CN106094569A - Multi-sensor Fusion unmanned plane perception with evade analogue system and emulation mode thereof - Google Patents
Multi-sensor Fusion unmanned plane perception with evade analogue system and emulation mode thereof Download PDFInfo
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Abstract
The invention discloses a kind of Multi-sensor Fusion unmanned plane perception and evade analogue system, including system configuration module, ADS B data module, unmanned aerial vehicle platform emulation module, sensing data emulation module and perception with evade algoritic module, above-mentioned modules is connected to system data pond, and carries out data interaction by system data pond.The invention also discloses the emulation mode of correspondence, solve existing unmanned plane perception and avoidance system method for designing cost height, the test problems such as risk factor is big, efficiency is low.
Description
Technical field
The invention belongs to Navigation of Pilotless Aircraft and control technology technical field, relate to a kind of Multi-sensor Fusion unmanned plane perception
With evade analogue system and emulation mode thereof.
Background technology
Along with unmanned plane constantly expands in range of application military, civil area, following spatial domain will be the most intensive, great Liang Wu
The intensive flight in man-machine spatial domain will make air traffic collision probability sharply increase, and bring great to existing air traffic safety
Threaten.Perception and the technology of evading by unmanned plane load airspace perceptual sensor realize the effectively monitoring to aerial target, with
Track, and controlled threatening effectively evading of target by evading path planning and emergency mobile, thus ensure unmanned plane
Spatial domain flight safety.
Unmanned plane perception relates to unmanned plane sensor configuration, airspace perceptual algorithm, collision assessment with the design of avoidance system
The aspects such as logic, unmanned plane evasion manoeuvre control, are complicated system-level engineerings.The sensor configuration of unmanned plane needs fully
Consider the task attribute of unmanned plane, load-carrying ability, aeroperformance etc., simultaneously the relevant rule of air traffic control system (ATCS) to be met
Then and configuration requirement；Unmanned plane airspace perceptual algorithm is based on sensing data, it is achieved effectively detection and the state estimation to target；
Collision assessment logic is carried out according to the regulation of aviation, impends based on aerial sensing results and assesses and collision alarm；Rule
Keep away path planning and maneuver autopilot to realize the safest, economic path of evading in the range of UAV Maneuver and design and stable
Evasion manoeuvre controls output.Perception based on above-mentioned functions and avoidance system design complexity, design based on actual hardware system
Mode needs to carry out purchasing and repeatedly configuring installation of multiple sensors, and process is loaded down with trivial details, economy is poor.Carry out algorithm design to need
The system test test risk through parameter testing repeatedly, carrying out real midair collision scene is relatively big, and causality loss is huge
Greatly.Compared to the design of hardware real system, unmanned plane perception based on software emulation platform designs energy with avoidance system
Enough functions such as Choice of Sensors, parameter configuration that realizes easily, risk is low, design efficiency is high in emulation experiment test, it is adaptable to nothing
The initial stage type selecting that man-machine perception and avoidance system design is designed and developed with algorithm.
Summary of the invention
It is an object of the invention to provide a kind of Multi-sensor Fusion unmanned plane perception and evade analogue system and emulation side thereof
Method, to solve that existing unmanned plane perception and avoidance system method for designing cost be high, risk factor is big, efficiency is low etc. asks in test
Topic.
The first technical scheme of the present invention is, Multi-sensor Fusion unmanned plane perception with evade analogue system,
Including system configuration module, ADS-B data module, unmanned aerial vehicle platform emulation module, sensing data emulation module and perception with
Evading algoritic module, above-mentioned modules is connected to system data pond, and carries out data interaction by system data pond；
Wherein, system configuration module, it is used for parameter configuration and the system initialization of analogue system, and by parameter with just
Beginning information sends to system data pond, and parameter includes SAA scene setting, the parameter configuration files of sensor, and algorithm parameter is joined
Put, unmanned aerial vehicle platform configuration information and aerial mission；
ADS-B data module, for obtaining initialization information by system data pond, and gathers the true empty of spatial domain target
Middle traffic data, truer air traffic data is stored to system data pond；
Sensing data emulation module, perception and evading sequentially forms between algoritic module and unmanned aerial vehicle platform emulation module
Data loop, its simulated flight status information is sent to sensing data emulation module, sensing by unmanned aerial vehicle platform emulation module
Device data simulation module further according to true air traffic data produce corresponding perception data and send to perception with evade algorithm
Module, perception with evade algoritic module and be calculated optimum and evade path and feed back to unmanned aerial vehicle platform emulation module so that nothing
Man-machine platform emulation module dynamically adjusts to ensure that it is in optimum all the time and evades path.
Further, unmanned aerial vehicle platform emulation module, it is used for simulating unmanned plane, and obtains emulation system by system data pond
Initialization information, way point information and the optimum of system evade path, to control the simulated flight of unmanned aerial vehicle platform emulation module, and
Simulated flight status information is stored to system data pond；
Sensing data emulation module, for obtaining by system data pond: the initialization information of analogue system, truly sky
Middle traffic data and the simulated flight status information exported by unmanned aerial vehicle platform emulation module, then produce corresponding perception
Data store to system data pond；
Perception with evade algoritic module, for obtaining perception data by system data pond, and according to perception data to sky
Territory target impends assessment and evade path planning, thus obtains optimum and evade path, and optimum is evaded path store to
System data pond.
Further, unmanned aerial vehicle platform emulation module, including the mission planning module being sequentially connected with system data pond, fly
Row control module and aircraft platforms emulation module；
Mission planning module, for loading the first departure position of unmanned plane, the joining of unmanned aerial vehicle platform by system data pond
Confidence breath and aerial mission；
Flight control modules, for following the tracks of the destination of unmanned plane；
Aircraft platforms emulation module, for exporting the simulated flight status information of unmanned plane.
Further, sensing data emulation module includes radar simulator, infrared simulator and/or photoelectric simulation device；
Radar simulator, for reading true air traffic data and simulated flight status information by system data pond,
And generate radar simulation data and store to system data pond, then transmit to perception with evade algoritic module；
Infrared simulator, for emulating the infrared intensity of the spatial domain target and background generated in scene, and by infrared
Image stores to system data pond, then transmit to perception with evade algoritic module；
Photoelectric simulation device, generates the visible ray realtime image data containing spatial domain target for emulating, and by real time imaging
Data store to system data pond, then transmit to perception with evade algoritic module.
Further, perception with evade environment sensing module, the prestige that algoritic module includes being sequentially connected with system data pond
Coerce evaluation module and evade algoritic module；
Environment sensing module, reads the parameter of each sensor in sensing data emulation module by system data pond and joins
Put file, and read perception data, further according to parameter configuration files and the perception number of sensor, according to the state obtaining spatial domain target
Estimate；
Threat assessment module, arranges by reading the algorithm parameter in system data pond, and calculates by reading environment sensing
The data of method module and the simulated flight status information of unmanned plane impend grade assessment, to exceeding certain threat level
Spatial domain target carries out collision alarm, and sends position and the speed state estimative figure of spatial domain target from high to low according to threat degree
According to perception with evade algoritic module；
Evade algoritic module, be used for carrying out unmanned plane optimum and evade path and resolve, and by calculation result with the form of destination
Sent to unmanned aerial vehicle platform emulation module by system data pond.
Further, ADS-B data module includes that ADS-B IN module, ADS-B IN module obtain spatial domain mesh by parsing
Target traffic location, height and route information, then traffic location, height and route information are stored to system data pond.
Further, system data pond also data cube computation has system evaluation module, and system evaluation module, for from system number
Obtain according in pond: simulated flight status information, true air traffic data, simulated flight status information, perception data and optimum
Evade path, carry out Performance Evaluation so that the airspace perceptual scope of analogue system and collision to be set aside some time.
Further, system data pond also data cube computation has 3D real-time simulation scene display module, 3D real-time simulation scene
Display module, for coming scene environment real according to SAA scene setting, simulated flight status information and true air traffic data
Shi Jianmo, is modeled the aerial scene that meets with.
The second technical scheme that the present invention uses is, the emulation mode of above-mentioned analogue system, including step in detail below:
Step 1, the major parameter configuration being completed analogue system by system configuration module and system initialization, and will configuration
Parameter by system data pond send to unmanned aerial vehicle platform emulation module, sensing data emulation module and perception with evade calculation
Method module, completes parameter initialization；
Step 2, by ADS-B data module receive air traffic ADS-B data, including position, the height of spatial domain target
Degree and route information, and send it to system data pond as the target machine data in traffic scene in simulated hollow；
Step 3, unmanned aerial vehicle platform emulation module load unmanned plane and initially configure with unmanned aerial vehicle platform, and destination is entered
Line trace, then exports the simulated flight status information of unmanned aerial vehicle platform emulation module to system data pond；
Step 4, obtained the perception data of each sensor by sensing data emulation module；
Step 5, by perception with evade algoritic module, the perception data according to obtaining in step 4 is calculated optimum and evades
Path, and feed back to unmanned aerial vehicle platform emulation module to instruct unmanned plane to evade path flight at optimum.
Further, emulation mode is further comprising the steps of:
Step 6, by 3D real-time scene display module, according to SAA scene setting, simulated flight status information and true aerial
Traffic data, to scene environment Real-time modeling set, to be modeled, the aerial scene that meets with to the situation in the machine flying scene
Show in real time；
Step 7, by system evaluation module read simulated flight status information, true air traffic data, simulated flight shape
State information, perception data and optimum evade path, with Progressive symmetric erythrokeratodermia of setting aside some time the airspace perceptual scope of analogue system and collision
Can assessment.
The invention has the beneficial effects as follows, enormously simplify the complexity of unmanned plane perception and avoidance system design, improve effect
Rate；This system can effectively emulate Traffic Environment, and carries out sensor configuration, perception and rule based on real-time empty numeric field data
Keep away algorithm function, the emulation of platform properties configuration；Compared to method for designing based on hardware system, there is low cost, reliability
The features such as high, test risk is low；It is applicable to the design to polytype unmanned plane perception and avoidance system and emulation.
Accompanying drawing explanation
Fig. 1 is Multi-sensor Fusion unmanned plane perception of the present invention and the structural representation evading analogue system；
Fig. 2 is Multi-sensor Fusion unmanned plane perception of the present invention and the simulation system software flow chart evading analogue system；
Fig. 3 is Multi-sensor Fusion unmanned plane perception of the present invention and evade analogue system radar surveying schematic diagram；
Fig. 4 is Multi-sensor Fusion unmanned plane perception of the present invention and evade analogue system photooptical data simulation flow；
Fig. 5 is Multi-sensor Fusion unmanned plane perception of the present invention and evade analogue system infrared simulation block flow diagram.
In figure, 1. system configuration module, 2.ADS-B data module, 3. unmanned aerial vehicle platform emulation module, 4. sensing data
Emulation module, 5. perception with evade algoritic module, 6.3D real-time simulation scene display module, 7. system evaluation module, 8. system
Data pool.
Detailed description of the invention
The present invention is described in detail with detailed description of the invention below in conjunction with the accompanying drawings.
The invention provides Multi-sensor Fusion unmanned plane perception and evade analogue system, seeing Fig. 1, using distributed mould
Massing simulation architecture, including system configuration module 1, ADS-B data module 2, sensing data emulation module 4, perception with evade
Algoritic module 5,3D real-time simulation scene display module 6, and system evaluation module 7, above-mentioned modules by fixing IP with
ICP/IP protocol realizes the data interaction with system data pond 8.Wherein, sensing data emulation module 4 specifically includes photoelectric transfer
Sensor, infrared sensor, radar sensor and other sensors etc..
1, system configuration module 1, has been used for parameter configuration and the system initialization of analogue system, and by parameter with initial
Change information sends to system data pond 8, and parameter includes SAA scene setting, the parameter configuration files of sensor, and algorithm parameter is joined
Put, unmanned aerial vehicle platform configuration information and aerial mission；Wherein, SAA scene is i.e. perception and evade scene；
2, ADS-B data module 2, for obtaining initialization information by system data pond 8, and gathers the true of spatial domain target
Real air traffic data, truer air traffic data is stored to system data pond 8；
Concrete, ADS-B data module 2 includes that ADS-B IN module, ADS-B IN module obtain spatial domain mesh by parsing
Target traffic location, height and route information, then traffic location, height and route information are stored to system data pond 8, and lead to
Cross UI interface display.
3, sensing data emulation module 4, perception and evading depends between algoritic module 5 and unmanned aerial vehicle platform emulation module 3
Secondary formation datacycle loop, the transmission of its simulated flight status information is imitated by unmanned aerial vehicle platform emulation module 3 to sensing data
True module 4, sensing data emulation module 4 produces corresponding perception data further according to true air traffic data and sends to sense
Know and evade algoritic module 5, perception with evade algoritic module 5 and be calculated optimum and evade path and feed back to unmanned aerial vehicle platform and imitate
True module 3 so that unmanned aerial vehicle platform emulation module 3 dynamically adjusts to ensure that it is in optimum all the time and evades path.
3.1, unmanned aerial vehicle platform emulation module 3, is used for simulating unmanned plane, and is obtained by system data pond 8: analogue system
Initialization information, way point information and optimum evade path, to control the simulated flight of unmanned aerial vehicle platform emulation module 3, and will
Simulated flight status information stores to system data pond 8.
Concrete, unmanned plane machine platform emulation module 3, including the mission planning module being sequentially connected with system data pond 8,
Flight control modules and aircraft platforms emulation module；
Mission planning module, for loading the first departure position of unmanned plane, the joining of unmanned aerial vehicle platform by system data pond 8
Confidence breath and aerial mission；Aerial mission includes flight starting point, terminal and flight path；
Flight control modules, for following the tracks of the destination of unmanned plane；
Aircraft platforms emulation module, for exporting the simulated flight status information of unmanned plane.
3.2, sensing data emulation module 4, for being obtained by system data pond 8: the initialization information of analogue system,
True air traffic data and the simulated flight status information exported by unmanned aerial vehicle platform emulation module 3, then produce corresponding
Perception data store to system data pond 8.
Concrete, sensing data emulation module 4 includes radar simulator, infrared simulator and/or photoelectric simulation device；
Radar simulator, for reading true air traffic data and simulated flight status information by system data pond 8,
And generate radar simulation data and store to system data pond 8, then transmit to perception with evade algoritic module 5；
Infrared simulator, for emulating the infrared intensity of the spatial domain target and background generated in scene, and by infrared
Image stores to system data pond 8, then transmit to perception with evade algoritic module 5；
Photoelectric simulation device, generates the visible ray realtime image data containing spatial domain target for emulating, and by real time imaging
Data store to system data pond 8, then transmit to perception with evade algoritic module 5.
3.3, perception with keep away algoritic module 5, for obtaining perception data by system data pond 8, and according to perception data
Impend assessment and evade path planning to spatial domain target, thus obtain optimum and evade path, and optimum is evaded path deposit
Storage is to system data pond 8.
Concrete, perception with evade environment sensing module, the prestige that algoritic module 5 includes being sequentially connected with system data pond 8
Coerce evaluation module and evade algoritic module；
Environment sensing module, reads the parameter of each sensor in sensing data emulation module 4 by system data pond 8
Configuration file, the system at sensing data emulation module configures and parameter sets on the premise of determining, and reads perception data,
Further according to parameter configuration files and the perception number of sensor, according to the state estimation obtaining spatial domain target；Wherein, environment sensing module
The method of state estimation is: perception data is carried out Preprocessing Algorithm design, multi-sensor information fusion, object detecting and tracking
Etc. function, the state estimation such as position and speed of finally exporting spatial domain target under unmanned plane coordinate system.
Threat assessment module, arranges by reading the algorithm parameter in system data pond 8, is defined collision threat,
When i.e. the distance of minimum separation between the machine and target machine is less than predetermined threshold, it is believed that collision threat vinegar exists, and by reading
The data of environment sensing algoritic module and the simulated flight status information of unmanned plane impend grade assessment, certain to exceeding
The spatial domain target of threat level carries out collision alarm, and sends position and the speed of spatial domain target from high to low according to threat degree
Data of State Estimation to perception with evade algoritic module 5；
Evade algoritic module, be used for carrying out unmanned plane optimum and evade path and resolve, and by calculation result with the form of destination
Sent to unmanned aerial vehicle platform emulation module 3 by system data pond 8.Wherein, this nothing should be taken into full account when carrying out algorithm design
The indexs such as man-machine maneuvering characteristics, motor-driven consumption, perceptual performance, it is achieved optimum evasion manoeuvre.
4, data cube computation is gone back in system data pond 8 system evaluation module 7, and system evaluation module 7, for from system data pond
Obtain in 8: simulated flight status information, true air traffic data, simulated flight status information, perception data and optimum are evaded
Path, carries out Performance Evaluation to set aside some time the airspace perceptual scope of analogue system and collision, and exports assessment result.
5, data cube computation is gone back in system data pond 8 3D real-time simulation scene display module 6,3D real-time simulation scene display mould
Block 6, for building in real time scene environment according to SAA scene setting, simulated flight status information and true air traffic data
Mould, is modeled the aerial scene that meets with.
Multi-sensor Fusion unmanned plane perception of the present invention with evade the concrete simulation process of analogue system as shown in Figure 2:
(1) analogue system is configured and system initialization by system configuration module 1 completion system major parameter, and will configuration
Parameter is sent to alternative document by system data pond 8, completes parameter initialization.
A. flying scene initializes:
During flying scene initializes, including flying height, flight weather, flight time.Flying scene is according to spatial domain not
With, it is divided into high-altitude scene, i.e. flying height > 6600 meters, hollow scene, flying height 1000～6600 meters, low latitude scene, flight
Highly < 1000 meters.According to aviation rules and regulations, different flight control layers to be installed corresponding awareness apparatus targetedly and lead to
News link.Flight weather con dition is divided into sunny, cloudy, mist, sleet etc..Flight time is divided into daytime and evening.Meteorological condition
Will act on the simulation result of imageing sensor with the flight time.
B. flying platform initializes
Carry out aircraft type selecting according to flying scene, (as a example by global hawk RQ-4A, fly including Altitude Long Endurance Unmanned Air Vehicle
Line speed 170～200m/s, load < 908kg), hollow unmanned plane (as a example by Predator, flight speed 36～60m/s, load <
1020kg), low latitude SUAV (flight speed < 50m/s, load < 50kg).
C. sensor initializing
Carry out Choice of Sensors according to type of aircraft and flying scene, and the performance parameter of sensor is configured.
Optional sensor includes photoelectricity, infrared, radar, and can self-developing other types sensor selective.Photoelectric simulation device based on
Vega Prime camera model emulates, can be according to common record photoelectric sensor performance parameter focusing, resolution etc.
Be configured, data rate；Infrared simulator emulates based on Vega Prime infrared imaging model, can to imaging band,
Resolution, focal length, data rate etc. are configured.Radar sensor can be to wave band, sphere of action, angular resolution, distance point
Resolution, angular error, range error etc. carry out emulation and arrange.
D. algorithm parameter configuration
Algorithm parameter configuration include to unmanned plane perception with evade in function in collision probability threshold value, evade reserved time
Between, distance of minimum separation etc. is configured.
Collision probability threshold value: judge that target is as the lowest confidence threatening target according to perception algorithm.
Evade and setting aside some time: be defined as evading the used time for the shortest of collision threat target.
Distance of minimum separation: the machine and target machine in flight course at a distance of beeline should be greater than minimum separation away from
From.
E. task attribute configuration
Task attribute configuration pin the flight of unmanned plane the machine is risen departure position, task destination, original state (position, speed,
Attitude etc.) it is configured.
(2) ADS-B module receives ADS-B data, and resolve obtain air traffic position, highly, the information such as course line, and
By UI interface display.
For improving the verity of analogue system, the Multi-sensor Fusion unmanned plane perception of the present invention is drawn with evading analogue system
Enter ADS-B IN equipment and realize the collection to airspace data, simulate real airflight field as the target machine in simulated environment
Scape, and by UI interface, air traffic state is carried out real-time display.It is high that ADS-B data have precision, and cooperative, information is complete
The kind feature waited, comprises the information such as the position of target, speed, attitude, course line.Target data is passed through number by ADS-B data module
Send to each sensor assembly according to pond, be used for emulating generation perception data.
(3) unmanned aerial vehicle platform emulation module 3 is by loading destination and platform configuration, and is realized by flight control system
Tracking to destination, and flight state output.
In unmanned aerial vehicle platform emulation module 3, use JSBSim software, based on platform properties configuration information, to aircraft
Carry out Kinematic Model, based on unmanned plane mission planning, carry out position of platform, speed and gesture stability, it is achieved to task destination
Or evade the tracking of destination, and position of platform, speed, the output of attitude state.Platform status information by data pool send to
Each sensor assembly and algorithm function module, be used for producing perception data and SAA algorithm.
(4) sensor Simulation
A. radar sensor emulation.Radar simulation module is by reading the system configuration module parameter for radar sensor
Configuration initializes, and reads air traffic data and local state data by data pool, generates radar simulation dataWherein i represents the object identifier detected, riFor the radial distance of target Yu the machine, αiRepresent target
With the horizontal angle of the machine, βiFor target vertical angle under the machine coordinate system, (σr,σα,σβ) it is that radar is at radial direction, azimuth
Poor with the statistical standard at the elevation angle.As it is shown on figure 3,Generating mode is as follows:
By target position X under world coordinate systemoWith the machine position X under world coordinate systemhAnd the machine is relative
Attitude Ω of world coordinate system obtains target in the position under the machine coordinate system
Pass throughAdd noise to obtain
Wherein ηr,ηα,ηβRadar measurement noise, equal Normal Distribution.
Radar simulation data are sent to data pool and preserve, and are sent to perception and evade algoritic module 5, for airspace perceptual
Algorithm.
B. photoelectric sensor.As shown in Figure 4, photoelectric sensor passes through MultiGen creator and Vega to its simulation process
Prime4.1 realizes.By reading transport information and the flatbed number of flight space, carry out sky based on MultiGen creator
Middle target 3D models, and by reading local state information and sensor configuration parameter, uses the Camera module of Vega Prime
Realize the realtime image data containing air traffic target is obtained.Photoelectric sensor emulation module sends data to system number
Preserve according to pond 8, and transmission for perception and evades algoritic module 5.
C. infrared sensor.Its simulation process is as it is shown in figure 5, realize infrared sensor by the API library function of Vega
Effective emulation.The internal procedure of Vega emulation is that Sensor Vision module utilizes Texture Mapping Mapper
(TMM) set the texture of object and physical characteristics of materials, then utilize MAT to set atmospheric transfer model, calculate atmospheric transmissivity,
The atmospheric background radiation, the sun or the direct radiation etc. of the moon, it is considered to this amount of calculation is bigger, it is difficult to complete in real time, it is fixed in advance to use
Justice also saves as the mode of .mat file, and in actual emulation, Sensor Vision module reads .mat file, directly uses
Precalculate parameter and realize real-time simulation；Call the various parameters being computed finally by Sensor Vision, use radiation
Degree computing formula, calculates the infrared intensity in scene, and completes the conversion from radiant intensity to gray value, generate infrared figure
Picture.Photoelectric sensor emulation module sends data to system data pond 8 and preserves, and is sent to perception and evades algoritic module 5.
(5) perception with evade algoritic module 5.Perception can divide with evading sequence flow according to perception with evading algoritic module 5
For environment sensing module, threat assessment module with evade algoritic module.User need to carry out algorithm design and test under this framework.
A. environment sensing module.Environment sensing module reads sensor configuration file by data pool, in the perception determined
On the premise of system configuration and parameter set, read the sensing data in data pool.And complete sensor based on this sensor
Data management, the function such as Preprocessing Algorithm design, multi-sensor information fusion, object detecting and tracking.This module finally exports
The state estimation (such as position, speed etc.) of the spatial domain target under the machine coordinate system.
B. threat assessment module.Threat assessment module is arranged by reading the algorithm parameter of data pool, enters collision threat
Row definition, and assess, to exceeding certain prestige by reading environment sensing module data and the local state data grade that impends
The target of side of body grade carries out collision alarm, and sends target data from high to low to evading algoritic module according to threat degree.
C. algoritic module is evaded.Evade algoritic module arranged by performance based on the machine and threaten dbjective state to carry out
Excellent path of evading resolves, and is sent to platform emulation module by data pool with the form of way point according to calculation result.Carry out
The indexs such as the maneuvering characteristics of the machine, motor-driven consumption, perceptual performance should be taken into full account, it is achieved optimum evades machine during algorithm design
Dynamic.
(6) 3D real-time simulation scene display module 6.
3D real-time scene display module is designed based on Vega Prime and MFC framework, and first module reading scene sets
Put parameter, it is achieved to the meteorology under simulating scenes, the setting of light and shade.By reading local state and the ADS-B data of target machine
Information, it is achieved under the machine angle, can pull and meet with the machine under scene and target machine in the real-time empty under multiple angles such as angle
State of flight, the display of flight path.
(7) system evaluation module 7.
System evaluation module completes perception and the real-time display of evading data, as sensor status data, local state,
It is motor-driven etc. that target apperception state, target time of day, targets'threat, the machine evade path and the machine.
System evaluation module also completes perception and avoidance system configuration and the assessment result of algorithm, main by such as lower section
Face is assessed:
A. airspace perceptual scope, under airspace perceptual scope is defined as configuring based on attribute sensor, it is possible to realize target
The maximum magnitude that effective information obtains, the level that is expressed as effective perception angle, vertical effectively perception angle and target effective perception
Distance.This index is calculated by reading sensor configuration parameter.
B. collision is set aside some time, and collision is set aside some time and is defined as the moment producing collision alarm to predicting that collision occurs point to need
The time wanted, this time is that the one to airspace perceptual sensor configuration, airspace perceptual algorithm and threat assessment logic comprehensively has
Effect judges.This index is evaded the status data in algorithm by reading and is obtained.
C. target distance of minimum separation
Target distance of minimum separation is defined as during whole evading, the machine and threaten smallest radial between target away from
From, this distance is that perception and avoidance system are evaded a kind of comprehensive assessment of performance and mobility.This index is by reading
The machine obtains with the flight path of target machine.
The present invention utilizes the combination of multiple sensors, the situations using single-sensors compared in prior art more and
Speech, it is possible to be adapted to high-altitude complex environment, improves under its meteorological condition severe such as cloud and mist, sleet, the illumination such as illumination, night bar
Airspace perceptual under part and in electromagnetic interference environment.And combine based on multiple sensors, it is possible to significantly improve perceived accuracy, fall
Low missing inspection and false-alarm probability.Meanwhile, when carrying out sensor configuration, should carry out according to the task of unmanned plane, working environment
Design targetedly and configure.
In prior art, the self-defining form of many employings simulates airspace data, and uses ADS-B data mould in the present invention
Block 2 can obtain more real airspace data, and sends airspace data to described system data pond 8.ADS-B IN can
Obtain a range of true airspace data.Simulate airspace data compared to self-defining mode, in this way can adopt
The state of flight of reduction airborne aircraft more true, effective, to aerial route situation, spatial domain traffic density, air traffic
Dynamic characteristic can effectively be simulated.
Claims (10)
1. the perception of Multi-sensor Fusion unmanned plane with evade analogue system, it is characterised in that include system configuration module (1),
ADS-B data module (2), unmanned aerial vehicle platform emulation module (3), sensing data emulation module (4) and perception with evade algorithm
Module (5), above-mentioned modules is connected to system data pond (8), and carries out data friendship by described system data pond (8)
Mutually；
Wherein, described system configuration module (1), it is used for parameter configuration and the system initialization of described analogue system, and will
Parameter and initialization information send to described system data pond (8), and described parameter includes SAA scene setting, the parameter of sensor
Configuration file, algorithm parameter configures, unmanned aerial vehicle platform configuration information and aerial mission；
Described ADS-B data module (2), for obtaining described initialization information by system data pond (8), and gathers spatial domain
The true air traffic data of target, more described true air traffic data is stored to described system data pond (8)；
Described sensing data emulation module (4), perception and evade algoritic module (5) and unmanned aerial vehicle platform emulation module (3) it
Between sequentially form data loop, its simulated flight status information is sent to described biography by described unmanned aerial vehicle platform emulation module (3)
Sensor data simulation module (4), described sensing data emulation module (4) produces phase further according to described true air traffic data
Perception data the transmission answered to described perception and evade algoritic module (5), and described perception calculates with evading algoritic module (5)
Evade path to optimum and feed back to described unmanned aerial vehicle platform emulation module (3) so that unmanned aerial vehicle platform emulation module (3) is dynamic
Adjust to ensure that it is in optimum all the time and evades path.
2. Multi-sensor Fusion unmanned plane perception as claimed in claim 1 with evade analogue system, it is characterised in that described nothing
Man-machine platform emulation module (3), is used for simulating unmanned plane, and obtains the initial of described analogue system by system data pond (8)
Change information, described way point information and described optimum evade path, to control the emulation of described unmanned aerial vehicle platform emulation module (3)
Flight, and described simulated flight status information is stored to described system data pond (8)；
Described sensing data emulation module (4), for obtaining by system data pond (8): described analogue system initial
Change information, described true air traffic data and the simulated flight state exported by described unmanned aerial vehicle platform emulation module (3)
Information, then produces corresponding perception data and stores to described system data pond (8)；
Described perception with evade algoritic module (5), for by system data pond (8) obtain described in perception data, and according to
Spatial domain target is impended and assesses and evade path planning by described perception data, thus obtains optimum and evade path, and by institute
State optimum to evade path and store to described system data pond (8).
3. Multi-sensor Fusion unmanned plane perception as claimed in claim 2 with evade analogue system, it is characterised in that described nothing
Man-machine platform emulation module (3), controls mould including the mission planning module being sequentially connected with described system data pond (8), flight
Block and aircraft platforms emulation module；
Described mission planning module, for loading the first departure position of unmanned plane, unmanned aerial vehicle platform by system data pond (8)
Configuration information and aerial mission；
Described flight control modules, for following the tracks of the destination of described unmanned plane；
Described aircraft platforms emulation module, for exporting the simulated flight status information of described unmanned plane.
4. Multi-sensor Fusion unmanned plane perception as claimed in claim 2 with evade analogue system, it is characterised in that described
Sensing data emulation module (4) includes radar simulator, infrared simulator and/or photoelectric simulation device；
Described radar simulator, for reading described true air traffic data and described imitative by described system data pond (8)
True state of flight information, and generate radar simulation data and store to described system data pond (8), then transmission is to described perception and rule
Keep away algoritic module (5)；
Described infrared simulator, for emulating the infrared intensity of the spatial domain target and background generated in scene, and by described
Infrared image stores to described system data pond (8), then transmits extremely described perception and evade algoritic module (5)；
Described photoelectric simulation device, generates containing the visible ray realtime image data of spatial domain target for emulating, and by described in real time
View data stores to described system data pond (8), then transmits extremely described perception and evade algoritic module (5).
5. Multi-sensor Fusion unmanned plane perception as claimed in claim 2 with evade analogue system, it is characterised in that described sense
Know and evade environment sensing module, the threat assessment module that algoritic module (5) includes being sequentially connected with described system data pond (8)
With evade algoritic module；
Described environment sensing module, reads each sensing in described sensing data emulation module (4) by system data pond (8)
The parameter configuration files of device, and read described perception data, further according to parameter configuration files and the described perception of described sensor
Number, according to the state estimation obtaining spatial domain target；
Described threat assessment module, is arranged by reading the algorithm parameter in system data pond (8), and by reading described environment
The data of perception algorithm module and the simulated flight status information of unmanned plane impend grade assessment, to exceeding certain threat
The spatial domain target of grade carries out collision alarm, and sends position and the speed state of spatial domain target from high to low according to threat degree
Estimate data extremely described perception and evade algoritic module (5)；
Described evade algoritic module, be used for carrying out unmanned plane optimum and evade path and resolve, and by calculation result with the form of destination
Sent to unmanned aerial vehicle platform emulation module (3) by system data pond (8).
6. Multi-sensor Fusion unmanned plane perception as claimed in claim 1 with evade analogue system, it is characterised in that described
ADS-B data module (2) includes that ADS-B IN module, described ADS-B IN module obtain the traffic position of spatial domain target by parsing
Put, height and route information, more described traffic location, height and route information are stored to described system data pond (8).
7. Multi-sensor Fusion unmanned plane perception as claimed in claim 1 with evade analogue system, it is characterised in that described
Data cube computation is gone back in system data pond (8) system evaluation module (7), and described system evaluation module (7), for from system data pond
(8) obtain in: described simulated flight status information, described true air traffic data, described simulated flight status information, described
Perception data and described optimum evade path, with Progressive symmetric erythrokeratodermia of setting aside some time the airspace perceptual scope of described analogue system and collision
Can assessment.
8. Multi-sensor Fusion unmanned plane perception as claimed in claim 1 with evade analogue system, it is characterised in that described
Data cube computation is gone back in system data pond (8) 3D real-time simulation scene display module (6), described 3D real-time simulation scene display module
(6), for coming field according to described SAA scene setting, described simulated flight status information and described true air traffic data
Scape environment Real-time modeling set, is modeled the aerial scene that meets with.
9. the emulation mode of analogue system as described in claim 1-8, it is characterised in that include step in detail below:
Step 1, the major parameter configuration being completed described analogue system by system configuration module (1) and system initialization, and will
The parameter of configuration is sent to unmanned aerial vehicle platform emulation module (3), sensing data emulation module (4) by system data pond (8)
With perception with evade algoritic module (5), complete parameter initialization；
Step 2, received the ADS-B data of air traffic by ADS-B data module (2), including the position, highly of spatial domain target
And route information, and send it to described system data pond (8) as the target machine data in traffic scene in simulated hollow；
Step 3, load by unmanned aerial vehicle platform emulation module (3) that unmanned plane is initial and unmanned aerial vehicle platform configures, and destination is entered
Line trace, then exports the simulated flight status information of unmanned aerial vehicle platform emulation module (3) to described system data pond (8)；
Step 4, obtained the perception data of each sensor by sensing data emulation module (4)；
Step 5, by perception with evade algoritic module (5), according in described step 4 obtain described perception data be calculated
Excellent path of evading, and feed back to unmanned aerial vehicle platform emulation module (3) instruct described unmanned plane optimum evade path flight.
10. the emulation mode of analogue system as claimed in claim 9, it is characterised in that described emulation mode also includes following step
Rapid:
Step 6, by 3D real-time scene display module (6), according to described SAA scene setting, described simulated flight status information and
Described true air traffic data, to scene environment Real-time modeling set, to be modeled the aerial scene that meets with, to fly the machine
Situation in scene shows in real time；
Step 7, read described simulated flight status information, described true air traffic data, described by system evaluation module (7)
Simulated flight status information, described perception data and described optimum evade path, with the airspace perceptual model to described analogue system
Enclose and collision is set aside some time and carried out Performance Evaluation.
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Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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Families Citing this family (1)
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|---|---|---|---|---|
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7272474B1 (en) * | 2004-03-31 | 2007-09-18 | Carnegie Mellon University | Method and system for estimating navigability of terrain |
| CN103869822A (en) * | 2014-04-01 | 2014-06-18 | 西北工业大学 | Multiple-rotor-wing unmanned aerial vehicle sensing and avoiding system and avoiding method thereof |
| CN104133378A (en) * | 2014-08-05 | 2014-11-05 | 中国民用航空总局第二研究所 | Real-time simulation platform for airport activity area monitoring guidance system |
| CN104503460A (en) * | 2014-12-05 | 2015-04-08 | 电子科技大学 | Ground station control system for universal unmanned aerial vehicle |
| CN105700553A (en) * | 2016-01-28 | 2016-06-22 | 中国科学院自动化研究所 | A multi-unmanned-aerial-vehicle autonomous collaborative-decision-making fast integration system |
-
2016
- 2016-07-06 CN CN201610530449.8A patent/CN106094569B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7272474B1 (en) * | 2004-03-31 | 2007-09-18 | Carnegie Mellon University | Method and system for estimating navigability of terrain |
| CN103869822A (en) * | 2014-04-01 | 2014-06-18 | 西北工业大学 | Multiple-rotor-wing unmanned aerial vehicle sensing and avoiding system and avoiding method thereof |
| CN104133378A (en) * | 2014-08-05 | 2014-11-05 | 中国民用航空总局第二研究所 | Real-time simulation platform for airport activity area monitoring guidance system |
| CN104503460A (en) * | 2014-12-05 | 2015-04-08 | 电子科技大学 | Ground station control system for universal unmanned aerial vehicle |
| CN105700553A (en) * | 2016-01-28 | 2016-06-22 | 中国科学院自动化研究所 | A multi-unmanned-aerial-vehicle autonomous collaborative-decision-making fast integration system |
Non-Patent Citations (1)
| Title |
|---|
| 李耀辉，等: "基于多源信息融合的无人机感知与规避研究", 《第29届中国控制会议》 * |
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