 | 中国电子科技集团公司第三十八研究所 | Airborne phased array radar track correlation method |
| JP2021169936A (en) * | 2020-04-14 | 2021-10-28 | 日本電気株式会社 | Target tracking device, target tracking system, target tracking method and target tracking program |
| CN113673787A (en) * | 2021-09-10 | 2021-11-19 | 中国舰船研究设计中心 | Unmanned cluster multi-domain detection data track association and prediction method |
| CN113870624A (en) * | 2021-12-02 | 2021-12-31 | 中国电子科技集团公司第二十八研究所 | Low-altitude airspace channel planning and management method |
| CN114090718A (en) * | 2022-01-11 | 2022-02-25 | 中国人民解放军海军工程大学 | Bi-LSTM prediction and fuzzy analysis based interrupted track correlation method |
| CN114663471A (en) * | 2022-02-17 | 2022-06-24 | 深圳大学 | Target tracking method and device and computer readable storage medium |
| CN114690178A (en) * | 2020-12-25 | 2022-07-01 | 杭州海康威视数字技术股份有限公司 | Target tracking method, device, equipment and storage medium |
| CN114972418A (en) * | 2022-03-30 | 2022-08-30 | 北京航空航天大学 | Maneuvering multi-target tracking method based on combination of nuclear adaptive filtering and YOLOX detection |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050163249A1 (en) * | 2004-01-27 | 2005-07-28 | Crestcom, Inc. | Predistortion circuit and method for compensating linear distortion in a digital RF communications transmitter |
| US11521382B2 (en) * | 2020-02-09 | 2022-12-06 | Stout Industrial Technology, Inc. | Machine vision plant tracking system for precision agriculture |
-
2022
- 2022-09-05 CN CN202211076776.2A patent/CN115168787B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104596544A (en) * | 2015-01-23 | 2015-05-06 | 北京航空航天大学 | Method for predicting airborne navigation performances under ionospheric scintillation |
| CN111316127A (en) * | 2018-12-29 | 2020-06-19 | 深圳市大疆创新科技有限公司 | Target track determining method, target tracking system and vehicle |
| CN110017838A (en) * | 2019-02-13 | 2019-07-16 | 浩亚信息科技有限公司 | Schedule flight trajectory predictions method, equipment, medium and system |
| CN110032710A (en) * | 2019-02-27 | 2019-07-19 | 中国人民解放军空军工程大学 | A kind of improved JPDA plot-track Association Algorithm |
| CN110060281A (en) * | 2019-03-25 | 2019-07-26 | 同济大学 | A kind of ship and over-water floats trajectory track system |
| CN110135314A (en) * | 2019-05-07 | 2019-08-16 | 电子科技大学 | A kind of multi-object tracking method based on depth Trajectory prediction |
| CN110596694A (en) * | 2019-09-20 | 2019-12-20 | 吉林大学 | Complex environment radar multi-target tracking and road running environment prediction method |
| JP2021169936A (en) * | 2020-04-14 | 2021-10-28 | 日本電気株式会社 | Target tracking device, target tracking system, target tracking method and target tracking program |
| CN111983601A (en) * | 2020-07-17 | 2020-11-24 | 北京理工大学 | Group target tracking track starting method based on Bayesian principle |
| CN112509032A (en) * | 2020-11-24 | 2021-03-16 | 江苏大学 | Design method of front sensing module based on automobile distributed sensing platform |
| CN114690178A (en) * | 2020-12-25 | 2022-07-01 | 杭州海康威视数字技术股份有限公司 | Target tracking method, device, equipment and storage medium |
| CN112946626A (en) * | 2021-03-11 | 2021-06-11 | 中国电子科技集团公司第三十八研究所 | Airborne phased array radar track correlation method |
| CN113673787A (en) * | 2021-09-10 | 2021-11-19 | 中国舰船研究设计中心 | Unmanned cluster multi-domain detection data track association and prediction method |
| CN113870624A (en) * | 2021-12-02 | 2021-12-31 | 中国电子科技集团公司第二十八研究所 | Low-altitude airspace channel planning and management method |
| CN114090718A (en) * | 2022-01-11 | 2022-02-25 | 中国人民解放军海军工程大学 | Bi-LSTM prediction and fuzzy analysis based interrupted track correlation method |
| CN114663471A (en) * | 2022-02-17 | 2022-06-24 | 深圳大学 | Target tracking method and device and computer readable storage medium |
| CN114972418A (en) * | 2022-03-30 | 2022-08-30 | 北京航空航天大学 | Maneuvering multi-target tracking method based on combination of nuclear adaptive filtering and YOLOX detection |
Non-Patent Citations (3)
| Title |
|---|
| 一种基于动态RCS的航路规划方法;钱海力;《电子技术与软件工程》;20200315(第06期);第81-82页 * |
| 一种基于动态规划的点目标轨迹关联算法;钟圣芳等;《计算机测量与控制》;20040825(第08期);第772-775页 * |
| 一种新的基于统计的航迹关联算法;张章等;《计算机应用与软件》;20120815(第08期);第269-271页 * |
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