Note: Descriptions are shown in the official language in which they were submitted.
CA 02605709 2007-11-02
REDUNDANT SYSTEM FOR THE INDICATION OF HEADING AND ATTITUDE
IN AN AIRCRAFT
This is a divisional application of Canadian Patent Application Serial No.
2,358,557 filed
on January 12, 2000.
TECHNICAL FIELD
The invention relates to a system function which provides display of heading
and attitude
on displays in an aircraft, for example a head-up display (HUD), in the event
of failures
in certain equipment for normal attitude display. The system function, which
in English
is called Attitude and Heading Reference System and is abbreviated AHRS with
reference to its initials, supplements the aircraft's normal display for
heading and attitude.
This display is intended to help the pilot to recover from difficult attitudes
and then
facilitate return to base/landing. It should be understood that the expression
"the
invention" and the like encompasses the subject matter of both the parent and
the
divisional applications.
PRIOR ART
In order not to lose attitude and heading display in an aircraft in the event
of failure of a
normally-used inertial navigation system (INS) a redundant system is required.
In good
visibility a pilot can fly by using the horizon as an attitude reference, but
with great
uncertainty as to the heading. In bad weather, in cloud and at night when the
horizon is
not visible, the pilot can easily become disoriented and thereby place the
aircraft and
him/herself in hazardous situations.
AHRS systems calculate, independently of normal systems, attitude angles
(pitch and
roll) and heading. Such a system continuously displays the position to the
pilot on a
display in the cockpit. The need for a redundant system for attitude may be so
great that
an aircraft is not permitted to fly without one.
Redundant systems in the form of an AHRS unit are available today. Such a unit
contains among other things gyros which measure aircraft angle changes in
pitch, roll and
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CA 02605709 2007-11-02
yaw. It also contains accelerometers and magnetic sensor. The accelerometers
are used
to establish a horizontal plane. The magnetic sensors are used to obtain a
magnetic north
end. This type of AHRS system in the form of hardware is costly and involves
the
installation of heavy, bulky equipment on the aircraft. To overcome this there
is
proposed in this description a synthetic
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CA 02605709 2007-11-02
AHRS which uses sensors existing in the aircraft, which are not normally
intended for AHRS
calculation and which therefore partly have significantly lower performance,
instead of
sensors of the type included in an AHRS unit.
The angles are calculated with the aid of existing sensors in the aircraft.
The aim is to use
existing angular rate gyro signals and support these with calculations based
on other available
primary data in the aircraft. Angular rate gyros are normally used in control
systems and
generally have substantially greater drift than gyros for navigation.
DESCRIPTION OF THE IlWENTION
According to one aspect of the invention, a method is provided for
synthetically calculating
redundant attitude and redundant heading by means of data existing in an
aircraft.
More specifically, the present invention provides a method for synthetically
calculating
redundant attitude for an aircraft when the heading of the aircraft is known,
with the aid
of data existing in the aircraft, such as the angular rates p, q, r around the
x-, y- and z-
coordinates of an aircraft-fixed (body frame) coordinate system, air data
information in
the form of speed, altitude and angle of attack as well as heading
information,
characterised in that the method includes the steps:
- attitude is calculated on the basis of the aircraft-fixed angular rates p,
q, r and
- the calculated attitude is corrected by means of air data and heading.
The present invention also provides a method for synthetically calculating
redundant
attitude and redundant heading for an aircraft with the aid of data existing
in the aircraft,
such as the angular rates p, q, r around the x-, y-, and z- coordinates of an
aircraft-fixed
(body frame) coordinate system, air data information in the form of speed,
altitude and
angle of attack, characterised in that the method includes the steps:
- attitude and heading are calculated on the basis of the body-frame angular
rates p, q, r
- the errors in the measured body-frame magnetic field vector components are
estimated,
- the measured body-frame field magnetic field vector is derived,
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- errors in calculated attitude and heading are estimated with the aid of air
data and
derived measured body-frame magnetic field vector components and
- the calculated attitude and heading are corrected by means of estimated
errors in
attitude and heading.
The present invention also provides an arrangement for synthetically
calculating
redundant attitude for an aircraft when the aircraft's heading is known, with
the aid of
data existing in the aircraft such as the aircraft's body-frame angular rates
(p, q and r), air
data including at least speed, altitude and angle of attack as well as heading
information,
characterised in that the arrangement includes an integration routine to
integrate out
the aircraft's attitude from information about the aircraft's body-frame
angular rates (p, q
and r) as well as that the calculated attitude is corrected by means of
reference attitude
from air data and redundant heading.
The present invention also provides an arrangement for synthetically
calculating
redundant attitude and redundant heading for an aircraft with the aid of data
existing in
the aircraft such as measured body-frame field vector components, the
aircraft's body-
frame angular rates (p, q and r) as well as air data including at least speed,
altitude and
angle of attack, characterised in that the arrangement includes a first
measurement
routine which transforms the measured body-frame magnetic field vector
components to the
aircraft's navigation system (navigation frame), a first filter which
estimates the errors in
the calculated measured body-frame field vector components, an integration
routine for
integrating out the aircraft's attitude and heading from information about the
aircraft's
body-frame angular rates (p, q and r), a second filter for estimating the
errors arising in
attitude and heading obtained in the said integration and a second measurement
routine for
calculating attitude and heading from air data and derived measured body-frame
magnetic
field vector components.
Different forms of embodiment have been developed. In one embodiment the
heading of the
aircraft is available and in another embodiment the heading is calculated on
the basis of a
magnetic heading sensor. When the heading is available the calculations can be
substantially
reduced.
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When the heading is available (redundant heading) attitude is calculated by
weighting together
the signals from the angular rate gyros in the flight control system of the
aircraft, information
from air data (altitude, speed, angle of attack) and information about heading
(redundant
heading).
When the heading is not available, attitude and heading are calculated
according to one
embodiment with the aid of l(alman filters by weighting together the signals
from the angular
rate gyros in the aircraft's control system, information from air data
(altitude, speed, angle of
attack and sideslip angle) as well as information from an existing magnetic
heading detector in
the aircraft.
One advantage of a synthetic AHRS according to the aspect of the invention is
that it works
out substantially cheaper than conventional AHRS system based on their own
sensors if
existing sensors in the aircraft can be used. This also saves space and weight
in the aircraft.
DESCRIPTION OF FIGURES
Figure 1 shows a schematic diagram of an AHRS function in which the heading is
available.
Figure 2 shows the principle for levelling of the attitude of the aircraft in
a head-up display, to
the left without levelling and to the right with levelling.
Figure 3 shows the block diagram of a redundant system for both attitude and
heading.
Figure 4 shows in three pictures the attitude and heading of the aircraft and
the axes in the
body frame coordinate system, as well as the angle of attack and the sideslip
angle.
Figure 5 shows how zero errors and scale factor errors impact the measured
value.
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DESCRIPTION OF EMBODIMENT
A number of embodiments are described below with the support of the figures.
According to
the invention, methods are provided for synthetically calculating attitude and
heading by
means of data existing in the aircraft.
In a simpler embodiment, the heading of the aircraft is available. The heading
information may be obtained from a heading gyro. Attitude may be integrated
out via
information about the body-frame angular rates (p, q and r) obtained from the
aircraft-
fixed angular rate gyros of the aircraft. Correction of the integrated-out
attitude can take
place with the aid of attitude calculated on the basis of air data information
and heading
information. In the arrangement of this embodiment, the heading information
can be
obtained from a heading gyro. The integration routine (8) can integrate out
the aircraft's
attitude from the aircraft's body-frame angular rates (p, q and r) obtained
from the
aircraft's body-frame angular rate gyros. The integration routine (8) can be
fed with the
zero-error-compensated body-frame angular rate gyro signals. A reference
attitude can
be calculated with air data information as well as redundant heading
information. A
synthetically-generated corrected attitude can be obtained by generating a
difference
between the attitude obtained from the integration routine (8) and an error
signal that
represents the error between the integrated attitude and the reference
attitude.
In another embodiment the heading is calculated, in this case on the basis of
a magnetic
heading sensor. Attitude and heading can be integrated out via information
about the
aircraft's body-frame angular rates (p, q and r) obtained from the aircraft's
body-frame
angular rate gyros. Estimation of errors in measured body-frame magnetic field
vector
components can be performed in a first filter (11). In a second filter (22)
can be
performed estimation of attitude errors and heading errors that arise on
integration of the
aircraft's body-frame angular rates (p, q and r) obtained from the aircraft's
body-frame
angular rate gyros, where the estimation can be done with the aid of attitude
calculated
from air data information as well as derived measured body-frame magnetic
field vector
components. The filtering can take place with the aid of Kalman filters. In
the
arrangement of this embodiment, the first measurement routine (10) can be fed
with the
measured body-frame magnetic field vector components, as well as attitude and
heading
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CA 02605709 2007-11-02
from the aircraft's normal navigation system and transforms the measured body-
frame
magnetic field vector components to the aircraft's navigation frame. The first
filter (11)
can be fed with information from the first measurement routine (10) and can
estimate the
errors in the measured body-frame magnetic field vector components. The
integration
routine (20) can integrate out the aircraft's attitude and heading from the
aircraft's body-
frame angular rates (p, q and r) obtained from the aircraft's body-frame
angular rate
gyros. The second measurement routine (21) can be fed with air data, the
derived
measured body-frame magnetic field vector components and with information
about the
aircraft's body-frame angular rates (p, q and r) and from these values can
calculate an
attitude and a heading. The second filter (22) can be fed with information
from the
second measurement routine (21) and can estimate the errors in attitude and
heading as
well as zero error in body-frame angular rate gyro signals and residual errors
in the
measured body-frame magnetic field vector components for generating an error
signal.
A synthetically-generated corrected attitude and heading can be obtained by
generating a
difference between
- the attitude obtained from the integration routine (20) and heading and
- the error signal from the second filter (22). The integration routine (20)
can be fed with
body-frame angular rate gyro signals compensated for estimated zero errors.
The first
filter (11) and/or the second filter (22) can consist of a Kalman filter.
Calculation of AHRS when the heading is known
The signals from the three angular rate gyros 2 rigidly mounted on the body
frame are used to
determine the orientation of the aircraft relative to the reference coordinate
system N
(navigation frame). The angular rate gyros 2 measure angular velocities around
the three body-
frame coordinate axes (x, y, z). The angular velocities are normally
designated wX or p
(rotation around the x-axis), cny or q (rotation around the y-axis) and taz or
r (rotation around
the z-axis). The orientation between the body-frame coordinate system B (body)
and the N
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system is given by the euler angles 0, 0 and V. However, since the heading is
known, only 0
and 0 are of interest. With the assumption that the N system is an inertial
system and is
oriented so that its z-axis is parallel to the g vector of the earth, it can
be shown that
6 - a) cos4 -coZsin
(1)
o + tan 0 (coy sin 0 + tnz cos
If the gyros 2 were ideal, the initial values 00 and 00 were error-free and if
the integration
method used were accurate, attitude angles can be obtained by solving Eqn (1).
In practice,
however, none of these preconditions is satisfied; instead, sensor errors etc
cause the solution
to diverge and relatively soon to become unusable.
Sensor errors in the form of among others zero errors, scale factor errors,
misaligned mounting
and acceleration-induced drifts constitute the dominant sources of error. In
level flight the zero
error is the error source that dominates error growth.
Owing to sensor imperfections and uncertainty in initial values, equation (1)
gives an estimate
of roll and pitch angle derivatives according to
- g - coycos $ - 0), sin $
(2)
wx+tan 6(coy sin +cozcos$)
The difference between the expected (pAHRS (calculated by the AHRS function)
and the
"actual" (plef (from air data, primary data calculated) attitude angles
constitutes an estimate of
the attitude error
A(p = (PAHRS - ref (3)
See below concerning the use of i p.
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Finally the attitude angles are given as
?AHRS = J(cp)dt+ yo-lim(dtp) (4)
r
where yo constitutes estimated initial values.
Calculation of (pref
The formula Oref = arcsin (h/vt) + (a * cos 4)) is used when calculating Oreg.
h is a high-pass-
filtered altitude signal. vt is true airspeed.
The formula 4)ref = arctan (vt * (yr)/g) is,used when calculating inf.
iy is a high-pass-filtered heading (redundant heading) signal.
Zero correction of the angular rate gyros
The zero errors in the angular rate gyros 2 are heavily temperature-dependent.
It may take 20
to 30 minutes for the gyros to reach operating temperature. This means that an
ITS failure
shortly after take-off might give large zero errors if flying continued.
However, it takes a
certain time from gyros 2 receiving voltage to the aircraft taking off, which
means that part of
the temperature stabilisation has been completed when a flight begins. It is
also assumed that
landing can take place within a short time in the event of an INS failure
during takeoff. To
minimise zero errors from the angular rate gyros 2 a zero correction of the
angular rate gyros
is performed by software. This involves comparing the oo (p, q and r) signals
from the angular
rate gyros 2 with the corresponding signal from the INS, see eqn (5), by
generating a
difference in 4a. The difference is low-pass-filtered in a filter 5 and added
to the angular rate
gyro signals in a difference generator 4b, where the signal Wk which
designates the zero-error-
corrected gyro signals and is used instead of in the AHRS calculations. This
is done
continuously as long as the INS is working. In the event of an INS failure the
most recently
performed zero corrections are used for the rest of the flight.
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PTNS $TNS - V,-,,s sin 07WS
0TNS - gTNS OTNSCOS0TNS+JTNSCOSBTNSSin4TNS (5)
rTNS -STNSSIn4TNS+ ITNSCOSQTNSCOS~TNS
A block diagram of the realisation of the AHRS function with zero correction
of the angular
rate gyros is shown in Figure 1. The figure gives a schematic illustration of
the AHRS
function. The zero correction of the angular rate gyros is performed by the
units inside the
dashed area D.
VTNS, BTNS and STNS are high-pass-filtered to obtain NITNS, STNS and $TNS =
These are used
in Eqn (5), which gives'TNS (pTNS, gTNS, r NS) in a first block 1. co (p, q,
r) which are
obtained as signals from the gyros designated by 2 are low-pass-filtered in a
low-pass filter 3,
before the difference is generated in 4a.
The difference signal between the coTNS ( PINS, gTNS, rTS) signals and the co
(p, q, r) signals
is low-pass-filtered with a long time-constant in a low-pass filter 5, ie its
mean value is
generated over a long time. The filter 5 is initialised at take-off rotation
with the shorter time-
constant. After a power failure, the filter 5 is initialised instantaneously.
In block 7, cp is calculated, after which the integration according to
Equation (4) is performed
in an integrator 8, to which the initial conditions (po are added. In a
difference generator 9a
the signal Acp is added, but is disconnected by means of a switch 9b under
certain changeover
conditions, as for example when hi > yLIM and 1~1 > . The &p signal passes
through a
limiter 9c. The magnitude of the output signal from the limiter 9c is
dependent on the
magnitude of the ,&(-p signal (ie the input signal to limiter 9c). The Acp
signal is generated
according to Equation (3) in a difference generator 9d to which are added
calculated (pAHRs
attitude angles and "actual" cpr f attitude angles from sensors (primary data)
designated with
9e.
Despite compensations, the calculated angles from the AHRS contain minor zero
errors. Since
the output signals are used for head-up display, this is corrected by using
04) in roll and D0 in
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pitch to level the SI image until a stable position is obtained. See Figure 2,
where the line H
symbolises the actual horizon and where an aircraft is represented by P. Note
that this levelling
of the HUD only takes place when one is within the limits described above.
AHRS calculation when the heading is also to be calculated
Figure 3 shows schematically the modules that form building blocks for another
variant of a
synthetic AHRS and how these modules are linked together to create a redundant
attitude and
a redundant heading.
Figure 3 shows the principle of the redundant system in accordance with the
aspect of the
invention. The system consists of two subsystems A and B; the first subsystem
A performs
estimation of any errors in the measured geomagnetic field and the other
subsystem B
performs calculation of redundant attitude and heading. In all, this results
in five building
blocks, where a first measurement routine 10 and a first Kalman filter 11
constitute the
building blocks in the first subsystem A and further where the integration
routine (1/s) 20,
measurement routine 21 and a second Kalman filter 22 constitute the building
blocks in the
second subsystem B.
With measurement routine 10, measured field vector components in the body
frame coordinate
system are transformed, to a north-, east- and vertically-oriented coordinate
system called the
navigation frame. The transformation takes place with the aid of attitude and
heading from the
inertial navigation system of the aircraft, INS, via wire 12. The field vector
components of the
geomagnetic field are taken from a magnetic heading sensor in the aircraft and
arrive via wire
13. In the first Kalman filter 11, the errors in the field vector components
are then estimated on
the basis of knowledge about the nominal nature of the components, after which
the estimated
values are stored in a memory 14.
Subsystem A (measurement routine 10 and Kalman filter 11) are used only when
the INS is
working correctly. In the event of INS failure, the latest possible estimate
of the errors in the
field vector components is used, ie that which has been stored in memory 14.
Since it may be
difficult in many cases to decide whether the INS is working as it should, the
absolutely last
estimate should not be used. In order to solve this, the estimates of errors
in the measured
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geomagnetic field that are used are at least one flight old. ie the estimates
that are stored in the
memory from the previous flight or earlier.
The. integration routine 20 receives information about angular velocities, in
this case for the
three coordinate axes x, y and z in the body frame. These are normally
designated cos or p
(rotation around the x-axis), coy or q (rotation around the y-axis) and coi or
r (rotation around
the z-axis). The information is taken from the angular rate gyros of the
control system and is
fed via wire 15 to routine 20 which integrates out attitude and heading via a
transformation
matrix.
The second measurement routine 21 consists of a developed variant of the first
measurement
routine 11 and uses the field vector components derived from the first
measurement routine
11. In addition, a roll and pitch angle are calculated with the aid of data
from existing air data
and existing slip sensors, data which arrives to measurement routine 21 via
wire 16 to
measurement routine 21. By means of the second Kalman filter 22 the attitude
and heading
errors that arise on integration of the angular rate gyro signals of the
control system are
primarily calculated. Secondarily, Kalman filter 22 is used to estimate the
biases in the angular
rate gyros, ie the biases in p, q, and r.
The first measurement routine 10
The geomagnetic field can be calculated theoretically all over the world. To
do this, the IGRF
(International Geomagnetic Reference Field) is used, for example.
The field vector in the body frame is designated here with BB and the field
vector in the
navigation frame with BN. Further, the three components of the field vector
are designated in
accordance with
B = [B, By, Bz]T (6)
With the aid of the transformation matrix C, which transforms a vector from
body frame to
navigation frame, we have
BN = C. = BB , (7)
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where C has the appearance
' C1i C12 C13
cN = C21 C22 C23 (8)
C31 C32 C33
The transformation matrix C. is calculated with the aid of attitude and
heading, 0, from
the INS.
The difference between a measured field vector and a field vector calculated
in accordance
with the model will be ~r
BN, measured - BN, calculated = C C.
S$B
where S designates the difference between the measured and the calculated
quantity.
The left-hand part of Eqn (9) becomes the output signal from the first
measurement routine 10
and thus the input signal to Kalman filter 11. Further, the right-hand part of
Eqn (9) is used in
Kalman filter 11, which is evident from the description of the first Kalman
filter 11 below.
The first Kalman filter 11
Given the state model
Xk+1 = Ftxk+wk
(10)
Zk = Hkxk + ek,
a Kalman filter works in accordance with:
Time updating
Xk+ 1 = FkXk (11)
Pk+ I = FkPkFF + Qk,
where Pkc+ 1 is the estimated uncertainty of the states after time updating.
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Measurement updating
T T
Kk+1 = Pk+1Hk+1[Hk+lPk+lHk+1+Rk+ll
+
Xk+1 = Xk+1+Kk+l1Zk+i-Hk+LXk+1J (12)
Pk+1 = Pk+1-Kk+1Hk+1Pk+1'
where Pt+ 1 is the estimated uncertainty of the states after measurement
updating-
The errors in the field vector components are modelled according to
5Bx bz sr kxy kxz Bx
5By = by + kyx sy kyz - By , (13)
SBz bz kzx kzy sz Bz
where b are biases, s are scale factor errors and k is a cross-coupling from
one component to
another (for example, index xy refers to how the y-component affects the x-
component). These
12 errors can represent the states in the first Kalman filter 11 according to
T
Xk = [bx by bz sz sy sz kxy kxz kyz kyx ku kzy] (14)
and each of the state equations looks like this
xk+1 = xk+wk , (15)
where the index k designates the time-discrete count-up in time.
In Eqn (15), wk is a weakly time-discrete process noise to model a certain
drift in the errors.
Eqn (15) means that the prediction matrix becomes the unit matrix and the
covariance matrix
for the process noise will be the unit matrix multiplied by aw, where aw is
typically set to
one hundred-thousandth (dimensionless since the field vector components are
normalised to
the amount 1 before they are used).
Where measurement updating of Kalman filter 11 is concerned, Eqn (9) is used
and the
measurement matrix looks like this
C11 C12 C13 C11Bx C12By C13Bz C11By C11Bz C12Bz c12Bx C13Bx c13By
Hk = C21 c22 c23 c21Bx c22By c23Bz c21By c21Bz c22Bz c22Bx c23Bx c23By (16)
C31 C32 C33 C31Bx C32By C33Bz C31By C31Bz C32Bz C32Bx C33Bx C33By
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Owing to unmodelled interference, the measured geomagnetic field vector will
deviate from
the model, both in direction and in amount. The simplest variant is to model
this interference
as a constant white measurement noise with the aid of the measurement noise
covariance
matrix Rk. The standard deviations for the measurement noise for the three
field vector
component measurements are each typically set to one-tenth (dimensionless
because the field
vector components are normalised to I before they are used).
A Chi2 test is used to avoid the impact of bad measurements. In addition, the
measurements of
the field vector components are not used if the angular velocities are too
high. The reason for
this is that various time delays exert an effect at high angular velocities.
Integration routine 20
It can be shown that the time-derivative of the transformation matrix e.
becomes
CB = CB C. Wla - WIN = CB . (17)
In Eqn (17) Wm and WIN are, respectively, B's (body frame) rotation relative
to I (inertial
frame) and N's (navigation frame) rotation relative to I. Both are written in
matrix form.
Since we are concerned with redundant attitude and redundant heading, where
the
requirements for attitude errors are of the order of 2 degrees, whilst the
elements in WIN are of
the order of 0.01 degrees, WIN is disregarded. The expression in (17) will
then be
CB = CB - WIB , (18)
where WIB is the angular rate gyro signals from the angular rate gyros of the
control system.
In principle Eqn (18) means that there are nine differential equations.
Because of
orthogonality, only six of these need be integrated and the other three can be
calculated with
the aid of the cross-product.
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The second measurement routine 21
The second measurement routine 21 consists of a developed variant of the first
measurement
routine 11, in which the expansion consists of calculating the roll and pitch
an ales with the aid
of data from air data (altitude and speed) and the slip sensors (angle of
attack and sideslip
angle).
In the first measurement routine 11 it is assumed that only the field vector
components are
incorrect and that attitude and heading are correct. This assumption is
reasonable because the
field vector components are resolved with the aid of attitude and heading from
the INS. In the
second measurement routine 21 this is not satisfied, and consideration must
also be given to
attitude and heading errors. The field vector used in the second measurement
routine is
compensated for errors estimated in subsystem A.
Errors in both the field vector and the transformation matrix mean that
N BN, Measured = CB ' BB, Measured (19)
-N
where CB stands for calculated transformation matrix and means that
CB = CB + SCB . (20)-
If we use (20), generate the difference between measured and calculated field
vector and
disregard error products, we get
B , Calculated 8 B ' BN, Measured + ' CB ' 8BB = (21)
In the second measurement routine 21, roll and pitch angle are calculated with
the aid of
altitude, speed, angle of attack and sideslip angle. The pitch angle can be
calculated according
to
eref = asin( )+ Cos(~)a+ sin(22)
To be able to calculate the pitch angle according to the expression in Eqn
(22) an altitude
derivative is required. This altitude derivative is not directly accessible
and must instead be
calculated on the basis of existing altitude which is obtained from air data.
The calculation is
done according to
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n h(n) T((T-fs~ ~e(n-1)+h(n)-h(n-1) (23)
ie a high-pass filtering of the altitude. The symbols '[ and fr in Eqn (23)
represent
respectively the time-constant of the filtering and the sampling frequency.
The speed v used in
Eqn (22)- is approximately vt (true speed relative to the air). By
approximately we mean that,
when calculating vt, measured temperature is not used, which is the normal
case, but a so-
called standard temperature distribution is used here instead.
Further, the roll angle can be calculated according to
ref = atan v . (24)
8
The expression in Eqn (24) applies only for small roll and pitch angles, small
angular
velocities and moreover when the angles of attack and the sideslip angles are
small.
The above two expressions are calculated and compared with the attitude that
is calculated via
the integration routine by generating the difference according to
c2 v(C33 = ()Z + C32 = (00
-ref = atan C33-atan8(C11+C21)
(25)
6 - gref = atan -0312 - (asin() + Cos(atanC32 a+ sin(atanC32)1 ),
1 - C31
where
= atanc32
C33
e - atan -C31
(26)
1 - c31
C33 = 0)Z + C32 = COy
2 2
C11+C21
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The second Kalman filter 22
The second Kalman filter 22 can be said to be the heart of the system. Here
are estimated the
attitude and heading errors that arise on integration of the angular rate gyro
signals from the
flight control system. Also estimated are the zero errors in the field vector
components of the
angular rate gyro signals. Further, possible residual errors in the field
vector components, ie
the errors that the first Kalman filter 11 cannot reach are estimated here.
All in all, this means
nine states: three for attitude and heading errors, three for the zero errors
in the angular rate
gyro signals and three for residual errors in the field vector components
(three zero errors).
Attitude and heading errors are represented by a rotation of the body-frame
system from a
calculated to a true coordinate system. The error in dB can be written
SC' = C- C C- C BI) . (27)
One can ascertain that
1 -yZ Yy
B = YZ 1 -yX = F+I , (28)
1
-Yy T.
where I is the matrix form of y = [YX, Y,, YZ]T and I is the unit matrix (T
means transponate).
The elements of the vector y describe a small rotation around the respective
axis between
actual (true) and calculated body frame system. The corresponding differential
equations for
the elements of y can be derived to
y = Sw, (29)
where Sco is the errors in the angular rates from the angular rate gyros.
The errors in the angular rates are modelled as three first-order Markov
processes according to
Scn = -z &o + uw (30)
where the time-constant T,, is set typically to a number of hours and the
three uc, to typically
less than one degree/second.
Residual errors in the field vector components are modelled (the zero errors)
in a similar way,
ie
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b ~b+ub (31)
b
where tb is set typically to a number of hours, and ub is set typically to a
few hundredths
(dimensionless because the field vector components are normalised to 1 before
they are used).
This gives a state vector according to
Xk = [y.;, Y, YZ Swx Swy S0) bX by bJ (32)
and a prediction matrix according to
r+AT
Fk = I+ J -A (,c)dc , (33),
where A('c) is the matrix that described the time-continuous state equations
as above.
The covariance matrix for the process noise Qk is set to a diagonal matrix.
Among other
things, u,, and ub described above are used as diagonal elements. As regards
the diagonal
elements linked to the states for attitude and heading errors (the first
three), the effects of the
scale factor errors in the angular rate gyros are included. These scale factor
errors are normally
of the order of 2% and can cause major errors in integrated-out attitude and
heading at high
angular rates.
The. measurements are five in number: three derived field vector components
and roll and pitch
angle calculated from air data. These measurements are obtained by using the
relations (21)
and (25).
As regards the measurement matrix Hk, relation (21) is used to fill out the
three top lines. This
results in the three top lines of the matrix having the appearance
Hk,1-3 =
C13By-C12Bz clIBz-C13Bx C12BX-c11By 0 0 0 C11 C12 C13
(34)
c23By - CZBz C21Bz - C23BX c22BX - c21By 0 0 0 c,l c22 c23
C33By - C32Bz C3I Bz - C33Bx C32Bx - C31 By 0 0 0 C31 C32 C33
For the last two lines of Hk Eqn (25) is used, by differentiating the two
right-hand parts with
respect to all states in the second Kalman filter 22. As a result, the last
two lines get the
elements (the index designates row and column in that order)
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yg(C33wy _ C32CJz)(Ci l + C21)
h411-
g2(C11 + 021)2 + v2(C33 ' CO- + c32 - Q )2
2vg(-C11C13-C21C23)(C33(z+C32Wr)-ygCOzC31(C21 +C21) C31C32
h42 2(C2 2 2 2 2
8 (Cl1 + C21) + v (C33 = C)z + C32 = o)y) C32 + C33
2 2
2vg(c11C1,+C21C22)(c33~z+C320)y)+vgo)yc3l(c1
1 +
h c21) C31C33 (35)
43 = -
2 2 2 2 2 2 2 2
(C11 + 021) + v(C33'(0z + C32 w)
g C32 + C33
2 2
VgC32(C11 + C21) 2 45 g2(cll + C21)2 + v2 2
(c33 ' COZ+ C32 = (Dy)
2 2
VgC33(C11 +C21)
ham
g2(C2 2 2 2 2
11+C21) +V (C33' U)z + C32 = COy)
and
h51 = sin(atan c2 )a- cos(atanC33)3
h52 = C33
C2 + C32 + 2 \ sin atan C33~CX + cos { atan _,) (36)
l 31 33 330)
~SIn~atan c3 a- COS(atanC33)
h53 - lc3 C2 C22 +C 23
31 3J
The remaining elements in the fourth and fifth line are zero.
The simplest choice for the covariance matrix for the measurement noise Rk is
a diagonal
matrix. The first four measurement noise elements have a standard deviation
which is set
typically to one-tenth. The fifth measurement noise element on the other hand
has a standard
deviation that is set to a function of the altitude derivative and the speed.
The function is quite
simply a scaled sum of the expression for calculating pitch angle and
according to Eqn (25)
differentiated with respect to the altitude derivative and the speed. The
function is set to
0 = IMA (37) (Irv 1
f(I, v) = 5 . MIhI + 5
and gives a measure of the sensitivity of the pitch angle calculation to
errors in the altitude
derivative and the speed.
Since the errors in attitude and heading calculated with the aid of the
integration routine grow
rapidly, estimated attitude and heading errors must be fed back to the
integration routine,
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which is done with wire 17. If this is not done, the error equations in the
second Kalman filter
22 rapidly become invalid by reason of the fact that the equations are
fundamentally non-
linear. In addition, the estimates of the zero errors in the angular rate
gyros are fed back via a
wire 18. This results in better linearisation of the second Kalman filter 22
and furthermore the
sampling frequency fs can be kept down.
In some flying situations the calculations that are performed in the second
measurement
routine 21 are inferior, either because the measurement equations are not
sufficiently matched
or because the measurement data is inherently poor. Calculation of the roll
angle from air data
is used only in level flight. No measurement is used if the angular rates are
not sufficiently
small, typically a couple of degrees or so per second. The measurement
residuals are also
checked, where the measurement residuals are not allowed to exceed typically
one to two
times the associated estimated uncertainty.
Symbols
Coordinate systems
I (Inertial frame): a system fixed in inertial space.
When flying above the surface of the earth it is customary for the centre of
this system to
coincide with the centre of the earth. This is really an approximation, since
a system fixed in
inertial space must not rotate. Because the earth rotates around the sun, the
I -system will also
rotate. However, the error that arises is negligible. The accelerations and
angular rates
measured by the sensors in an inertial navigation system are relative to that
system.
N (Navigation frame): a system with its centre in the aircraft and with its xy
plane always
parallel to the surface of the earth.
The x-axis points to the north, the y-axis to the east and the z-axis
vertically down towards the
surface of the earth.
B (Body frame): a system in the aircraft, fixed to the body frame.
This coordinate system rotates with the aircraft. The x-axis points out
through the nose, the y-
axis through the starboard wing and the z-axis vertically down relative to the
aircraft.
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Table 1 Explanation of designations (symbols) for angles and angular rates.
See also Figure 4.
Angle between yB and the horizontal plane, tilted by the
angle 0 along xB (roll angle).
Initial value for the roll angle and estimated roll angle,
respectively
Oref Roll angle calculated with the aid of data from air data
and the heading derivative
0 Angle between xB and the horizontal plane (pitch angle).
00,6 Initial value for the pitch angle and estimated pitch angle,
respectively
ref Pitch angle calculated with the aid of data from air data
and the slip sensors
T
t¾ = [4, 0] Compressed symbol for roll angle and pitch angle
cp, TO, A(P Respectively: estimated roll and pitch angle, estimated
initial values for roll and pitch angle and difference
between integrated-out and reference-calculated roll and
pitch angle
Pref, TAHRS Respectively: roll and pitch angle calculated with the aid
of air data and primary data, and integrated-out roll and
pitch angle, where integration is done with the aid of the
angular rate gyro signals
V,11/ Respectively: angle between the projection of xB in the
horizontal plane and north (heading angle), and discrete
indexing of heading angle
a Angle between air-related rate vector projected on the t-
axis in body frame and projected on the x-axis in body
frame (angle of attack)
Angle between air-related velocity vector and air-related
velocity vector projected on the y-axis in body frame
(sideslip angle)
C Transformation matrix (3 x 3 matrix) which transforms a
vector from body frame (actual) to navigation frame. The
elements of this matrix are designated c11, C12, C13, C21,
C22, c23, c31, c32, C33, where the index designates row and
column in that order
- C. = B = CB Transformation matrix which transforms a vector from
body frame (calculated) to navigation frame
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Table I Explanation of designations (symbols) for angles and angular rates.
See also Figure 4.
8CI. Difference between calculated and true C
y = (,( yy, ,Y` '" Rotation around, respectively, the x-, y- and z-axis in
body frame, corresponding to the error between true and
calculated body frame
r Anti-symmetrical matrix form of the vector y
wIB = m = (mr wy, wZ)T Angular rate around, respectively, the x-, y- and z-
axis in
body frame (angular rate gyro signals). These angular rate
components are customarily also designated (p, q, r) T
WIB The vector wlB expressed in anti-symmetrical matrix
form
Sw = (Stns, Stay, S(u2)T Difference between actual and measured angular rate
around, respectively, the x-, y- and z-axis in body frame
WIN Rotation of navigation frame relative to inertial frame that
occurs when moving over the curved surface of the earth.
Anti-symmetrical matrix form
Table 2 Explanation of symbols for the geomagnetic field.
Bs, B. BZ Geomagnetic field vector components" in body frame
SBr SBy, SBz Difference between measured and actual field vector
components in body frame
BN, BB Geomagnetic field vector in navigation frame and body
frame, respectively
Table 3 Explanation of symbols used in connection with filters
k, k + 1 Used as an index, and represent the instant before
and after time updating, respectively
n, n + 1 Used to represent the present and subsequent
sample, respectively
-, + Used as an index, and represent the instant before
and after measurement updating, respectively
x, z, P State vector, measurement vector and estimate
uncertainty matrix
w, Q Process noise vector and covariance matrix for
process noise, respectively
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Table 3 Explanation of symbols used in connection with filters
A, F Prediction matrix in time-continuous and time-
discrete form
K, H, R Kalman gain matrix, measurement matrix and
covariance matrix for measurement noise,
respectively
uw, Ub, US Driving noise for the Markov processes
tiw, tb, Ts, 2, tt,'t2 Time-constants
fS Sampling frequency
Table 4 Explanation of other symbols. See also Figure 5.
bX, by, bZ Bias (zero errors)
sX, sy, sZ Scale factor errors
kXy, kXZ, k7x, kyz, kzX, kn, Cross-connection errors (for example, index xy
stands
for how the y -component affects the x -component).
Arise because the axes in triad are not truly orthogonal.
h, h Altitude and low-pass-filtered time-derived altitude
respectively
vt, v True speed relative to the air
g Gravity
