CN106601032B - A kind of multipath landform integrality detection method based on lower view sensor - Google Patents
A kind of multipath landform integrality detection method based on lower view sensor Download PDFInfo
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- G—PHYSICS
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- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
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- G08G5/0086—Surveillance aids for monitoring terrain
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Abstract
The invention discloses a kind of multipath landform integrality detection method based on lower view sensor, belong to avionics system field, to make pilot believe, synthetic vision system is capable of providing accurate external sights, it is desirable that has certain integrity monitoring and alarm ability.Method disclosed by the invention detects the consistent degree for the actual landform data that airborne topographic database is measured with lower view sensor in real time, and when the two deviation is more than given threshold, warning information is sent out to pilot.It specifically includes：Airborne profile database sampling algorithm, sensor measurement data synthesis landform algorithm, multipath detected algorithm and statistical test algorithm.The method can detect the horizontal error and vertical error of terrain data simultaneously, and accuracy of detection is not influenced by aspect, and accuracy of detection is high, and real-time is good, to flight safety important in inhibiting.
Description
Technical field
The invention belongs to avionics system fields, and in particular in synthetic vision system, one kind being based on lower view sensor
Multipath landform integrality detection method.
Background technology
In order to make pilot believe, synthetic vision system (SVS) is capable of providing accurate external sights, and be safe from danger misleading
Information, system requirements have certain integrity monitoring and alarm ability.If integrity detection finds airborne profile database
It being mismatched with actual landform, display system will send out alarm to pilot, prompt Synthetic vision unreliable and cannot use, with
It reduces to provide pilot and endangers misleading terrain information.
The purpose of landform integrity detection is to detect airborne topographic database in real time to measure practically with lower view sensor
The consistent degree of graphic data rather than the correctness of airborne profile database.Its key technology, first, airborne profile database sampling mould
The foundation of type, model should measure characteristic close to echo altimeter to greatest extent, to ensure accuracy of detection, second is that how to examine simultaneously
Vertical error and horizontal transfer error are tested, third, reducing alarm time, sends out warning information to pilot in time, ensures flight peace
Entirely.
Invention content
It is an object of the invention to solve the deficiency of existing landform integrality detection method in synthetic vision system, it is proposed that
A kind of multipath landform integrality detection method based on lower view sensor.
The multipath landform integrality detection method based on lower view sensor of the present invention, including following steps：
Step 1：Airborne profile database sampling；
Step 2：Calculate synthesis Terrain Elevation；
Step 3：Counting statistics inspected number；
Step 4：Multipath detected；
Step 5：Hypothesis testing, if the actual landform data that airborne profile database is measured with lower view sensor differ
Cause degree exceeds given threshold, then sends out warning information to pilot.
The advantage of the invention is that：
(1) in existing airborne profile database sampling algorithm, what sampling model assumed echo altimeter measurement mostly is winged
Plumb height immediately below machine, this limitation cause sampling error of the aircraft in pitching and roll attitude, and this error
It easily appears in the case of taking off and land etc. to landform integrity demands height.The sampling model proposed in the present invention, gram
This limitation is taken, no matter which kind of posture aircraft is in, and keeps high-precision landform integrity detection；
(2) in the present invention, when to airborne profile database sampling, intersection detection and bilinearity difference has been used, has been protected
While demonstrate,proving sampling precision, efficiency is improved to greatest extent；
(3) existing landform integrity detection is detected using single path mostly, is only capable of vertical error in detection topographic database,
Especially when topography is flat, horizontal transfer error in topographic database, multipath inspection used in the present invention can not be detected
It surveys and provides a kind of method detecting horizontal error in topographic database, while detecting vertical error and horizontal error, improve
Landform integrity detection ability.
Description of the drawings
Fig. 1 is the flow chart of the present invention；
Fig. 2 is airborne profile database sampling model schematic；
Fig. 3 is synthesis landform instrumentation plan；
Fig. 4 is synthetic vision system landform integrity detection event tree.
Specific implementation mode
Below in conjunction with drawings and examples, the present invention is described in further detail.
The multipath landform integrality detection method based on lower view sensor of the present invention, passes through multipath detected and statistics
Algorithm is learned, the consistent degree for the actual landform data that airborne topographic database is measured with lower view sensor is detected in real time, when the two is inclined
When difference is more than given threshold, warning information is sent out to pilot.
The present invention a kind of multipath landform integrality detection method based on lower view sensor, as shown in Figure 1, include with
Lower step：
Step 1：Airborne profile database sampling.
As shown in Fig. 2, in synthetic vision system, it is high being surveyed comprising radar using echo altimeter installation site as origin
It counts in beam area, sends out ray along echo altimeter antenna direction, intersection detection is carried out with landform, take nearest with plane distance
Point calculates sampled point height value as the sampled point compared with echo altimeter measured value, and using bilinear interpolation method
hDEM(latDGPS(ti),lonDGPS(ti)), and then obtain topographic database terrain profile.
Wherein, ray and the nearest sampled point of selected distance aircraft are sent out along echo altimeter antenna direction, and non-aircraft
Vertical direction sampled point, it is therefore an objective to sampling model be made to measure characteristic closer to echo altimeter.Sampled point height value is calculated, except double
Outside linear interpolation algorithm, closest interpolation method and cubic convolution interpolation method also may be selected, but closest interpolation method precision is low, three times
Convoluting interpolation method calculation amount is excessive, to meet the requirement of real-time and precision, present invention selection bilinear interpolation simultaneously.
Step 2：Calculate synthesis Terrain Elevation.
As shown in figure 3, synthesis terrain profile is the ground level on sea level or more:
hsynth(ti)=hDGPS(ti)-(hradalt(ti)+hantenna)
Wherein, hDGPSIt is height value of the aircraft more than sea level for having DGPS to provide；hantennaGPS antenna top with
The difference in height of echo altimeter antenna low side；hradaltIt is the measured value of echo altimeter.
Step 3：Counting statistics inspected number.
(1) echo altimeter is measured to the absolute error p of synthesis terrain profile and topographic database sampling terrain profile
(ti) be defined as：
p(ti)=hSYNT(ti)-hDEM(latDGPS,lonDGPS)
Wherein, hDEM(latDGPS,lonDGPS) it is topographic database mesorelief height, hSYNT(ti) be landform synthesis it is high
Degree.
(2) to absolute error p (ti) Kalman filtering is carried out, reduce sensor and digital elevation model (Digital
Elevation Model, vehicle economy M) specified noise in data and estimate sensor and the deviation of DEM, it is as follows：
1) predicted value is initializedAnd error variance
Wherein,It is 0 according to hypothesis system model,Value range be ((15)2,(20)2)；
Calculate Kalman filter gain：
Wherein, KkIt is Kalman filtering gain,It is the error variance of laststate, HkIt is unit domain transformation matrix, RkIt is
The measured value of error variance is constant；
2) estimated value of sampled value is updated：
Wherein,It is tkThe estimated value at moment,It is laststate estimated value, zkIt is in tkThe measured value at moment；
3) error variance of estimated value is calculated
Wherein, PkIt is the error variance of estimated value；
4) predicted value is calculated
Wherein,It is tk+1The predicted value at moment, ΦkFor unit state-transition matrix,It is tk+1The prediction at moment misses
Poor variance, QkIt is system noise variance, referred to as tuner parameters of filter are constant；
5) it returns 2), above procedure is repeated, until system operation terminates.
(3) statistical check amount is defined：
Wherein, T is statistical check amount, and P is the estimated value of error variance, and N is the number of sampled point,It is by card
Absolute error after Kalman Filtering.
Step 4：Multipath detected.
(1) flight path is carried out horizontal-shift, a plurality of flight path is obtained, according to step by dummy level DEM Transfer Errors
Method in rapid three calculates multipath statistical check amount：
Wherein, T (m, n) is statistical check amount；
latDGPS=latDGPS(ti)+lat_offmm∈(1,M)；
lonDGPS=lonDGPS(ti)+lon_offn n∈(1,N)。
(2) statistical check amount T in calculating 1, possesses the offset path of minimum T values, it is considered to be aircraft is in topographic database
Current horizontal location, be defined as：
Wherein, min () function returns to estimated location,It is the minimum value of statistic T.
Define TV(ti)=TminFor vertical error inspected number.TminIt is inspected number minimum value.
(3) estimated location is defined as topographic database estimated location lonDBPAnd latDBP；Actual position is defined as
lontrueAnd lattrue, calculate horizontal error between the two：
pH=dist ([lonDBP,latDBP],[lontrue,lattrue])
Wherein, dist () returns to 2 points in space of distance；lontrue,lattrueFor the measurement position of DGPS.
(4) calculated level error statistics inspected number.
Wherein σpFor standard deviation.
Step 5：Hypothesis testing is carried out, event tree is as shown in Figure 4.If airborne profile database is measured with lower view sensor
Actual landform data inconsistent degree exceed given threshold, then send out warning information to pilot.
(1) two mutually contradictory hypothesis are proposed：
Null hypothesis H0：System is operated in rated condition or does not find run-time error；
Wherein,It is 0 to obey mean value, standard deviation σpNormal distribution；
Alternative hypothesis H1：System operation finds mistake；
Wherein,Obedience mean value is μB, standard deviation σpNormal distribution.
(2) it is alerted as three kinds of auxiliary, key element, tactics element different applications to omitting according to synthetic vision system
Probability sets three secure thresholds and determines fault alarm PFFD, omit alarm PMDProbability, for three kinds of applications to safe class
Difference requires, and omits alarm probability and is respectively set as：Less than 10-3, 10-4~10-7,10-6~10-9, wherein
PFFD=P (detect mistake | H0)·P(H0)
PMD=P (mistake is not detected | H1)·P(H1)
It is tested through practical flight, takes the inspection threshold value T of suitable vertical error-tested amount and horizontal error inspected numberVDAnd THD
Value, meets PFFDAnd PMDIt is required that.
(3) vertical error inspected number and horizontal error inspected number are tested and is made a policy respectively, if being less than step
Three, the vertical check threshold value T in step 4 and horizontal check threshold value TH, then receive H0, conversely, then refusing H0。
(4) as refusal H0When, synthetic vision system sends out warning information to pilot, as reception H0When, then it represents that system is transported
Row is normal.
Particular embodiments described above has carried out further in detail the purpose of the present invention, technical solution and advantageous effect
It describes in detail bright, it should be understood that the above is only a specific embodiment of the present invention, is not intended to restrict the invention, it is all
Within the spirit and principles in the present invention, any modification, equivalent substitution, improvement and etc. done should be included in the guarantor of the present invention
Within the scope of shield.
Claims (2)
1. a kind of multipath landform integrality detection method based on lower view sensor, includes the following steps：
Step 1：Airborne profile database sampling；
In synthetic vision system, using echo altimeter installation site as origin, in echo altimeter beam area, along radar
Altimeter antenna direction sends out ray, and intersection detection is carried out with landform, take with plane distance closest approach, as with echo altimeter
The sampled point that measured value compares calculates sampled point height value hDEM(latDGPS(ti),lonDGPS(ti)), wherein latDGPS(ti)
Indicate tiMoment latitude determination value, lonDGPS(ti) indicate tiMoment longitude measurement；
Step 2：Calculate synthesis Terrain Elevation；
Synthesis terrain profile is the ground level on sea level or more:
hsynth(ti)=hDGPS(ti)-(hradalt(ti)+hantenna)
Wherein, hDGPSThe height value for being aircraft more than sea level；hantennaIt is that GPS antenna top is low with echo altimeter antenna
The difference in height at end；hradaltIt is the measured value of echo altimeter；
Step 3：Calculate vertical statistical check amount；
(1) the absolute error p (t that echo altimeter measures synthesis terrain profile and topographic database sampling terrain profile are obtainedi)：
p(ti)=hSYNT(ti)-hDEM(latDGPS,lonDGPS)
Wherein, hDEM(latDGPS,lonDGPS) it is topographic database mesorelief height, hSYNT(ti) be landform synthesis height；
(2) to absolute error p (ti) carry out Kalman filtering；
(3) vertical statistical check amount is obtained：
Wherein, T is vertical statistical check amount, and P is the estimated value of error variance, and N is the number of sampled point,It is by karr
Graceful filtered absolute error；
Step 4：Multipath detected；
(1) flight path is carried out horizontal-shift by dummy level DEM Transfer Errors, obtains a plurality of flight path, calculates multipath
Statistical check amount：
Wherein, T (m, n) is statistical check amount；M, N indicates latitude, longitude offset maximum value respectively；
latDGPS=latDGPS(ti)+lat_offmm∈(1,M)；
lonDGPS=lonDGPS(ti)+lon_offnn∈(1,N)；
(2) set the offset path of minimum T values as aircraft topographic database current horizontal location：
Wherein, min () function returns to estimated location,It is the minimum value of statistic T；
(3) latitude, longitude of estimated location are the latitude and longitude of topographic database estimated location, are respectively defined as lonDBP
And latDBP；Longitude, the latitude of actual position are respectively lontrueAnd lattrue, calculate horizontal error between the two：
pH=dist ([lonDBP,latDBP],[lontrue,lattrue])
Wherein, dist () returns to 2 points in space of distance；
(4) calculated level error statistics inspected number；
Wherein：σpFor standard deviation；
Step 5：Hypothesis testing is carried out, if the actual landform data that airborne profile database is measured with lower view sensor differ
Cause degree exceeds given threshold, then sends out warning information to pilot；
(1) two mutually contradictory hypothesis are proposed：
Null hypothesis H0：Synthetic vision system is operated in rated condition or does not find run-time error；
Wherein,It is 0 to obey mean value, standard deviation σpNormal distribution；
Alternative hypothesis H1：Synthetic vision system operation finds mistake；
Wherein,Obedience mean value is μB, standard deviation σpNormal distribution；
(2) the fault alarm P of synthetic vision system is determinedFFD, omit alarm PMDProbability：
PFFD=P (detect mistake | H0)·P(H0)
PMD=P (mistake is not detected | H1)·P(H1)
(3) vertical error inspected number and horizontal error inspected number are tested and is made a policy respectively, if being less than Step 3: step
Vertical check amount in rapid four and horizontal check amount, then receive H0, conversely, then refusing H0；
(4) as refusal H0When, synthetic vision system sends out warning information to pilot, as reception H0When, then it represents that Synthetic vision system
System normal operation.
2. a kind of multipath landform integrality detection method based on lower view sensor according to claim 1, described
(2) are specially in step 3：
1) predicted value is initializedAnd error variance It is 0 according to hypothesis system model,Value range be ((15)2,
(20)2)；
Calculate Kalman filter gain：
Wherein, KkIt is Kalman filtering gain,It is the error variance of laststate, HkIt is unit domain transformation matrix, RkIt is error
The measured value of variance；
2) estimated value of sampled value is updated：
Wherein,It is tkThe estimated value at moment,It is laststate estimated value, zkIt is in tkThe measured value at moment；
3) error variance of estimated value is calculated
Wherein, PkIt is the error variance of estimated value；
4) predicted value is calculated
Wherein,It is tk+1The predicted value at moment, ΦkFor unit state-transition matrix,It is tk+1The prediction error side at moment
Difference, QkIt is system noise variance, referred to as tuner parameters of filter；
5) return to step 2), until terminating.
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| EP3862784A1 (en) * | 2020-02-04 | 2021-08-11 | Honeywell International Inc. | Methods and systems for monitoring a fault condition of a radar altitude device |
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| CN108681616B (en) * | 2018-03-28 | 2022-05-17 | 中国电子科技集团公司第三十六研究所 | Method and device for selecting installation point of antenna outside airplane cabin and intelligent terminal |
| CN112669671B (en) * | 2020-12-28 | 2022-10-25 | 北京航空航天大学江西研究院 | Mixed reality flight simulation system based on physical interaction |
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| CN101539417A (en) * | 2009-04-23 | 2009-09-23 | 中国农业大学 | On-board 3D terrain automatic measuring system and method |
| CN103339525A (en) * | 2010-12-21 | 2013-10-02 | 塔莱斯公司 | Method and device for monitoring variations in terrain |
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