CN104808197A - Multi-surveillance-source flying target parallel track processing method - Google Patents
Multi-surveillance-source flying target parallel track processing method Download PDFInfo
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Abstract
The invention discloses a multi-surveillance-source flying target parallel track processing method. The method includes the steps: multi-surveillance-source data receiving; multi-surveillance-source data analysis; radar data processing; ADS-B (automatic dependent surveillance-broadcast) data processing; multi-surveillance-source data fusion. Surveillance of quality of data accessing to radar is realized by monitoring and analyzing quality of radar signals. In addition, real-time receive processing of the radar data is realized by means of multithreading, high safety, high reliability and high usability of a data processing system can be further guaranteed, and accuracy and quickness in track processing of flying targets in different data types from different surveillance sources can be realized.
Description
Technical field
The present invention relates to a kind of many supervision source airbound target Parallel Tracking disposal route.
Background technology
Current, air traffic control substantially depends on radar surveillance and communicates with very high frequency(VHF) (VHF), these two kinds of means are all limited to line-of-sight propagation, cover beneficial scope relatively little, general radar surveillance only covers on air route, and in wide spatial domain, ocean and outlying mountain, desert or spatial domain, jungle area, due to the restriction of various factors, radar and VHF covering cannot be realized, cause the blind area of flying area, bring hidden danger to flight safety.For overcoming these shortcomings, realize effective air traffic surveillance, International Civil Aviation Organization (ICAO:International CivilAviationOrganization): put forward a kind of supervision concept newly, the air traffic surveillance in future is based upon on the basis of applied satellite technology, Here it is automatic dependent surveillance (ADS:AutomaticDependent Surveillance).International Civil Aviation Organization 1992 annual general meeting formally by the new air navigation system scheme based on satellite navigation, satellite communication communicate with Data-Link, thus starts air traffic control from existing ground-based system to new navigation system transition.New navigation system is by communicating, navigating, monitor and air traffic control 4 parts form, wherein supervision and automatic dependent surveillance, it is by the four-dimensional position data of the Navigation and localization system measurement aircraft on aircraft, automatically deliver to terrestrial air traffic control center by earth-space communication Data-Link, carry out air traffic control and traffic management.Therefore, after introducing new navigation system, the means of multiple supervision aircraft are just there are, as radar, ADS-B etc., if can by monitoring source from difference, not in the same time, the monitoring data of different coordinates merges, and just can realize Multi folds coverage, expand the scope of monitoring and controlling, improve target location accuracy, increase reliability forecasting, thus ensure the security of flight, the high efficiency of area of space utilization.
Data fusion technique is in brief namely: carry out overall treatment from multiple sensor or multi-source information, thus obtains more accurate, conclusion reliably.Stricter definition is namely: utilize computer technology to the observation information of the some sensors obtained chronologically in addition automatic analysis, comprehensive under certain criterion, the information process carried out to complete the decision-making of needs and estimation task.
The shortcoming that prior art exists is as follows:
1, monitor that source data disposal system Yin Jiege road monitors that source signal quality is directly connected to the quality merging signal, existing ATC system monitors and has some limitations in source signal Analysis of Quality Control drawing to connect more.
2, to radar data processing module, parameter is the geographic coordinate of each radar signal Format Type and speed, radar antenna position and magnetic bias angle, antenna rotation rate mainly, track initiation value, the flight path stop value of flight path quality management, the multi-radar data fusion threshold parameter value such as correlation distance, relevant height, relevant speed, relevant course, the static weighted value of all radar participation fusions during many radar fusion and Dynamic weighting values etc.In existing system employing program, the method for cure parameter is configured radar parameter, cannot modify to parameters such as the static weighted value of Radar Data Fusion thresholding, all radars participation fusion and Dynamic weighting values, any variation of these parameters all needs the technical support of programmer, lack dirigibility, poor operability.
3, follow the tracks of in processing procedure at radar data, data receiver, decoding, process are high to requirement of real-time, in radar disposal system, adopt single-threaded programming technique, radar data receives and follow the tracks of cycle for the treatment of to carry out, easily cause loss of data phenomenon, can radar terminal receive radar data in real time and accurately and seem particularly important.
Summary of the invention
In order to overcome the shortcoming of prior art, the invention provides a kind of many supervision source airbound target Parallel Tracking disposal route, by carrying out monitoring analysis to radar signal quality, monitoring the quality of data of access radar; Adopt multithreading to realize the real-time reception process of radar data simultaneously, guarantee the high security of data handling system, high reliability and high availability further, process monitors source different types of data airbound target from difference can be followed the tracks of quickly and accurately.
The technical solution adopted in the present invention is: a kind of many supervision source airbound target Parallel Tracking disposal route, comprises the steps:
Step one, many supervision source datas receive;
Step 2, many supervision source datas are resolved: carry out the differentiation of type of message information to the raw data that step one receives, then calling data resolver is resolved data, and all kinds of message datas parsed are carried out normalization process, be then stored in internal data table;
Step 3, radar data process:
(1) real-time quality controls;
(2) radar data pre-service;
(3) radar data process: comprise single radar tracking process and the process of many radar fusion;
Step 4, ADS-B data processing: generate single ADS-B flight path and ADS-B fusion flight path, and by flight path stored in ADS-B flight path table;
Step 5, many supervision source datas merge:
(1) system track association;
(2) system Track In Track;
(3) ADS-B flight path and radar track merge.
Compared with prior art, good effect of the present invention is:
1, in radar data processing procedure, adopt Multi-thread control structure, use the concurrent mode combined with serial to realize the process of the different types of data of each radar, effectively control the quantity of radar data processing threads, to the demand of internal memory and CPU when alleviating system cloud gray model, also meet the requirement of radar data process real-time simultaneously.
2, invention introduces for radar signal quality monitoring, by the frame loss condition of real-time police radar data, conveniently check some mark (flight path) data of each road radar signal.By arranging System Fault Tolerance parameter, system can carry out follow-up fusion treatment by the radar that meets the demands of automatic selecting signal quality.
3, the present invention adopts visualization interface to be configured radar parameter.Radar parameter value and data fusion threshold parameter value, the parameters such as the static weighted value how radar participation all during radar fusion merged and Dynamic weighting values, employing visualization interface configures, system user of service just can revise corresponding parameter value according to configuration needs on use seat, configuration is succinct, flexible, convenient, workable.
4, the supervision source of monitor message provided by the invention is made up of multiple supervision sources such as primary radar, secondary radar, ADS-B, and this is a typical multisensor function synthetic schemes.ADS-B data and many radars are combined and can realize Multi folds coverage, expands the scope of monitoring and controlling, improve target location accuracy, increase reliability forecasting, thus the high efficiency that the security of guarantee flight and area of space utilize.
5, the data fusion of many radars and ADS-B adopts distributed fusion structure, and this structure tracing property is good, and requires low to communication bandwidth, and computing velocity is fast, good reliability.
Accompanying drawing explanation
Examples of the present invention will be described by way of reference to the accompanying drawings, wherein:
Fig. 1 is many supervision source of the present invention airbound target Parallel Tracking processing flow chart;
Fig. 2 is the process flow diagram that source data receives that monitors of the present invention more;
Fig. 3 is the schematic diagram of the earth's core fixed coordinate system;
Fig. 4 is the process flow diagram of single radar data process of the present invention;
Fig. 5 is the process flow diagram of many radar fusion data processing of the present invention;
Fig. 6 is radar track association process flow diagram;
Fig. 7 is the distributed Fusion Model schematic diagram of many radars and ADS-B flight path;
Embodiment
Many supervision source airbound target Parallel Tracking disposal system of the present invention's design comprises data receiver, data prediction, radar data process, ADS-B data processing and fused data process five part, and its flow process as shown in Figure 1.
In the airbound target Parallel Tracking process of many supervision source, first each radar head data and ADS-B data acquisition to be got off, and be stored in database.Then need to verify these data, classify and reject partial error data.The Targets Dots obtained within single radar single pass cycle, uses radar processor to carry out tracking process to these Targets Dots, generates single radar track data, and provide the state estimation of target.Meanwhile, the local flight path of radar is generated by multi-radar data processing.According to same treatment scheme, process ADS-B point mark, generates single ADS-B flight path and the local flight path of ADS-B.Local for radar flight path and the local flight path of ADS-B are sent into fusion treatment module and carries out system track association and fusion, the final tracing and monitoring realized airbound target on a large scale.
Concrete implementation step is as follows:
Step one, many supervision source datas receive (reception to raw data)
The physical layer interface of raw data receiver module is network interface, and by interface that kit provides, receive raw data, then the raw data received is submitted to pretreatment module, according to different agreements, raw data is resolved, CRC check, calculating, process, be deposited into database after being disposed.
The upper strata of data receiver is database, be oracle database, the raw information, configuration information etc. of equipment are all configured by visualization interface herein, preserve in a database, Data classification work data reception module reads after configuration from database, then carries out data receiver.
Consider that the supervision source of airbound target is many, in order to ensure the real-time of software data processing, software can use multithreading, ensures that data can high-speed receiving, prevents buffer zone from piling with spillings, obliterated data, reach the requirement processed in real time.After software startup, loading agreement is set by according to the radar parameter in database, and initialization services, comprising receiving port and protocol type etc.Open thread, be responsible for monitoring the port of specifying.
As shown in Figure 2, the flow process monitoring that source data receives as follows more:
1. building database connects, from data source parameter configuration table, read data source information, if read data to provide exceptional value in log recording, and quits a program.
2. create corresponding data sink according to the IP address of data source, port, data type, data subtypes, each data sink is a thread.
3. start thread, receive the raw data of corresponding port.
4. receiver thread is by the raw data that receives stored in raw data base, waits for subsequent treatment.
Step 2, many supervision source datas are resolved
Raw data is carried out the differentiation of type of message information by Data Analysis, call ADS-B data parser or SSR data parser is resolved data, and convert all kinds of message datas parsed to normalized monitoring data form, be stored in internal data table.
Data resolution module adopts multithreading to realize, and resolving is divided into three steps: digital independent, data processing, data are preserved.
1. start digital independent thread, from raw data base, read raw data.
2. start the processing threads of respective type according to the data type of raw data, to raw data normalization process.Normalization process can be divided into data prediction, sorter, data parser and format converter.
Sorter differentiates according to the type of message information that receives, and call corresponding resolver and resolve data.In data decoding procedure, have employed version processing policy: when receiving message, searching SAC|SIC corresponding in version cache table with or without colophon according to SAC and SIC in message, if having, using this version analytic message; If without version or have version but resolve unsuccessful, then other versions attempted from high to low are resolved, if there is a successfully resolved, are recorded to for resolving next time in buffer memory corresponding to SAC|SIC, if resolve all unsuccessful, return parse error.When using some versions to carry out data decode, complete following steps:
Message is verified first: checking message length whether at least 3 bytes; Whether type of message (message first character joint) mates with resolver; Whether message length is consistent with the numerical value of message length field.If be verified, carry out next step, otherwise stop resolving and returning parse error;
Resolve SAC, SIC information, the version number used when searching its successfully resolved last time according to the value of message SAC|SIC;
Attempt resolving: if version when finding successfully resolved last time, then according to this version analytic message, if do not find, attempt successively resolving with each version, if there is a version successfully resolved, then the version recording the message that this SAC|SIC stands was resolved for next time; If all unsuccessful, then return parse error.
Its each data item of the message of successfully resolved is kept in resolver built-in variable, uses as default, can generate SQL statement as required during successfully resolved, for being updated in database for the data item do not provided in message.
Data prediction is in data identification and normalisation process, carries out dealing of abnormal data and quality of data supervision and adds up.When the oblique distance difference of enrolling the continuous multiple spot of data is zero, is just regarded as to follow the tracks of and loses; When certain point or certain several point and front and back data difference of enrolling data are obviously greater than normal difference, be regarded as hop.The statistics of exceptional value adds counter in a program, the number of recording exceptional data, and when the ratio of abnormal data and total data is greater than the fault-tolerant value of system, data are considered as invalid.The fault-tolerant value of system can be arranged in the software of radar signal Analysis of Quality Control record.Raw data pre-service, for large section obliterated data, is directly rejected.Corresponding algorithm is applied for hop data calculate, and recovered.
Data processing is according to the data type read from database, and when there being message to receive, main thread is opened by-pass journey and classified and Data Format Transform to raw data, and main thread continues to monitor.After by-pass journey receives raw data from main thread, according to agreement, School Affairs Preliminary Analysis is carried out to data, obtain the data type of raw data, comprise monitoring data, aftn message data (flight planning, navigational intelligence, meteorologic information), flight traffic monitoring, airspace operation, blank pipe infrastructure.By-pass journey is by after data processing, and according to agreement, stored in database, after confirming, by-pass journey life terminates.There is mistake in period, enters fault-tolerant processing module.Software receives the termination order that user sends, and after the data that are disposed, stops main thread.
3. start data storage threads, the data after resolving are stored in corresponding data prediction table, in order to follow-up use.
Step 3, radar data process
Consider that the supervision source of airbound target is many, in order to ensure the real-time of software data processing, the design of software have employed a two-dimentional Multi-thread control structure, thus can expanding system and can fast processing many radars website relatively easily.
Because the speed dependent of radar data process is in the reading of radar data, need whether to complete in the transmission of prior police radar data, arrive once in the every 4s of radar data, therefore within 4s, namely before next radar data arrives, the radar data process of all websites must be completed.The data processing of each radar station is realized by thread, and program controls the process of each radar different types of data by Multi-thread control structure.Due to self existing mode serial data reading of thread of the different types of data of each radar, to avoid between radar and the conflict of data access between the different types of data of radar, simultaneously also without the need to using the access of other mechanism control data.
The present invention devises a Multi-thread control structure, and this control structure can be regarded as the two-dimensional array of the capable n row of m, wherein row defines needs M kind radar data type to be processed, and row define the N number of radar website needing monitoring.Here represent this two bit array with Control [M] [N], Control [i] [j] then illustrates i-th data type of process process that whether can start a jth radar website.Control [i] [j]=true, the then current process that can start the data type i of radar website j.Control if [i] [j]=false, then show to be disposed to i-th data type of radar website or etc. pending.Can be easy to realize by Multi-thread control structure and process the radar data of each radar website, different types of data.Ruuning situation according to reality shows, it not the different types of data simultaneously processing all radar websites concomitantly, but adopt the mode that above-mentioned concurrent and serial is combined, effectively control the quantity of radar data processing threads, to the demand of internal memory and CPU when alleviating system cloud gray model, do not affect the real-time of radar data process simultaneously yet.
1. start digital independent thread, from data prediction table, read normalized radar data.
2., according to the data type of radar website and normalization radar, start corresponding thread and complete process to radar data.
The field that radar data processes paired all kinds of radar standardizing number certificate is resolved, and generates single radar track and many radar tracks.This resume module can be divided into real-time quality control, radar data pre-service, radar data process.
As shown in Figure 4, radar data treatment scheme is as follows:
1) overload process, station state judge
Radar station data source is monitored in real time, evaluates station data quality and make correct response in time; The flow of radar source data is monitored, during overload, produces acceptable spilling, and do corresponding alarming processing; Quality gating is carried out to the supervision source signal of dual input.
Radar data process real-time quality controls to comprise the monitoring of radar station data source real-time quality, overload process and radar data passage than choosing:
A) radar station data source real-time quality monitoring.By process radar land station status report, obtain station state value, evaluate station data quality, and by the status information of website stored in database.
B) radar data overload process.Monitoring data process software accepts a flight path/mark data of multiple stage land station simultaneously, its single station flight path processing and multi-site Data Fusion ability be according to each website and radar data budget flow, just in time can complete Processing tasks design by 50% of the system of use maximum processing capability.For preventing radar station point data from overloading, can the total amount of certain all kinds of message in supervision source that obtains of real-time statistics, real-time assessment its whether exceed permissible flow.Once exceed the adaptability thresholding of setting, software will cut off this station data immediately and use part to export to data processing module and data, till detecting that the data stream recovery of this website is normal.
C) radar data passage is than choosing.Radar data passage is carry out quality gating to the supervision source signal of dual input than choosing, and by setting-up time unit, the quality quantification index of real-time dynamic monitoring each road radar signal, signal quality produces alarm lower than during the metrics-thresholds arranged.
2) radar data pre-service
Radar data pre-service comprises data validity inspection, coordinate conversion and space-time aligning etc.
A) validity check
Data validity inspection comprises altitude information inspection and speed data inspection.In height velocity checks, barometer altitude correction can be carried out according to QNH value, carry out QNH Data Update, QNH multidomain treat-ment, height layer and height conversion process by automatically processing weather information and manually inputting.
B) coordinate conversion
Coordinate conversion be by the position provided in message, highly, under the data such as speed are transformed into unified ECEF coordinate system.Coordinate conversion comprises the coordinate conversion of positional information and velocity information.ECEF coordinate system (ECEF) represents earth meridian circle sectional view, and as shown in Figure 3: C is the earth's core, N is the arctic, and S is the South Pole, and EF is equator, and HK is the ground level of observation station O, the vertical HK of OP.The parallel SN of OM, the angle of it and OH is the geographic latitude of φ, φ i.e. O point, and angle OPF equals φ.
C) space-time calibration
Due to local radar each own different scan period and synchronous clock, except a unified coordinate space, also need a unified time reference, kinematics parameters in all track data is moved on the time point of one-period all on a timeline, and this is that track association and fusion treatment are necessary.After space-time is aimed at, the data of many radars are all unified in the same coordinate system, and data obtain alignment in time.
1. data space technique of alignment
It is exactly selection frame of reference that so-called data space is aimed at, all same under this coordinate system from different radar data, and inter-process of the present invention, same employing ECEF coordinate system.
2. time alignment technique
So-called time alignment is exactly at one time in sheet, carries out interpolation, extrapolation, temporal for High Accuracy Observation data calculated on the observation time point of low precision the target observation data that each sensor gathers.Native system adopts simple Linear Recurrence mode to carry out interpolation or the extrapolation of data, thus carries out time alignment.
3) radar data process
Radar data process comprises single radar data and follows the tracks of process and multi-radar data fusion process.Radar data processor can receive the different GPR Detection Data of multiple stage, adopt distributed multi-sensor information fusion system structural model, after Track In Track process is done to each but radar, carry out track association and fusion, formed and maintenance system flight path, multi-radar data fusion treatment technology can improve target inspection probability, expansion radar area coverage, increase system reliability, raising accuracy of target measurement and accelerate the effect of system Target track displaying refreshing.
A) single radar tracking process
1. target following
A mark, to the radar data through coordinate transform, by Track In Track rule, will be followed the tracks of into flight path by system.Its process comprises: tracking initiation, tracking maintain, follow the tracks of end.
It is as follows that single radar track follows the tracks of specific algorithm:
● track initiation
After radar system first time has been scanned, many somes marks are created.After radar system carries out the second scanning, according to the expected range of first stage point mark associated gate, the some mark of present scan is correlated with, is correlated with successfully and produces initial flight path.
● confirm new flight path
In scanning process after system, judge whether to there is flight path relevant, if without relevant flight path, then produce new flight path according to the secondary code of analyzing spot mark, height and distance.If there is relevant flight path, then according to a mark information updating flight path state.
● flight path maintains and state estimation
In radar scanning process afterwards, adopt the correlation rule of previous step, confirm that flight path maintains, and carry out track filtering (Kalman filter technology), produce stable single radar track, the position next time occurred is estimated meanwhile.Kalman filter is a kind of linear filtering, then needs to revise when target is in motor-driven; The object of flight path state filtering is the error reduced as much as possible because various interference causes, and obtains the flight path that error is minimum.
● course extrapolation
When a certain flight path loses reference point mark data, transfer its state to extrapolation flight path, within the scope of the extrapolation of Operation system setting, as there is new reference point mark, flight path recovering state is normal flight path.
● flight path stops
All do not find reference point mark when N the scan period of exercise, stop this flight path, the value of N is default systematic parameter (in the present embodiment, the value of N is 5) here.
2. ripple door
Ripple door makes, for judging that the some mark in certain scan period comes from oneself to set up flight path, still to belong to the initial of a new flight path.Ripple door is exactly an area of space centered by the predicted value of certain radar scanning, and it determines that an observation is the preliminary identification of the target relevant or new to known flight path, and the flight path observation that the observation fallen in associated gate just carries out next step is matched.If within only having an observed reading to be positioned at flight path ripple door and this observed reading be not positioned within other flight path ripple doors, then this observed reading is relevant with flight path, then with this observed reading upgrade flight path.If multiple observed reading is within flight path ripple door, or an observed reading is positioned within multiple ripple door, just needs further interrelated logic process.When observation does not meet the ripple door condition of any known flight path, it is used to the new flight path of initialization one.
B) many radar fusion process
Multi-radar data fusion technology carries out format conversion, coordinate transform, space-time calibration that data are relevant to different platform multi-section radar data, and realizes on this basis merging.According to the factor such as radar detection precision, Track In Track quality of the local flight path of each radar, carry out the calculating of weighting parameters needed for Track Fusion, to realize renewal to system flight path and maintenance.
As shown in Figure 5, concrete facture side is as follows for multi-radar data fusion treatment scheme:
1. track association
Track association function, adopts weighted statistical Distance test method, is associated with by single radar track of the multiple stage radar of same for the correspondence of input target in an already present system flight path or newly-generated system flight path.The association of many radar tracks is based on flight path identifier/address or wails and the flight path number of local system flight path, and dual-purpose horizontal range, secondary code, highly, the state indices such as speed and course carries out real-time statistics judgement.Radar track association process method is shown in Fig. 6.
First judge whether flight path number associates, if flight path is number uncorrelated, then task is not same flight path, directly carries out follow-up relevant treatment.If flight path number is relevant, then to horizontal range, secondary code (SSR code), highly, speed and course test, if these values all pass through inspection (if distance is within the scope of the range deviation of Operation system setting), then can confirm track association.Otherwise enter correlated judgment, correlated judgment processing mode of the present invention is first judge course, speed and distance, if not in the deviation range of systemic presupposition, then confirms uncorrelated.If course, speed and distance all pass through inspection, then judge secondary code, highly, if one of them is by inspection, then can confirm to be correlated with.
2. radar system flight path is set up
The method for building up of system flight path is similar to single radar track.A current main radar of relevant Bo Mennei single radar track can not with any system track association existed time, start newly-built system track initiation.When this starter system flight path recurs association, change this system flight path into confirmation system flight path.When system flight path continuous several times (number of times is systematic parameter) can not be associated with any single radar track, stop this system flight path.Before termination system flight path, can extrapolate to flight path (extrapolation number of times is 5 times).
3. data fusion
The present invention adopts the dynamic weighting method of average to carry out Track Fusion, to reduce random site error.When being weighted the factor and calculating, be divided into static Summing Factor dynamic factor two parts, the static part of weighting factor depends on radar detection precision, and the aimed at precision of the radar detection that precision is high is higher, and weighting factor is larger.Dynamic part is relevant with single radar track tracking quality, and the weighting factor that quality is higher is larger.Because weighting factor had both considered the factor of projection accuracy, consider again the precision factor of object feature value, therefore can overcome the phenomenons such as beat in target location, characteristic parameter sudden change soon, the position potential difference that simultaneously can cause the random time difference carries out suppression to a certain degree.
Dynamic weighting algorithm can represent with formula below:
In formula, Si is i-th eigenwert participating in the single radar track merged, a
i is quietbe the static weighting factor of i-th single radar track, a
i movesbe the dynamic weighting factor of i-th single radar track, S is the eigenwert of the integrated track after merging, and N is the number simultaneously detecting radar.
3. start data storage threads, the single radar track data after process and many radar tracks data are stored in track data table.
Step 4, ADS-B data processing
The flow process of ADS-B data processing is similar with radar data process, can refer to radar data treatment scheme.Radar data process mainly completes the process to CAT001 message.And ADS-B completes and resolves the field of CAT021 message, ADS-B finally generates single ADS-B flight path and ADS-B merges flight path, and by flight path stored in ADS-B flight path table.
Step 5, many supervision source datas merge
1. distributed system architecture
Many supervision source data merges employing Distributed Track Fusion framework, as shown in Figure 7, proposes and many radar tracks and ADS-B flight path is merged, and produces the flight path quality that flight path quality is not less than any one monitoring data participating in fusion treatment.
In distributed frame system, first raw data is carried out a mark and follow the tracks of, predict and track association, form respective local flight path, and result is sent to fusion center, in fusion center, generate accurate system flight path through merging.Because distributed frame have compressed data volume effectively, reduce the communication load monitoring and come between data fusion center, and center processor also only carries out track data fusion, and the burden of fusion center is alleviated greatly.Because distributed frame has the independently tracked ability in local, there is the good overall situation simultaneously and monitor and evaluation of properties, and transmission volume and calculated amount lower, add stability and the reliability of system.
In distributed processing system(DPS), system relationship on the basis of local flight path coordinate serialization, will carry out in the scan period of Operation system setting.Because the selected scan period is likely different from the supervision source detection moment, when carrying out interpolation, extrapolation, weighted statistical distance criterion needs to make special consideration according to scanning moment and the difference in detection moment.When having that track is available, in order to improve association performance, the information that also can provide by means of track.
2. system track association
System track association and radar track correlating method similar, it by obtaining from radar data process and ADS-B data processing module, the local track data of corresponding same target is associated with in the many radars/ADS-B integrated track of already present or new generation.In local Track In Track process, all give the flight path formed and maintain a unique flight path number, therefore, the associated therewith local flight path number had in any system track data generated is the important evidence of follow-up track association.After flight path number association is set up, the inspection having to pass through 5 item number certificates confirms (horizontal range, SSR code, highly, speed, course), to determine that maintaining original relation still cancels its incidence relation.
3. system Track In Track
The Track In Track method of system flight path and the tracking of radar track similar, specific implementation is followed the tracks of see radar track.
4.ADS-B flight path and radar track merge
In the airbound target Parallel Tracking disposal system of many supervision source, system flight path and multiple local flight path are correlated with, and the parameter of system flight path is formed according to the fusion of certain blending algorithm by the local radar track of associated association or the parameter of local ADS-B.Merged by the kinematic parameter such as position and speed jointly observing same target obtain to multiple supervision source, not only can improve the reliability of result data, and error can be suppressed further.
The fusion of many supervision source data is the same with multi-radar data fusion uses Weighted Average Algorithm.It gives each local radar track or ADS-B flight path weight coefficient of participating in fusion, and each local flight path participates in the update process of system flight path according to weight coefficient.Average weighted weight coefficient represents the quality of data of each local flight path participating in fusion, and the weighting coefficient that quality is higher is larger, and the weighting coefficient that quality is lower is less.
Each sensor, after data processing is carried out to surveyed target in this locality, obtains t Target state estimator value after elapsed time aligning, and covariance matrix.Track Fusion utilizes covariance matrix to carry out as system input.The filtering covariance matrix that each radar or ADS-B provide is different, illustrates the difference of different supervision sources track data precision.Weighted Fusion algorithm utilizes covariance matrix to merge flight path exactly.
Claims (8)
1. the source of supervision more than an airbound target Parallel Tracking disposal route, is characterized in that: comprise the steps:
Step one, many supervision source datas receive;
Step 2, many supervision source datas are resolved: carry out the differentiation of type of message information to the raw data that step one receives, then calling data resolver is resolved data, and all kinds of message datas parsed are carried out normalization process, be then stored in internal data table;
Step 3, radar data process:
(1) real-time quality controls;
(2) radar data pre-service;
(3) radar data process: comprise single radar tracking process and the process of many radar fusion;
Step 4, ADS-B data processing: generate single ADS-B flight path and ADS-B fusion flight path, and by flight path stored in ADS-B flight path table;
Step 5, many supervision source datas merge:
(1) system track association;
(2) system Track In Track;
(3) ADS-B flight path and radar track merge.
2. one many supervision source according to claim 1 airbound target Parallel Tracking disposal route, is characterized in that: the many supervision source data described in step one receives and comprises following flow process:
(1) building database connects, from data source parameter configuration table, read data source information;
(2) judge whether data streams read provides exceptional value in log recording: if then quit a program; If not, then next step is entered;
(3) create corresponding data sink according to the IP address of data source, port, data type, data subtypes, each data sink is a thread;
(4) start thread, receive the raw data of corresponding port;
(5) receiver thread is by the raw data that receives stored in raw data base, waits for subsequent treatment.
3. one many supervision source according to claim 1 airbound target Parallel Tracking disposal route, it is characterized in that: described in step 2 the differentiation of type of message information is carried out to raw data before first pre-service is carried out to raw data: when the oblique distance difference of enrolling data continuous multiple spots is zero, is regarded as to follow the tracks of and loses; When certain point or certain several point and front and back data difference of enrolling data are obviously greater than normal difference, be regarded as hop; Add up abnormal data, when the ratio of abnormal data and total data is greater than the System Fault Tolerance value of setting, it is invalid data to be considered as.
4. one many supervision source according to claim 1 airbound target Parallel Tracking disposal route, it is characterized in that: adopt version processing policy when the data parser described in step 2 is resolved data: when receiving message, search SAC and SIC corresponding in version cache table with or without colophon according to SAC and SIC in message, if having, use this version analytic message; If without this version or have this version but resolve unsuccessful, then adopt other versions to resolve from high to low, if there is a successfully resolved, be recorded to for resolving next time in buffer memory corresponding to SAC and SIC, if resolve all unsuccessful, return parse error.
5. one many supervision source according to claim 1 airbound target Parallel Tracking disposal route, is characterized in that: the real-time quality described in step 3 controls to comprise:
A) radar station data source real-time quality monitoring: by radar land station status report, obtain station state value, evaluates station data quality, and by the status information of website stored in database;
B) radar data overload process: real-time statistics is carried out to the total amount of all kinds of message in supervision source and whether real-time judge exceedes the permissible flow of setting, if exceed, then cut off the output of this station data immediately, till detecting that the data stream recovery of this website is normal;
C) radar data passage is than choosing: by setting-up time unit, the quantizating index of real-time dynamic monitoring each road radar signal quality, if signal quality is lower than the metrics-thresholds of setting, produces alarm.
6. one many supervision source according to claim 1 airbound target Parallel Tracking disposal route, is characterized in that: the radar data pre-service described in step 3 comprises:
A) data validity inspection: comprise altitude information inspection and speed data inspection;
B) coordinate conversion: by the position provided in message, highly, under the data such as speed are transformed into unified ECEF coordinate system;
C) space-time calibration: the kinematics parameters in all track data is moved on the time point of one-period all on a timeline.
7. one many supervision source according to claim 1 airbound target Parallel Tracking disposal route, is characterized in that: the single radar tracking process described in step 3 comprises:
1. track initiation: radar system first time produces some mark after having scanned; After radar system carries out the second scanning, according to the expected range of the some mark associated gate that first time scanning produces, the some mark of present scan is correlated with, is correlated with successfully and produces initial flight path;
2. confirm new flight path: in scanning process afterwards, judge whether to there is flight path relevant according to the secondary code of analyzing spot mark, height and distance: if uncorrelated, then produce new flight path; If relevant, then according to a mark information updating flight path state;
3. flight path maintains and state estimation: in scanning process afterwards, adopts the correlation rule of previous step, confirms that flight path maintains, and carries out track filtering, produce stable single radar track, estimate the position occurred next time meanwhile;
4. course extrapolation: when a certain flight path loses reference point mark data, transfer its state to extrapolation flight path, within the scope of the extrapolation of Operation system setting, as there is new reference point mark, flight path recovering state is normal flight path;
5. flight path stops: when all not finding reference point mark in N the scan period of presetting, then stop this flight path.
8. one many supervision source according to claim 1 airbound target Parallel Tracking disposal route, is characterized in that: the many radar fusion process described in step 3 comprises:
1. track association: first judge whether flight path number is correlated with: if uncorrelated, then task is not same flight path, directly carries out follow-up relevant treatment; If relevant, then to horizontal range, secondary code, highly, speed and course test, if all by checking, then confirm track association; Otherwise, first judge that course, speed and distance are whether in the deviation range of systemic presupposition, if not, then confirm uncorrelated, if so, then continue inspection secondary code or height, if one of them is by inspection, then confirm track association;
2. radar system flight path set up: a current main radar of relevant Bo Mennei single radar track can not with any system track association existed time, start newly-built system track initiation; When this starter system flight path recurs association, then change this system flight path into confirmation system flight path; When system flight path all can not be associated with any single radar track in the read-around ratio set, stop this system flight path;
3. data fusion: adopt the dynamic weighting method of average to carry out Track Fusion:
In formula, Si is i-th eigenwert participating in the single radar track merged, a
i is quietbe the static weighting factor of i-th single radar track, a
i movesbe the dynamic weighting factor of i-th single radar track, S is the eigenwert of the integrated track after merging, and N is the number simultaneously detecting radar.
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| CN106534316A (en) * | 2016-11-14 | 2017-03-22 | 中国电子科技集团公司第二十八研究所 | Radar intelligence processing system based on data subscription and distribution service |
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| CN107132515A (en) * | 2017-05-09 | 2017-09-05 | 哈尔滨工业大学 | A kind of point mark screening technique constrained based on multidimensional information |
| CN107578646A (en) * | 2017-08-28 | 2018-01-12 | 梁晓龙 | low slow small target detection monitoring management system and method |
| CN108090240A (en) * | 2016-11-23 | 2018-05-29 | 北京空间技术研制试验中心 | The processing of pneumatic gauging test flight data and appraisal procedure |
| CN108089184A (en) * | 2017-12-08 | 2018-05-29 | 中国船舶重工集团公司第七二四研究所 | A kind of TWS radar targets spatial position grouping parallel tracking processing method |
| CN108181618A (en) * | 2018-03-01 | 2018-06-19 | 中国人民解放军陆军炮兵防空兵学院郑州校区 | A kind of Radar Calibration method |
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| CN114994633A (en) * | 2022-08-04 | 2022-09-02 | 四川九洲空管科技有限责任公司 | Method for secondary radar point track correlation processing |
| RU2801584C1 (en) * | 2022-07-12 | 2023-08-11 | Акционерное Общество "Северо-Западный Региональный Центр Концерна Вко "Алмаз-Антей" - Обуховский Завод" | Method and device for monitoring the reliability of surveillance information |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101110166A (en) * | 2007-08-15 | 2008-01-23 | 民航数据通信有限责任公司 | ADS-B flight path and plan related processing system |
| JP2011047882A (en) * | 2009-08-28 | 2011-03-10 | Toshiba Corp | Target-tracking system |
| CN202549080U (en) * | 2012-03-16 | 2012-11-21 | 中国民用航空总局第二研究所 | Fusion system of radar data, flight plan data and ADS-B data |
| CN103926564A (en) * | 2014-03-21 | 2014-07-16 | 成都民航空管科技发展有限公司 | Multi-source monitoring data fusion method and device |
-
2015
- 2015-05-06 CN CN201510224655.1A patent/CN104808197B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101110166A (en) * | 2007-08-15 | 2008-01-23 | 民航数据通信有限责任公司 | ADS-B flight path and plan related processing system |
| JP2011047882A (en) * | 2009-08-28 | 2011-03-10 | Toshiba Corp | Target-tracking system |
| CN202549080U (en) * | 2012-03-16 | 2012-11-21 | 中国民用航空总局第二研究所 | Fusion system of radar data, flight plan data and ADS-B data |
| CN103926564A (en) * | 2014-03-21 | 2014-07-16 | 成都民航空管科技发展有限公司 | Multi-source monitoring data fusion method and device |
Non-Patent Citations (5)
| Title |
|---|
| 付强: "《ADS-B原理及在空中交通管制中的应用一在长春空中交通管制中的分析设计》", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
| 何桂萍: "《ADS-B与雷达组合监视数据融合方法研究》", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 尚德佳: "《空管多监视数据融合研究》", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
| 张元忠: "《多雷达数据融合测试软件的研究与实现》", 《中国优秀博硕士学位论文全文数据库 (硕士) 信息科技辑》 * |
| 陈雷 等: "《通用雷达数据格式化分析与预处理系统》", 《中国科技信息》 * |
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