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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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 the field of avionic systems, and particularly relates to a multipath terrain integrity detection method based on a downward-looking sensor in a synthetic vision system.
Background
In order for the pilot to believe that the Synthetic Vision System (SVS) can provide an accurate appearance without danger misleading information, the system requires certain integrity monitoring and warning capabilities. If the integrity detection finds that the airborne terrain database is not matched with the actual terrain, the display system gives an alarm to the pilot to prompt that the synthetic view is unreliable and unusable, so that the risk of providing misleading terrain information to the pilot is reduced.
The purpose of the terrain integrity test is to detect the consistency of the airborne terrain database with the actual terrain data measured by the look-down sensor in real time, rather than the correctness of the airborne terrain database. The method has the key technologies that firstly, an airborne terrain database sampling model is established, the model should be close to the measurement characteristics of a radar altimeter to the maximum extent so as to ensure the detection precision, secondly, how to simultaneously detect the vertical error and the horizontal transfer error, thirdly, the alarm time is reduced, the alarm information is sent to a pilot in time, and the flight safety is ensured.
Disclosure of Invention
The invention aims to overcome the defects of the existing terrain integrity detection method in a composite vision system, and provides a multipath terrain integrity detection method based on a downward-looking sensor.
The invention discloses a multipath terrain integrity detection method based on a downward-looking sensor, which comprises the following steps:
the method comprises the following steps: sampling an airborne terrain database;
step two: calculating the height of the synthesized terrain;
step three: calculating a statistical test quantity;
step four: detecting a multipath;
step five: and (4) supposing the test, if the inconsistency between the onboard terrain database and the actual terrain data measured by the downward-looking sensor exceeds a set threshold value, sending alarm information to the pilot.
The invention has the advantages that:
(1) in the existing airborne terrain database sampling algorithm, a sampling model mostly assumes that a vertical height measured by a radar altimeter is right below an airplane, the limitation causes sampling errors of the airplane in pitching and rolling postures, and the errors are easy to appear under the condition that the requirements of the airplane on the terrain integrity such as takeoff and landing are high. The sampling model provided by the invention overcomes the limitation, and high-precision terrain integrity detection is kept no matter what attitude the aircraft is in;
(2) in the invention, when the airborne terrain database is sampled, intersection detection and bilinear difference are used, so that the efficiency is improved to the maximum extent while the sampling precision is ensured;
(3) the multi-path detection used by the invention provides a method for detecting horizontal errors in the terrain database, and simultaneously detects vertical errors and horizontal errors, thereby improving the detection capability of the terrain integrity.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a schematic view of an airborne terrain database sampling model;
FIG. 3 is a schematic view of a synthetic terrain measurement;
fig. 4 is a tree of synthetic view system terrain integrity detection events.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
The multipath terrain integrity detection method based on the downward-looking sensor detects the consistency of the airborne terrain database and the actual terrain data measured by the downward-looking sensor in real time through multipath detection and a statistical algorithm, and sends out warning information to a pilot when the deviation of the airborne terrain database and the actual terrain data exceeds a set threshold value.
The invention discloses a multipath terrain integrity detection method based on a downward-looking sensor, which comprises the following steps as shown in figure 1:
the method comprises the following steps: and sampling an airborne terrain database.
As shown in FIG. 2, in the synthetic view system, the installation position of the radar altimeter is used as the origin, rays are emitted along the antenna direction of the radar altimeter within the wave beam range containing the radar altimeter, the intersection detection is carried out with the terrain, the closest point to the airplane is taken as a sampling point to be compared with the measurement value of the radar altimeter, and the bilinear interpolation method is adopted to calculate the height value h of the sampling pointDEM(latDGPS(ti),lonDGPS(ti) And then obtaining a terrain profile of the terrain database.
The method comprises the steps of sending rays along the antenna direction of the radar altimeter, selecting a sampling point closest to an airplane instead of a sampling point in the vertical direction of the airplane, and aiming at enabling a sampling model to be closer to the measurement characteristic of the radar altimeter. And calculating the height value of the sampling point, and selecting a nearest neighbor interpolation method and a cubic convolution interpolation method besides a bilinear interpolation algorithm, wherein the nearest neighbor interpolation method has low precision, and the cubic convolution interpolation method has overlarge calculated amount, so that the requirements of real-time property and precision are met simultaneously.
Step two: the synthetic terrain height is calculated.
As shown in fig. 3, the resultant terrain profile is the ground height above sea level:
hsynth(ti)＝hDGPS(ti)-(hradalt(ti)+hantenna)
wherein h isDGPSIs the height value above sea level of an airplane provided by DGPS; h isantennaIs the height difference between the top end of the GPS antenna and the low end of the radar altimeter antenna; h isradaltIs the measurement of a radar altimeter.
Step three: and calculating the statistical test quantity.
(1) Measuring absolute error p (t) of synthesized terrain contour and terrain contour sampled by terrain database by radar altimeteri) Is defined as:
p(ti)＝hSYNT(ti)-hDEM(latDGPS,lonDGPS)
wherein h isDEM(latDGPS,lonDGPS) Is the height of the terrain in the terrain database, hSYNT(ti) Is the composite height of the terrain.
(2) For absolute error p (t)i) Performing Kalman filtering, reducing rated noise in data of a sensor and a digital elevation Model (DEM for short), and estimating the deviation between the sensor and the DEM, wherein the method comprises the following specific steps:
1) initializing a prediction valueSum error variance
Wherein,according to the assumption that the system model is 0,has a value range of ((15)2,(20)2)；
Calculating a Kalman filter gain:
wherein, KkIs the gain of the kalman filter, and,is the error variance of the previous state, HkIs a unit domain transform matrix, RkIs a measure of the error variance, which is constant;
2) updating the estimated value of the sampling value:
wherein,is tkAn estimate of the time of day is determined,is the last state estimate, zkIs at tkA measured value of time of day;
3) calculating error variance of estimated value
Wherein, PkIs the error variance of the estimated value;
4) calculating a predicted value
Wherein,is tk+1Predicted value of time, phikIn the form of a unit state transition matrix,is tk+1Variance of prediction error of time, QkIs the system noise variance, called the tuning parameter of the filter, which is a constant;
5) and returning to 2), repeating the above processes until the system operation is finished.
(3) Defining the statistical test quantity:
where T is the statistical test quantity, P is the estimated value of the error variance, N is the number of sample points,is the absolute error after kalman filtering.
Step four: and (4) multi-path detection.
(1) Simulating a horizontal DEM transfer error, horizontally offsetting the flight paths to obtain a plurality of flight paths, and calculating the multipath statistical test quantity according to the method in the third step:
wherein T (m, n) is a statistical test quantity;
latDGPS＝latDGPS(ti)+lat_offmm∈(1,M)；
lonDGPS＝lonDGPS(ti)+lon_offnn∈(1,N)。
(2) the statistical test quantity T in calculation 1, the deviation path with the smallest value of T, which is considered to be the current horizontal position of the aircraft in the terrain database, is defined as:
where the min () function returns the estimated position,is the minimum value of the statistic T.
Definition of TV(ti)＝TminIs a vertical error check quantity. T isminIs the check quantity minimum.
(3) Defining an estimated position as an estimated position lon for a terrain databaseDBPAnd latDBP(ii) a The true position is defined as lontrueAnd lattrueCalculating the horizontal error between the two:
pH＝dist([lonDBP,latDBP],[lontrue,lattrue])
wherein dist () returns the distance of two points in space; lontrue,lattrueIs the measured position of DGPS.
(4) And calculating the statistical test quantity of the horizontal error.
Wherein sigmapIs the standard deviation.
Step five: a hypothesis test is performed and the event tree is shown in fig. 4. And if the inconsistency between the airborne terrain database and the actual terrain data measured by the downward-looking sensor exceeds a set threshold value, sending alarm information to the pilot.
(1) Two mutually opposite assumptions are proposed:
primitive hypothesis H0: the system works in a rated state or no operation error is found;
wherein,obedience mean 0, standard deviation σpNormal distribution of (2);
alternative hypothesis H1: the system runs to find errors;
wherein,obey mean value of muBStandard deviation of σpIs normally distributed.
(2) Setting three safety thresholds for the missed alarm probability to determine the false alarm P according to the three different applications of the synthetic vision system as an auxiliary, key and tactical elementsFFDMissing alarm PMDThe probability of missing alarm is respectively set as follows according to different requirements of three applications on the safety level: less than 10-3，10-4～10-7,10-6～10-9Wherein
PFFDP (error detected | H)0)·P(H0)
PMDP (no error detected | H)1)·P(H1)
Through actual flight experiment, a proper detection threshold value T of a vertical error detection quantity and a horizontal error detection quantity is obtainedVDAnd THDValue of, satisfies PFFDAnd PMDThe method is required.
(3) Respectively checking the vertical error checking quantity and the horizontal error checking quantity and making a decision, if the vertical error checking quantity and the horizontal error checking quantity are smaller than the vertical checking threshold T and the horizontal checking threshold T in the third step and the fourth stepHThen receive H0Otherwise, reject H0。
(4) When rejecting H0The synthetic vision system sends out warning information to the pilot, and when receiving H0And if so, indicating that the system is normally operated.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (2)
1. A multipath terrain integrity detection method based on a downward-looking sensor comprises the following steps:
the method comprises the following steps: sampling an airborne terrain database;
in the synthetic vision system, the installation position of a radar altimeter is taken as an original point, rays are emitted along the antenna direction of the radar altimeter within the wave beam range of the radar altimeter, intersection detection is carried out on the rays and the terrain, the point closest to the airplane is taken as a sampling point to be compared with the measurement value of the radar altimeter, and the height value h of the sampling point is calculatedDEM(latDGPS(ti),lonDGPS(ti) Wherein, latDGPS(ti) Represents tiTime of day latitude measurement, lonDGPS(ti) Represents tiA time of day longitude measurement;
step two: calculating the height of the synthesized terrain;
the synthetic terrain profile is the ground height above sea level:
hsynth(ti)＝hDGPS(ti)-(hradalt(ti)+hantenna)
wherein h isDGPSThe height value of the airplane above the sea level; h isantennaIs the height difference between the top end of the GPS antenna and the low end of the radar altimeter antenna; h isradaltIs the measurement of a radar altimeter;
step three: calculating a vertical statistical test quantity;
(1) obtaining the absolute error p (t) of the synthetic terrain profile measured by the radar altimeter and the sampling terrain profile of the terrain databasei)：
p(ti)＝hSYNT(ti)-hDEM(latDGPS,lonDGPS)
Wherein h isDEM(latDGPS,lonDGPS) Is the height of the terrain in the terrain database, hSYNT(ti) Is the composite height of the terrain;
(2) for absolute error p (t)i) Performing Kalman filtering;
(3) obtaining vertical statistical test quantity:
where T is the vertical statistical test quantity, P is the estimated value of the error variance, N is the number of sample points,is the absolute error after kalman filtering;
step four: detecting a multipath;
(1) simulating a horizontal DEM transfer error, horizontally offsetting the flight paths to obtain a plurality of flight paths, and calculating a multi-path statistical test quantity:
wherein T (m, n) is a statistical test quantity; m, N denotes latitude and longitude offset maximum values, respectively;
latDGPS＝latDGPS(ti)+lat_offmm∈(1,M)；
lonDGPS＝lonDGPS(ti)+lon_offnn∈(1,N)；
(2) and setting the deviation path of the minimum T value as the current horizontal position of the airplane in the terrain database:
where the min () function returns the estimated position,is the minimum of the statistic T;
(3) the latitude and longitude of the estimated position are the latitude and longitude of the estimated position in the terrain database, and are respectively defined as lonDBPAnd latDBP(ii) a The longitude and latitude of the real position are respectively lontrueAnd lattrueCalculating the horizontal error between the two:
pH＝dist([lonDBP,latDBP],[lontrue,lattrue])
wherein dist () returns the distance of two points in space;
(4) calculating the statistical test quantity of the horizontal errors;
wherein: sigmapIs the standard deviation;
step five: performing hypothesis test, and if the inconsistency between the airborne terrain database and the actual terrain data measured by the downward-looking sensor exceeds a set threshold value, sending warning information to the pilot;
(1) two mutually opposite assumptions are proposed:
primitive hypothesis H0: the synthetic vision system works in a rated state or no operation error is found;
wherein,obedience mean 0, standard deviation σpNormal distribution of (2);
alternative hypothesis H1: the synthetic vision system is operated to find errors;
wherein,obey mean value of muBStandard deviation of σpNormal distribution of (2);
(2) determining false alarms P for composite vision systemsFFDMissing alarm PMDProbability of (c):
PFFDp (error detected | H)0)·P(H0)
PMDP (no error detected | H)1)·P(H1)
(3) Respectively checking the vertical error checking quantity and the horizontal error checking quantity and making a decision, and if the vertical error checking quantity and the horizontal error checking quantity are less than those in the third step and the fourth step, receiving H0Otherwise, reject H0；
(4) When rejecting H0The synthetic vision system sends out warning information to the pilot, and when receiving H0When it is, then it means synthesisThe vision system operates normally.
2. The multi-path terrain integrity detection method based on downward-looking sensors as claimed in claim 1, wherein the step three (2) is specifically as follows:
1) initializing a prediction valueSum error variance According to the assumption that the system model is 0,has a value range of ((15)2,(20)2)；
Calculating a Kalman filter gain:
wherein, KkIs the gain of the kalman filter, and,is the error variance of the previous state, HkIs a unit domain transform matrix, RkIs a measure of error variance;
2) updating the estimated value of the sampling value:
wherein,is tkAn estimate of the time of day is determined,is the last state estimate, zkIs at tkA measured value of time of day;
3) calculating error variance of estimated value
Wherein, PkIs the error variance of the estimated value;
4) calculating a predicted value
Wherein,is tk+1Predicted value of time, phikIn the form of a unit state transition matrix,is tk+1Variance of prediction error of time, QkIs the system noise variance, called the tuning parameter of the filter;
5) and returning to the step 2) until finishing.
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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 |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101539417A (en) * | 2009-04-23 | 2009-09-23 | 中国农业大学 | On-board 3D terrain automatic measuring system and method |
| CN103268632A (en) * | 2013-01-07 | 2013-08-28 | 河海大学 | Method for generating terrain information by scanning through airborne laser radar |
| CN103339525A (en) * | 2010-12-21 | 2013-10-02 | 塔莱斯公司 | Method and device for monitoring variations in terrain |
| CN105093925A (en) * | 2015-07-15 | 2015-11-25 | 山东理工大学 | Measured-landform-feature-based real-time adaptive adjusting method and apparatus for airborne laser radar parameters |
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| Publication number | Priority date | Publication date | Assignee | Title |
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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 |
| CN103268632A (en) * | 2013-01-07 | 2013-08-28 | 河海大学 | Method for generating terrain information by scanning through airborne laser radar |
| CN105093925A (en) * | 2015-07-15 | 2015-11-25 | 山东理工大学 | Measured-landform-feature-based real-time adaptive adjusting method and apparatus for airborne laser radar parameters |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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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