CN109357696A - Multiple Source Sensor information merges closed loop test framework - Google Patents
Multiple Source Sensor information merges closed loop test framework Download PDFInfo
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- CN109357696A CN109357696A CN201811134566.8A CN201811134566A CN109357696A CN 109357696 A CN109357696 A CN 109357696A CN 201811134566 A CN201811134566 A CN 201811134566A CN 109357696 A CN109357696 A CN 109357696A
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- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
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Abstract
A kind of Multiple Source Sensor information proposed by the present invention merges closed loop test framework, it is desirable to provide a kind of testing efficiency is high, and test case has the closed loop test framework of flexibility.The technical scheme is that: during the dynamic test based on scene, the target acquisition information generated in real time is sent to information fusion system and carries out use processing by sensor detection model；The evaluation index of sensor data fusion performance is resolved into a series of influent factors by information fusion system, establish the mapping relations of index and element, analysis assessment in real time is carried out by analysis evaluation module is admitted to by the fuse information of target association and Trajectory Prediction output target, the test case of scene situation and scene is adjusted according to dynamic when index fructufy, automatically generate new Test Strategy, automatic seeking is bad, Automatic-searching blending algorithm boundary and adaptability, it automatically generates and contains the real-time planning of aircraft track, can be realized the test case that test scene dynamic changes.
Description
Technical field
The present invention relates to a kind of closed-loop dynamic test structures mainly for the fusion of airborne Multiple Source Sensor information.
Background technique
Its information source of the data fusion of early stage is similar multisensor, such as more sonars, more radars, the positioning of more passive detection targets
Etc., message form is mainly sensing data.Information fusion technology makes joint-detection and association of the multisensor to target
This is possibly realized for finding that weak signal target is most important as early as possible with tracking.Information fusion, which refers to, carries intracorporal information to multiple
It carries out synthesis, handle to reach a certain purpose.Information fusion is also referred to as data fusion (datafusion), and one of information fusion
Critical function is the feedback control to information Perception and collecting device and fusion treatment process.Feedback control includes assisting to information source
Determine with the control of work, the control of sensor detection operations mode, target detection state modulator, fusion (as association determines, mesh
Mark motor-driven judgement etc.) state modulator, multiple parameters control etc. in situation and threat estimating.Information fusion technology has comparable
Complexity and difficulty, complexity are shown: the monitoring data that intentional interference or destruction will lead to Sensor Network are endless
It is whole, inaccurate, even mutually exclusive；The level of information fusion is analyzed from the angle of information, information fusion can be divided into three
Rank: data level, feature level and decision level.Pixel-based fusion is the fusion of lowest level, directly to not pretreated biography
Sensor original observed data carries out fusion treatment, is then based on fused result and carries out feature extraction and decision.Its advantage is that
Only less data amount is lost, and minute information as much as possible is maintained, so precision highest；The disadvantage is that the biography of required processing
Sensor data are too many, and the processing time is long, and real-time is poor, and can only handle the data of homogeneity sensor.Feature-based fusion is to belong to
It is tentatively to be pre-processed to sensor, and extract essential characteristic by each sensor is abstract in the fusion of the intermediate level
After vector, on this basis based on the fusion treatment of those feature vectors.Its advantage is that both having kept sufficient amount of important letter
Breath, and realizes effective data compression, reduces the requirement to bandwidth, improve treatment process real-time and anti-interference energy
Power.But due to inevitably having lost partial information, so that the performance of emerging system decreases.Decision level fusion is one
The high-level fusion of kind, is the decision that each sensor makes oneself based on oneself data collected first, on this basis
Fusion treatment is carried out further according to certain criterion, obtains a final decision.Its advantage is that the dependence to sensor is small, and allow
The information of Heterogeneous Sensor merges, and bandwidth requirement is low, strong antijamming capability.But its data degradation amount is maximum, it is comparatively smart
It spends minimum.Some scholars integrate existing technology, it is intended to establish general information fusion framework, it is desirable to be able to as much as possible by it
It is applied in various information fusion systems.But instantly there are no complete theoretical frame and Fusion Model is formed, now
The more heat transfer agent functional modes used have Dasarathy functional mode (a highly useful classification has been done to data fusion,
It is the type that is obtained according to the type of handled data or information and processing to define.Integrated command laboratory
(JDLJointDirectorsLaboratories) model has carried out the division of logic to the function that information merges, it is contained
Some functions definition of any information fusion system has closed loop to control the flowing of information, and to the function of information fusion
The division Omnibus functional mode etc. of logic is can be carried out, but they are all more or less there are more shortcoming, cannot be pushed away and wide
It.Multi-sensor data fusion can be described as Multi-Sensor Data Fusion or Multi-source Information Fusion again, refers to and utilizes different time or sky
Between multiple sensors data information, analyzed, integrated and applied according to certain criterion, obtain to the consistent of measurand
Property explain and description, to realize corresponding decision and estimation.Although there are many research about multi-sensor data fusion, arrive
Currently not yet broad sense, effective blending algorithm.So-called Multi-source Information Fusion is to make full use of different time and space
Multi-sensor information resource, using computer technology to the multisensor observation information chronologically obtained under certain criterion plus
To automatically analyze, integrate, dominate, the consistency for obtaining measurand is explained and description, obtains system with the task needed for completing
Obtain performance more superior than its each component part.Sensor information fusion be it is a kind of using mathematical method and processing technique to sensing
Data carry out comprehensive form framework, in order to obtain useful information, it is necessary to handle the informix of multi-source, specific process
It is very complicated.Mainly expertise is modeled by the rule being connected with feature in the application of information fusion.More sensings
Device information merges (MultiSensorInformationFusion) or Multi-source Information Fusion
(MultiSourceInformationFusion).Since the Fusion Method Research of early stage is for data processing, so having
When also information fusion be known as data fusion (DataFusion).According to the difference of data processing method, information fusion system
There are three types of architectures: distributed, centralized and hybrid.It is distributed: first to each standalone sensor original number obtained
According to Local treatment is carried out, result is then sent into information fusion center progress intelligent optimization combination to obtain final result again.
Demand of the distribution to communication bandwidth is low, calculating speed is fast, reliability and continuity are good, but the precision tracked is far from concentrating
Formula is high；Distributed fusion structure can be divided into the distributed fusion structure with feedback and the distributed fusion knot without feedback again
Structure.Centralization: the initial data that each sensor obtains is fed directly to central processing unit and carries out fusion treatment, Ke Yishi by centralization
The precision of existing real time fusion, data processing is high, and algorithm is flexible, the disadvantage is that the requirement to processor is high, reliability is lower, data
Amount is big, therefore is difficult to realize；Hybrid: in hybrid multi-sensor information fusion frame, operative sensor uses central fusion
Mode, remaining sensor is using distributed amalgamation mode.Hybrid fusion frame has stronger adaptability, has taken into account collection
Chinese style fusion and distributed advantage, stability are strong.The structure of hybrid amalgamation mode is more multiple than the structure of first two amalgamation mode
It is miscellaneous, thus increase the cost in communication and calculating.Indispensable in information fusion is mathematical tool, it will be all
Input data is effectively described in a public space, while suitably integrate to these data, finally with appropriate
Form exports and shows these data.Multi-source Information Fusion is primarily referred to as carrying out comprehensive point to multi-sensor information using computer
Analysis processing, to obtain the understanding to objective things essence, process has complexity with the multifarious of objective things essence
Property.Multi-source Information Fusion is an emerging data processing technique, it is using computer technology to from multisensor or more
The metrical information in source is chronologically automatically analyzed with certain criterion and integrated disposal processing, to complete required decision and sentence
It is fixed.
Due to the complication of aero-engine, the type and number of sensor sharply increase, and numerous sensors forms
Sensor array, the raw information of acquisition be often it is unordered, dispersion even wrong, only by a large amount of information into
Row fusion treatment can just obtain valuable decision information.The situation real-time detection of measured target object is gone out by sensor
Next and other data sources cooperatively constitute the information input of data fusion system.When data are after fusion treatment, it is unsatisfactory for
When expected performance indicator, so that it may the resource distribution that sensor is adjusted by increasing sensor management system, so that entirely melting
Conjunction process becomes closed loop configuration, using the gap of present fusion result and estimated performance, further adjusts sensor management strategy,
Keep fusion results close to expected performance, can accomplish that meet expected performance requirement is unlikely to that sensor is caused to provide again in this way
The waste in source, to make full use of each sensor.
The selection of test method directly affects the complexity for examining fusion treatment logic, fusion mass and performance.In addition,
From the point of view of engineering development angle, reasonable information fusion testing scheme is the necessary item guaranteed in examination blending algorithm robustness
Part advocates to merge information in definition stage, design phase carrying out scientific test and evaluation examination, can not only save manpower
Material resources, moreover it is possible to guarantee the quality of engineering development.But the implementation of the test method of current information fusion mostly concentrates on static state
Test flight data playback, the open-loop test of dynamic scene driving etc..Due to sensor itself characteristic and working environment not
Certainty, leading to sensing data includes unascertainable ingredient, makes that the true and false or the numerical value description of objective things cannot be provided
One specific judgement.For the hard decision sensor that single thresholding determines, multi-threshold is used to raw measured signal
Or become thresholding and carry out noise and clutter judgement, dependent on decision condition, (such as false-alarm probability, detection probability are converted to testing result
Confidence level) to realize detection and tracking to weak signal target or maneuvering target.It can be realized true test flight data playback to swash
Encourage test, the virtual dynamic flying data stimuli test based on scene.But from the point of view of application effect, existing information fusion test
Method is specifically included that there is also many deficiencies
1, test scene and inflexible with case script.Existing test scene and use-case are that before testing, designer is according to will assess
Fusion index targetedly design multiple typical test scenes, multiple Scene cases are then melted into test case, then into
Capable test and evaluation one by one.In general, typical test case only can be carried out the test of unitem, and test process thousand one
Rule, flexibility be not high.
2, test scene and use-case are various.As described above, being directed to different estimation items, typical test scene use-case is at hundred
Thousands of, each use-case will carry out entire testing process, greatly waste human resources.
3, assessment result is unrelated with test case.Test case cannot be generated according to assessment result, test case is usually
Realization is ready to, rather than targetedly generates test case according to the result of assessment.
Summary of the invention
The purpose of the present invention is be directed to above-mentioned existing aircraft navigation airborne sensor Multi-source Information Fusion test method not
Foot place provides a kind of testing efficiency height, the relevance of test case and evaluation index can be improved, and test case has flexibility
Multiple Source Sensor information merge closed loop test framework.
Above-mentioned purpose of the invention can be reached by the following measures, a kind of Multiple Source Sensor information fusion closed loop test
Framework, comprising: the sensor detection model in dynamic scene excitation module, the information fusion system as test object are set
System, analysis evaluation module, Test Strategy generation module and experimental data base, which is characterized in that in the dynamic test based on scene
During, aircraft track planning that sensor detection model is provided according to Test Strategy generation module Test Strategy, six are freely
Information and sensor parameters setting are spent, the target acquisition information generated in real time is sent to information fusion system and carries out information
Fusion treatment；Information merge test phase, information fusion system previously according to mission requirements, situation type information feature,
The evaluation index of sensor data fusion performance is resolved into a series of influent factors, index and element are established according to influent factor
Mapping relations, will by target association and Trajectory Prediction output target fuse information be admitted to analysis evaluation module；Analysis
Evaluation module carries out analysis assessment in real time to received fuse information data, exports analysis assessment information index data plan after tested
Slightly generation module observation, index are associated with impact analysis, find logic error, according to dynamic adjustment scene situation when index fructufy
With the test case of scene, automatically generates and new contain the test plan of new aircraft track planning and new sensor parameters
Slightly, which carries out new use-case test to dynamic scene excitation module, merges assessment result according to information,
Automatic seeking is bad, Automatic-searching blending algorithm boundary and adaptability, automatically generates and contains the real-time planning of aircraft track, Neng Goushi
The test case that existing test scene dynamic changes.
The present invention has the following beneficial effects: compared with the prior art
Testing efficiency is high.For the present invention during dynamic test based on scene, sensor detection model is according to Test Strategy
Aircraft track planning, six-degree-of-freedom information and the sensor parameters setting that generation module Test Strategy provides, will generate in real time
Target acquisition information be sent to information fusion system carry out use processing, utilize aircraft Multi-source Information Fusion analysis assessment
The observability of index automatically generates Test Strategy according to the mapping relations of evaluation index and its influent factor, realizes multi-source
The closed-loop dynamic test structure of information fusion, completes " automatic seeking is bad " process, reduces on the basis of automatically generating test case
The complexity of entire test process, improves the efficiency of system testing, can merge assessment result according to information and automatically generate
Corresponding test case improves the testing efficiency of information fusion, and the performance Automatic-searching that can be merged based on information is melted
Hop algorithm boundary and adaptability.Blending algorithm passes through fuse information to uncertain in precision higher than any single piece of information source
The fusion of property information can be such that the confidence level of target information greatly improves.
Improve the relevance of test case and evaluation index.The present invention information merge test phase, previously according to appoint
The evaluation index of information fusion performance is resolved into a series of influent factors by business demand, situation type, information feature etc., according to
Influent factor establishes the mapping relations of index and element, will be by the fuse information quilt of target association and Trajectory Prediction output target
It is sent into analysis evaluation module, difficulty of test is changed based on strategy, reaches examination fusion performance bounds, enhances test case and comment
The relevance for estimating index, by assessing the performance indicator of blending algorithm in real time during the dynamic based on scene is tested, and
It uses the method based on strategy dynamically to adjust scene situation in real time according to evaluation index result, is used for automatic examination blending algorithm
Energy boundary, Automatic-searching fusion software logic error, improve the relevance of test case and evaluation index, survey to automatically generate
Examination strategy lays the foundation.
Test case has flexibility.The present invention carries out received fuse information data using analysis evaluation module real-time
Analysis assessment, policy generation module observation, index are associated with impact analysis to output analysis assessment information index data after tested, according to
The test case that scene is adjusted when index fructufy automatically generates and new contains new aircraft track planning and new sensing
The Test Strategy of device parameter automatically generates the test case planned in real time comprising aircraft track, can be realized test scene
Dynamic changes, and with the variation of information fusion performance, the test case of generation also changes therewith, realizes that the dynamic of test scene changes
Become, to achieve the purpose that long-time uninterrupted test, improve the duration of entire test process, is calculated for examination information fusion
The robustness of method provides support.And it is capable of the task environment of dynamic generation complexity, greatly extends the flexibility of test, together
When also improve the flexibility of test case, avoid the process of artificial setting test case, reduce the investment of human resources.
Dynamic test structure proposed by the present invention is a kind of " automatic seeking is bad " process, is automatically generating test case in real time
On the basis of reduce the complexity of entire test process, improve the efficiency of system testing, while enhancing test case and commenting
Estimate the relevance of index, and be capable of the task environment of dynamic generation complexity, greatly extends the flexibility of test.It can be extensive
Applied to the multi-sensor information fusion for having the platforms such as man-machine and unmanned plane.
Detailed description of the invention
Fig. 1 is the test philosophy schematic diagram of Multiple Source Sensor information fusion closed loop test framework of the present invention.
Present invention will be further explained below with reference to the attached drawings and examples.
Specific embodiment
Refering to fig. 1.In the embodiment described below, a kind of Multiple Source Sensor information merges closed loop test framework, comprising:
Sensor detection model in dynamic scene excitation module, the information fusion system as test object, analysis assessment are set
Module, Test Strategy generation module and experimental data base.Wherein, sensor is using radar, UV chain, photodetection etc., sensor
Model primitive is off-mode.Information fusion system is the Project Realization of Multi-source Information Fusion algorithm as test object.
Experimental data base saves the detection information of dynamic scene excitation module in closed loop test process in real time, information fusion system information is melted
The data for closing information, analysis evaluation module output, provide data supporting for ex-post analysis.
During the dynamic test based on scene, sensor detection model tests plan according to Test Strategy generation module
Aircraft track planning, six-degree-of-freedom information and the sensor parameters setting slightly provided, the target acquisition information that will be generated in real time
It is sent to information fusion system and carries out use processing；Information merge test phase, information fusion system previously according to appoint
The evaluation index of sensor data fusion performance is resolved into a series of influent factors by the information feature of business demand, situation type,
The mapping relations that index and element are established according to influent factor will be believed by the fusion of target association and Trajectory Prediction output target
Breath is sent into analysis evaluation module；It analyzes evaluation module and analysis assessment in real time, output analysis is carried out to received fuse information data
Assessing information index data, policy generation module observation, index are associated with impact analysis after tested, logic error are found, according to index
Adjustment dynamic adjusts the test case of scene situation and scene when fructufy, automatically generates the new new aircraft track that contains and advises
It draws and the Test Strategy of new sensor parameters, the Test Strategy closed loop feedback carries out new use to dynamic scene excitation module
Example test merges assessment result according to information, and automatic seeking is bad, and Automatic-searching blending algorithm boundary and adaptability automatically generate packet
The real-time planning for having contained aircraft track can be realized the test case that test scene dynamic changes.
Dynamic scene excitation module has control simulation run, telecommunication management, offer sensor model control by built-in
The dynamic scene excitation software run, issue sensor die shape parameter, obtaining flying platform data etc..Pass through built-in dynamic scene
It motivates software load to generate initial platform motion profile and the sensor parameters list of this test, starts this test assignment.
The target data real-time Transmission that dynamic scene excitation software exports sensor model is to information fusion system to be measured
Software is assessed with analysis.Information fusion system to be measured carries out fusion treatment to sensor model detection result, and by processing result
It is sent to analysis assessment software.
The built-in analysis assessment software of evaluation module is analyzed, analysis assessment software counts the evaluation index of fusion front and back
It calculates, calculated result input adaptive Test Strategy generates software.
Analysis evaluation module determines that the evaluation index of this test, the evaluation index of test are adopted according to the demand of fusion test
With fusion before with merge after targetpath quality.If this test purpose tested is test target track in high-speed maneuver condition
Under (such as heavy dense targets flight, the high maneuvering flight of targeted cache), there is stable track to export after being still able to maintain fusion, this survey
The evaluation index of examination is stability, the targetpath quantity of targetpath.
Test Strategy generation module is by built-in adaptive testing strategy generating software according to evaluation index result
And test purpose generates new Test Strategy, Test Strategy moves track adaptive correction to current both sides, generates new platform
List is arranged in motion profile and sensor parameters.
Adaptive testing strategy generating software firstly generates the initial testing strategy of this test, according to initial testing strategy
It carries out both sides and moves trajectory planning, generating platform motion profile and sensor parameters initial setting up list.Then in test process
Middle test purpose and real-time evaluation index according to this test is as a result, dynamic adjusts the ginseng of both sides' motion profile and sensor
Number.It is exemplified below:
Test purpose: influence of the different sensors using combination to fusion results；Test Strategy: according to the effect of each sensor away from
From the switching sequence that stochastic and dynamic generates each sensor, to change the use combination of sensor；
Test purpose: sensor detection performance declines the influence to fusion results；
Test Strategy: according to the detection performance of each sensor, dynamic changes the kinetic characteristic of target, so that target is carried out high maneuver and flies
Row, if S type flies, underriding draws high flight etc., so as to cause the decline of sensor detection performance.
The foregoing is merely presently preferred embodiments of the present invention, is merely illustrative for the purpose of the present invention, and not restrictive
's.Those skilled in the art understand that it can be carried out in the spirit and scope defined by the claims in the present invention it is many change,
It modifies, is even equivalent, but falling in protection scope of the present invention.
Claims (10)
1. a kind of Multiple Source Sensor information merges closed loop test framework, comprising: the sensing in dynamic scene excitation module is arranged in
Device detection model, the information fusion system as test object, analysis evaluation module, Test Strategy generation module and test data
Library, which is characterized in that during the dynamic test based on scene, sensor detection model is according to Test Strategy generation module
Aircraft track planning, six-degree-of-freedom information and the sensor parameters setting that Test Strategy provides, the target generated in real time is visited
Measurement information is sent to information fusion system and carries out use processing；Test phase is merged in information, information fusion system is preparatory
According to the information feature of mission requirements, situation type, the evaluation index of sensor data fusion performance is resolved into a series of shadows
Element is rung, the mapping relations of index and element are established according to influent factor, target will be exported by target association and Trajectory Prediction
Fuse information be admitted to analysis evaluation module, to received fuse information data carry out in real time analysis assessment, output analysis comment
Estimate information index data policy generation module observation, index association impact analysis after tested, logic error is found, according to index knot
Dynamic adjusts the test case of scene situation and scene when fruit, automatically generate it is new contain new aircraft track planning and
The Test Strategy of new sensor parameters, the Test Strategy closed loop feedback carry out new use-case to dynamic scene excitation module and survey
Examination merges assessment result according to information, and automatic seeking is bad, and Automatic-searching blending algorithm boundary and adaptability are automatically generated and contained
The real-time planning of aircraft track can be realized the test case that test scene dynamic changes.
2. Multiple Source Sensor information as described in claim 1 merges closed loop test framework, it is characterised in that: experimental data base is real
The detection information of dynamic scene excitation module, information fusion system information fuse information, analysis in Shi Baocun closed loop test process
The data of evaluation module output, provide data supporting for ex-post analysis.
3. Multiple Source Sensor information as described in claim 1 merges closed loop test framework, it is characterised in that: dynamic scene excitation
There is module control simulation run, telecommunication management, offer sensor model control to run, issue sensor model ginseng built in
Number, the dynamic scene for obtaining flying platform data motivate software, motivate software load to generate this survey by built-in dynamic scene
The initial platform motion profile of examination and sensor parameters list, start this test assignment.
4. Multiple Source Sensor information as claimed in claim 3 merges closed loop test framework, it is characterised in that: dynamic scene excitation
The target data real-time Transmission that software exports sensor model is to information fusion system to be measured and analysis assessment software.
5. Multiple Source Sensor information as claimed in claim 4 merges closed loop test framework, it is characterised in that: merged to measurement information
System carries out fusion treatment to sensor model detection result, and processing result is sent to analysis assessment software.
6. Multiple Source Sensor information as described in claim 1 merges closed loop test framework, it is characterised in that: analysis evaluation module
Software is assessed in built-in analysis, and analysis assessment software calculates the evaluation index of fusion front and back, calculated result input adaptive
Test Strategy generates software.
7. Multiple Source Sensor information as described in claim 1 merges closed loop test framework, it is characterised in that: analysis evaluation module
Determine the evaluation index of this test according to the demand of fusion test, the evaluation index of test using before fusion with merge after target
Flight path quality；The evaluation index of this test is stability, the targetpath quantity of targetpath.
8. Multiple Source Sensor information as described in claim 1 merges closed loop test framework, it is characterised in that: Test Strategy generates
It is raw according to evaluation index result and test purpose to generate software by built-in adaptive testing strategy generating software for module
The Test Strategy of Cheng Xin, Test Strategy move track adaptive correction to current both sides, generate new platform motion profile and biography
Sensor parameter setting list.
9. Multiple Source Sensor information as described in claim 1 merges closed loop test framework, it is characterised in that: adaptive testing plan
The initial testing strategy that software firstly generates this test is slightly generated, both sides are carried out according to initial testing strategy and move track rule
It draws, generating platform motion profile and sensor parameters initial setting up list.
10. Multiple Source Sensor information as described in claim 1 merges closed loop test framework, it is characterised in that: adaptive testing
Strategy generating software is during the test according to the test purpose of this test and real-time evaluation index as a result, dynamic adjustment is double
The parameter of square motion profile and sensor.
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| CN111695614A (en) * | 2020-05-28 | 2020-09-22 | 中国农业大学 | Dynamic monitoring sensor layout and multi-source information fusion method and system |
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| CN114623816A (en) * | 2022-02-16 | 2022-06-14 | 中国电子科技集团公司第十研究所 | Method and device for tracking and maintaining airborne fusion information guide sensor |
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