CN111257593A - Atmospheric data estimation and state monitoring method fusing navigation data - Google Patents

Atmospheric data estimation and state monitoring method fusing navigation data Download PDF

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CN111257593A
CN111257593A CN202010090161.XA CN202010090161A CN111257593A CN 111257593 A CN111257593 A CN 111257593A CN 202010090161 A CN202010090161 A CN 202010090161A CN 111257593 A CN111257593 A CN 111257593A
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atmospheric data
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李荣冰
邱望彦
刘建业
鄢俊胜
朱祺
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Nanjing University of Aeronautics and Astronautics
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    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
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Abstract

The invention discloses an atmospheric data estimation and state monitoring method fusing navigation data, which comprises the following steps: collecting atmospheric data and inertial navigation data, and analyzing the relation between the atmospheric data and the inertial navigation data; establishing a virtual atmospheric data system model, and calculating a fusion attack angle and a fusion sideslip angle; when the atmospheric data system works normally, the mean value of the difference between the fusion attack angle and the measurement attack angle is calculated
Figure DDA0002383420170000012
And the mean square error σ; and (3) performing different threshold judgment by adopting a variance v of a difference value between the fused attack angle and the measured attack angle within a period of time, and judging that the atmospheric data system is not abnormal when | v | < n σ. The method and the device can effectively monitor the data abnormity in time, and are beneficial to enhancing the safety and reliability of the aviation aircraft.

Description

Atmospheric data estimation and state monitoring method fusing navigation data
Technical Field
The invention belongs to the field of aviation aircraft data monitoring, and particularly relates to an atmospheric data estimation and state monitoring method.
Background
The angle of attack, the angle of sideslip, and the vacuum speed are very important atmospheric parameters, and therefore other atmospheric information can be obtained. The atmospheric parameters represent the stress and heating conditions of the aircraft, are instruction information of a flight control system of the aerospace aircraft, and the measurement precision and reliability of the atmospheric parameters are directly related to the normal work and performance exertion of systems such as aircraft control and the like.
With the rapid development of the aviation industry, the security and reliability of data systems applied to aviation become more and more important. In order to ensure the flight safety of an aviation aircraft and the accurate measurement of an attack angle and a sideslip angle, an anomaly monitoring system needs to be configured for the attack angle and the sideslip angle in the aircraft.
Aviation aircraft are sometimes required to make extensive high-speed maneuvers or fly under severe conditions, and thus there is a possibility of failure of the air data system. For safety and reliability reasons, an aircraft must have atmospheric parameter anomaly monitoring functionality. In an aircraft, data abnormality is generally monitored by means of hardware redundancy, sensor redundancy, voting modules and the like, so that the accuracy of data information is ensured. However, considering the influence of factors such as equipment price, the anomaly monitoring of the atmospheric data needs to be realized in a set of INS/GNSS/ADS equipment. Therefore, three common anomaly monitoring modes cannot be used, so that a new method needs to be found to realize the function of monitoring the data anomaly of the general aviation aircraft.
Disclosure of Invention
In order to solve the technical problems mentioned in the background art, the invention provides an atmospheric data estimation and state monitoring method fusing navigation data.
In order to achieve the technical purpose, the technical scheme of the invention is as follows:
an atmospheric data estimation and state monitoring method fusing navigation data comprises the following steps:
(1) collecting atmospheric data and inertial navigation data, and analyzing the relation between the atmospheric data and the inertial navigation data;
(2) establishing a virtual atmospheric data system model, and calculating a fusion attack angle and a fusion sideslip angle;
(3) when the atmospheric data system works normally, the fusion attack angle and measurement are calculatedMean of difference between angles of attack
Figure BDA00023834201500000213
And the mean square error σ; and (3) performing different threshold judgment by adopting a variance v of a difference value between the fused attack angle and the measured attack angle within a period of time delta T, judging that the atmospheric data system is not abnormal when | v | < n σ, and otherwise, judging that the atmospheric data system is abnormal, wherein n is a set coefficient.
Further, in step (1), the relationship between the atmospheric data and the inertial navigation data is as follows:
Figure BDA0002383420150000021
Figure BDA0002383420150000022
Figure BDA0002383420150000023
Figure BDA0002383420150000024
Figure BDA0002383420150000025
in the above formula, M is the flying Mach number of the aircraft; t issIs the Kelvin temperature; vTIs the speed of the aircraft relative to air, i.e. the vacuum speed;
Figure BDA0002383420150000026
the speed of the air under the machine body system relative to the geographical system, namely the wind speed under the machine body system;
Figure BDA0002383420150000027
a posture transfer matrix for the navigation system to the body system;
Figure BDA0002383420150000028
the speed of the aircraft under the engine system relative to the geographic system, namely the ground speed of the engine system;
Figure BDA0002383420150000029
the machine body is under vacuum speed;
Figure BDA00023834201500000210
the vacuum velocity is the component of the machine system along the transverse axis of the machine body to the right,
Figure BDA00023834201500000211
the component of the vacuum speed of the machine system along the longitudinal axis of the machine body is forward,
Figure BDA00023834201500000212
the component of the vacuum speed along the vertical axis of the machine body under the machine system, α is a fusion attack angle, and β is a fusion sideslip angle.
Further, in step (2), based on the established virtual atmospheric data system model, considering that the aircraft is affected by the lever arm effect when making angular motion, the velocities above the nose, the right wing and the fuselage are different from the velocity of the aircraft centroid point, and the calculation formula of the fusion attack angle α and the fusion sideslip angle β is obtained:
Figure BDA0002383420150000031
Figure BDA0002383420150000032
in the above formula, the first and second carbon atoms are,
Figure BDA0002383420150000033
linear velocity of three axes of mass center under the aircraft system, p, q, r are angular velocities of three axes under the aircraft system, xs,ys,zsThe lever arm length of the lower three shafts of the aircraft system.
Further:
Figure BDA0002383420150000034
in the above formula, theta, gamma, psi are attitude angles,
Figure BDA0002383420150000035
is the first differential of theta, gamma and psi, i.e. the attitude angular velocity.
Further, in the step (3), selecting a plurality of time periods of aircraft flight, making a difference between the fusion attack angle and the measurement attack angle, and counting data to obtain a mean value and mean square error statistics; different abnormal threshold values are adopted in different time periods, and the maximum value and the minimum value in the difference values of the fusion attack angle and the measurement attack angle are respectively set as xmaxAnd xminLet ε equal max { | xmax|,|xminI.e. the coefficient
Figure BDA0002383420150000036
Wherein
Figure BDA0002383420150000037
Indicating a ceiling operation.
Further, in step (3), Δ T is 2 s.
Adopt the beneficial effect that above-mentioned technical scheme brought:
the virtual atmospheric data system fusing navigation data is adopted to estimate the atmospheric data and monitor the state of the atmospheric data, so that the data abnormality can be timely and effectively monitored, and the safety and the reliability of the aviation aircraft can be enhanced.
Drawings
FIG. 1 is a block diagram of a virtual atmosphere data system of the present invention;
FIG. 2 is a diagram of an anomaly monitoring algorithm of the present invention.
Detailed Description
The technical scheme of the invention is explained in detail in the following with the accompanying drawings.
The invention designs an atmospheric data estimation and state monitoring method fusing navigation data, which comprises the following steps:
step 1: collecting atmospheric data and inertial navigation data, and analyzing the relation between the atmospheric data and the inertial navigation data;
step 2: establishing a virtual atmospheric data system model, and calculating a fusion attack angle and a fusion sideslip angle;
and step 3: when the atmospheric data system works normally, the mean value of the difference between the fusion attack angle and the measurement attack angle is calculated
Figure BDA0002383420150000049
And the mean square error σ; and (3) performing different threshold judgment by adopting a variance v of a difference value between the fused attack angle and the measured attack angle within a period of time delta T, judging that the atmospheric data system is not abnormal when | v | < n σ, and otherwise, judging that the atmospheric data system is abnormal, wherein n is a set coefficient.
In this embodiment, in step 1, the acquired atmospheric data includes an attack angle, a sideslip angle, a mach number, a vacuum speed, and the like, and the acquired inertial navigation data includes an attitude angle, an attitude angle rate, a northeast direction speed, and the like.
The relationship between atmospheric data and inertial navigation data is as follows:
Figure BDA0002383420150000041
Figure BDA0002383420150000042
Figure BDA0002383420150000043
Figure BDA0002383420150000044
Figure BDA0002383420150000045
in the above formula, M is the flying Mach number of the aircraft; t issIs the Kelvin temperature; vTIs the speed of the aircraft relative to air, i.e. the vacuum speed;
Figure BDA0002383420150000046
the speed of the air under the machine body system relative to the geographical system, namely the wind speed under the machine body system;
Figure BDA0002383420150000047
a posture transfer matrix for the navigation system to the body system;
Figure BDA0002383420150000048
the speed of the aircraft under the engine system relative to the geographic system, namely the ground speed of the engine system;
Figure BDA0002383420150000051
the machine body is under vacuum speed;
Figure BDA0002383420150000052
the vacuum velocity is the component of the machine system along the transverse axis of the machine body to the right,
Figure BDA0002383420150000053
the component of the vacuum speed of the machine system along the longitudinal axis of the machine body is forward,
Figure BDA0002383420150000054
the component of the vacuum speed along the vertical axis of the machine body under the machine system, α is a fusion attack angle, and β is a fusion sideslip angle.
In this embodiment, in step 2, the virtual atmosphere data system model is established as shown in fig. 1. As shown in FIG. 2, the wind speed is calculated from the vacuum speed and the ground speed at the previous time, and the fused vacuum speed at the current time is obtained from the ground speed at the current time and the wind speed at the previous time according to the principle that the wind speed is not changed for a short time
Figure BDA0002383420150000055
Further obtain a fused angle of attack
Figure BDA0002383420150000056
And blended sideslip angle
Figure BDA0002383420150000057
When the airplane does angular motion, due to the influence of the lever arm effect, the speed above the nose, the right wing and the airplane body is different from the speed of the center of mass point of the airplane, so that the influence of the lever arm effect needs to be eliminated by the following formula:
Figure BDA0002383420150000058
in the above formula, the first and second carbon atoms are,
Figure BDA0002383420150000059
linear velocity of centroid (x, y, z) axis under aircraft system, angular velocity of (x, y, z) axis under aircraft system, xs,ys,zsIs the lever arm length of the lower (x, y, z) axis of the aircraft architecture.
The output of the inertial navigation system is the attitude angular velocity under the geographic system
Figure BDA00023834201500000510
The attitude angular velocity under the geographic system needs to be converted into the angular velocity under the mechanical system (p, q, r) by the following formula.
Figure BDA00023834201500000511
On the basis of the above equation, considering the influence of the lever arm effect, the following equation is obtained:
Figure BDA00023834201500000512
Figure BDA00023834201500000513
through the formula, the model of the virtual atmospheric data system is established, and a more accurate fusion attack angle and a fusion sideslip angle can be obtained.
In this embodiment, in step 3, considering that a false alarm and a false alarm may be generated by using a difference at a certain time as a threshold value for determining, and affecting the accuracy of the atmospheric data anomaly monitoring method, the variance of the difference over a period of time is used for determining the anomaly threshold value. Since the system needs to monitor the fault within 2s after the fault occurs, the variance of the difference value within 2s is adopted for threshold judgment.
Selecting a plurality of time periods of aircraft flight, subtracting the fusion attack angle and the measurement attack angle, and carrying out statistics on data to obtain a mean value and mean square error statistics; different abnormal threshold values are adopted in different time periods, and the maximum value and the minimum value in the difference values of the fusion attack angle and the measurement attack angle are respectively set as xmaxAnd xminLet ε equal max { | xmax|,|xminI.e. the coefficient
Figure BDA0002383420150000061
Wherein
Figure BDA0002383420150000062
Indicating a ceiling operation.
The embodiments are only for illustrating the technical idea of the present invention, and the technical idea of the present invention is not limited thereto, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the scope of the present invention.

Claims (6)

1. An atmospheric data estimation and state monitoring method fusing navigation data is characterized by comprising the following steps:
(1) collecting atmospheric data and inertial navigation data, and analyzing the relation between the atmospheric data and the inertial navigation data;
(2) establishing a virtual atmospheric data system model, and calculating a fusion attack angle and a fusion sideslip angle;
(3) when the atmospheric data system works normally, the mean value of the difference between the fusion attack angle and the measurement attack angle is calculated
Figure FDA00023834201400000113
And the mean square error σ; different threshold judgment is carried out by adopting variance v of the difference value between the fused attack angle and the measured attack angle within a period of time delta T, and when | v | < n σ, atmospheric data is judgedAnd (4) the system is not abnormal, otherwise, the atmospheric data system is abnormal, wherein n is a set coefficient.
2. The method for estimating atmospheric data and monitoring state of fused navigation data according to claim 1, wherein in step (1), the relationship between the atmospheric data and the inertial navigation data is as follows:
Figure FDA0002383420140000011
Figure FDA0002383420140000012
Figure FDA0002383420140000013
Figure FDA0002383420140000014
Figure FDA0002383420140000015
in the above formula, M is the flying Mach number of the aircraft; t issIs the Kelvin temperature; vTIs the speed of the aircraft relative to air, i.e. the vacuum speed;
Figure FDA0002383420140000016
the speed of the air under the machine body system relative to the geographical system, namely the wind speed under the machine body system;
Figure FDA0002383420140000017
a posture transfer matrix for the navigation system to the body system;
Figure FDA0002383420140000018
for the speed of the aircraft relative to the geographical system under the system, i.e. the systemTying down the ground speed;
Figure FDA0002383420140000019
the machine body is under vacuum speed;
Figure FDA00023834201400000110
the vacuum velocity is the component of the machine system along the transverse axis of the machine body to the right,
Figure FDA00023834201400000111
the component of the vacuum speed of the machine system along the longitudinal axis of the machine body is forward,
Figure FDA00023834201400000112
the component of the vacuum speed along the vertical axis of the machine body under the machine system, α is a fusion attack angle, and β is a fusion sideslip angle.
3. The method for estimating atmospheric data and monitoring state according to the fused navigation data of claim 2, wherein in the step (2), based on the established virtual atmospheric data system model, the calculation formula of the fused attack angle α and the fused sideslip angle β is obtained by considering that the speed of the aircraft above the nose, the right wing and the fuselage is different from the speed of the aircraft center of mass point when the aircraft is subjected to the lever arm effect during the angular motion:
Figure FDA0002383420140000021
Figure FDA0002383420140000022
in the above formula, the first and second carbon atoms are,
Figure FDA0002383420140000023
linear velocity of three axes of mass center under the aircraft system, p, q, r are angular velocities of three axes under the aircraft system, xs,ys,zsThe lever arm length of the lower three shafts of the aircraft system.
4. The method for atmospheric data estimation and condition monitoring with fused navigation data according to claim 3, wherein:
Figure FDA0002383420140000024
in the above formula, theta, gamma and psi are attitude angles,
Figure FDA0002383420140000025
is the first differential of theta, gamma and psi, i.e. the attitude angular velocity.
5. The method for estimating atmospheric data and monitoring state of fusion navigation data according to claim 1, wherein in the step (3), a plurality of time periods of aircraft flight are selected, the fusion angle of attack and the measured angle of attack are differentiated, and data are counted to obtain a mean value and a mean square error statistic; different abnormal threshold values are adopted in different time periods, and the maximum value and the minimum value in the difference values of the fusion attack angle and the measurement attack angle are respectively set as xmaxAnd xminLet ε equal max { | xmax|,|xminI.e. the coefficient
Figure FDA0002383420140000026
Wherein
Figure FDA0002383420140000027
Indicating a ceiling operation.
6. The method for estimating atmospheric data and monitoring the state of the merged navigation data according to claim 1, wherein Δ T is 2s in the step (3).
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