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| United States Patent Application |
20020004692
|
| Kind Code
|
A1
|
|
Nicosia, Joseph M.
;   et al.
|
January 10, 2002
|
High accuracy, high integrity scene mapped navigation
Abstract
An aircraft including an approach and landing system, including a
navigation unit for providing navigation information, a weather radar
unit for providing radar information, a processor which receives
navigation information from the navigation unit and information from the
weather radar unit, the processor unit providing an output representing
information concerning the aircraft in accordance with the provided
navigation information and radar information, a memory for storing
information representing a scene, the processor unit correlating the
stored scene information with the output representing information
concerning the aircraft to provide a mapped scene, a display unit for
displaying the output of said processor and the mapped scene, and a
steppable frequency oscillator for providing a signal which is stepped in
frequency to the weather radar unit, thereby providing an increased range
resolution.
| Inventors: |
Nicosia, Joseph M.; (Carlsbad, CA)
; Loss, Keith R.; (Escondido, CA)
; Taylor, Gordon A.; (Escondido, CA)
|
| Correspondence Address:
|
SUGHRUE, MION, ZINN, MACPEAK & SEAS
2100 Pennsylvania Avenue, N.W.
Washington
DC
20037
US
|
| Assignee: |
Winged Systems Corporation
|
| Serial No.:
|
799723 |
| Series Code:
|
09
|
| Filed:
|
March 7, 2001 |
| Current U.S. Class: |
701/16; 340/947; 701/17 |
| Class at Publication: |
701/16; 701/17; 340/947 |
| International Class: |
G08G 005/00 |
Claims
What is claimed is:
1. An aircraft including an approach and landing system, said system
comprising: at least one navigation unit for providing navigation
information; a weather radar unit for providing radar information; a
processor unit coupled to receive navigation information from said at
least one navigation unit, and to receive radar information from said
weather radar unit, said processor unit operable for providing an output
representing information concerning an aircraft in accordance with the
provided navigation information and radar information; a memory, coupled
to said processor unit, for storing information representing a scene,
said processor unit operable for correlating the stored scene information
with the output representing information concerning the aircraft to
provide a mapped scene; a display unit, coupled to receive the output of
said processor and coupled to said memory, for displaying the output of
said processor and the mapped scene; and a steppable frequency oscillator
for providing a signal which is stepped in frequency to said weather
radar unit, thereby providing an increased range resolution.
2. The approach and landing system as defined in claim 1, wherein said
processor unit operates according to a Generalized Hough Transform
map-match routine to provide the mapped scene.
3. The approach and landing system as defined in claim 1, wherein said
signal provided by said oscillator to said weather radar unit is randomly
stepped in frequency.
4. The approach and landing system as defined in claim 3, where said
signal provided by said oscillator to said weather radar unit comprises a
series of pulses.
5. The approach and landing system as defined in claim 4, wherein said a
first predetermined number of said pulses are randomly stepped in
frequency so that each of said predetermined number of pulses is at a
different frequency.
6. The approach and landing system as defined in claim 5, wherein the
predetermined number of pulses is 160.
7. The approach and landing system as defined in claim 1, wherein a
frequency step size of said oscillator is 250 KHz.
8. The approach and landing system as defined in claim 1, wherein said at
least one navigation unit includes an Inertial Navigation System (INS).
9. The approach and landing system as defined in claim 7, wherein said at
least one navigation unit further includes a Global Positioning System
(GPS).
10. A method of improving a range resolution of an aircraft approach and
landing system including a weather radar unit, the method comprising the
steps of: generating a waveform which is stepped in frequency; and
applying the generated waveform to the weather radar unit.
11. The method as defined in claim 10, wherein said generating step
includes the step of randomizing the frequency steps so that the waveform
applied to the weather radar unit is randomly stepped in frequency.
12. The method as defined in claim 11, wherein said generating step
includes generating a series of pulses as the waveform.
13. The method as defined in claim 12, wherein a predetermined number of
said pulses is randomly stepped in frequency so that each pulse is at a
different frequency.
Description
FIELD OF THE INVENTION
[0001] The present invention is directed to an autonomous precision
approach and landing system (APALS) for enabling low visibility landings
at airports.
BACKGROUND OF THE INVENTION
[0002] Current industry practice for low-visibility landings is dependent
on airport ground equipment and inertial navigation equipment. These
techniques are limited to landings at those runways which are equipped
with highly reliable transmitters of radio frequency localizer and glide
slope information. These existing systems either land the aircraft using
an automatic pilot or aid the pilot in landing the aircraft by providing
the pilot with autopilot control commands displayed on a Head Up Display
(HUD).
[0003] It has been suggested that future systems make use of information
received from the Global Positioning System (GPS) in conjunction with
on-board Inertial Navigation systems (INS) to generate the necessary
precise navigation for landing. However, in addition to the external
satellites required for GPS, these systems are currently envisioned to
require ground stations at known locations near the runway for the
differential precision necessary for landing. Other proposed systems
provide the pilot with a real time image of the runway scene as derived
from millimeter wave (MMW), X-Band, or infrared (IR) frequencies.
[0004] The following are further examples of navigation systems known in
the art.
[0005] U.S. Pat. No. 5,136,297 to Lux et al discloses an autonomous
landing system. The Lux patent includes a navigation unit employed in the
system which includes a sensor, flight position data, an image correction
unit, a segmentation unit, a feature extraction unit and a comparison
unit. The Lux patent discloses that a comparison is conducted as to
whether or not a sequence of features in the overflight path image
pattern agrees with features found in a reference store, such as map data
which is stored in the system. Further, Lux discloses the use of a radar
navigation system for use as a sensor in the system.
[0006] U.S. Pat. No. 4,698,635 to Hilton et al discloses a radar guidance
system coupled to an inertial navigation apparatus. The system includes a
master processor, a radar altimeter, a video processor, a memory and a
clock. The memory has stored therein cartographic map data.
[0007] U.S. Pat. No. 4,495,580 to Keearns is cited to show a navigation
system including a radar terrain sensor and a reference map storage
device for storing data representing a terrain elevation map.
[0008] U.S. Pat. No. 4,910,674 to Lerche discloses a navigation method
which includes a correlator for comparing terrain reference data with
processed altitude data obtained with a wave sensor.
[0009] U.S. Pat. No. 4,914,734 to Love et al is cited to show a
map-matching aircraft navigation system which provides navigational
updates to an aircraft by correlating sensed map data with stored
reference map data.
[0010] U.S. Pat. No. 4,891,762 to C
hotiros is cited to show a pattern
recognition system for use in an autonomous navigation system.
[0011] The above-mentioned prior systems suffer from one or more of the
following problems:
[0012] 1) Reliance on ground-based systems for precise terminal landing
information severely reduces the number of runways available for Cat III
a and b landings (currently 38 runways in the U.S.).
[0013] 2) Reliance on GPS' and differential ground transmitters for GPS
creates a need for currently rare ground equipment and a lack of
reliability (based on the military nature of GPS). The GPS is a military
program owned, operated, and paid for by the United States Air Force
originally intended for military navigational purposes and is designed so
that civilian use can be made of it but at a reduced accuracy. The
military uses a very special code which gives them better accuracy, that
is called the P code. The normal civilian code is called the C code which
is good to about 30 m in accuracy; however, the military retains the
right to disable the C code to the point where the accuracy goes down to
about no better 100 m. This is what the military refers to as "selective
availability" so that in time of conflict they can turn on selective
availability and deny the enemy the ability to navigate better than 100
m. There are a number of schemes for getting around the inaccuracies
imposed by the military. However, the Air Force has maintained a position
that they are against any of these schemes which improve the accuracy
when they are trying to make it inaccurate.
[0014] The lack of reliability is also a result of the fact that, in order
to be accurate, at least four satellites must be present in the overhead
view; and, if one of the four satellites fails, then the accuracy will be
degraded. Thus, the reliability is not just based on the on-board
equipment, i.e., the GPS receiver, but it is also based on the
reliability of the satellites themselves.
[0015] 3) Additional sensors such as MMW and IR, currently envisioned for
systems to provide pilots with the "situational awareness" necessary to
successfully land in low visibility conditions are expensive additions to
the on-board flight equipment and are marginal in performance. MMW
real-beam radars provide "grainy" low resolution images which are
difficult to interpret and IR systems cannot penetrate in many types of
fog that cause the "low visibility" in the first place.
SUMMARY OF THE INVENTION
[0016] It is therefore an object of the present invention to overcome the
problems associated with the prior approach and landing systems.
[0017] It is another object of the invention to provide an approach and
landing system which provides low visibility take-off and landing
assistance for several classes of aircraft.
[0018] It is another object of the invention to provide safe landing of
general aviation and transport aircraft (covered by parts 25, 91, 121 and
125 in the Code of Federal Regulation) in low visibility conditions
[Category II, IIIa, and IIIb defined by the Federal Aviation
Administration (FAA)] without dependence on high reliability ground
transmitting equipment.
[0019] These and other objects are accomplished by the present invention
which provides an Autonomous Precision Approach & Landing System that
makes use of radar echoes from ground terrain and cultural (man made)
targets to provide the on-board Inertial Navigation System with accurate
aircraft position and velocity updates. According to the invention, these
measurements come from a modified standard X-band, low-resolution weather
radar.
BRIEF DESCRIPTION OF THE DRAWINGS
[0020] FIG. 1 is a block diagram of the APALS system according to the
invention.
[0021] FIG. 2 is a waveform diagram according to the invention.
[0022] FIG. 3 is a circuit diagram of a modified weather radar device
according to the invention.
[0023] FIGS. 4(a)-4(e) illustrate steps of APALS Synthetic Aperture Radar
(SAR) processing according to the invention.
[0024] FIG. 5 shows a reference scene and a corresponding Radar Map
according to the present invention.
[0025] FIG. 6 illustrates a Generalized Hough Transform Map-Match
Algorithm employed in the present invention.
[0026] FIG. 7 illustrates a Navigation Solution according to an example of
the invention.
[0027] FIG. 8 illustrates a Head-up Display (HUD) according to the present
invention.
DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT
[0028] Several of the important features of the APALS system according to
the invention are set forth below:
[0029] A. Modified Weather Radar: The modification to a conventional
weather radar allows the modified weather radar to make high resolution
synthetic aperture maps of overflown terrain.
[0030] B. Area Correlation: This refers to the application of matching
synthetic aperture radar maps with previously stored references to locate
specific spots on the ground near a path to a specific runway.
[0031] C. Range/Range Rate Measurements Integrated Into Kalman Filter:
This refers to the application of using high resolution radar range and
velocity measurements of specific, but not augmented, spots on the ground
of known location to update a navigation system using Kalman filtering.
[0032] D. Situational Awareness Display Format: This refers to the
application of precise navigational information to provide the pilot with
a "situational awareness" display of sufficient accuracy to allow the
pilot to land the aircraft in low visibility conditions in the same
manner as if (s)he were using his/her judgement to land the plane in good
visibility conditions.
[0033] Each of the above features is discussed in detail below.
[0034] FIG. 1 is a block diagram of the APALS system according to the
present invention. The other NAV Aids 2 refers to the navigation aids
that are conventionally employed on any aircraft and include, for
example, a VOR (VHF omnidirectional radar), DME (distance measuring
equipment) receiving equipment, the artificial horizon, the vertical
gyro, the airspeed indicator, and the altimeter (which is a barometric
altimeter). The APALS processor 16 will make use of this information in
order to monitor the reasonableness of the APALS estimate concerning the
state of the vehicle, which is the output {circumflex over (X)} from the
processor 16. The above-discussed elements all interface to the system
over a standard interface bus such as the known ARINC 429 bus.
[0035] The INS (inertial navigation system) or IMU (inertial measurement
unit) 4 are inertial instruments that measure the translational
accelerations and the angular rates. There are several different IMU's
that can be employed in APALS, one of which is, for example, a Bendix
unit known as the Bendix mini-tact IMU.
[0036] The GPS receiver 6 is a special receiver that is designated to
receive the satellite signals and deduce from those satellite signals the
position and velocity of the aircraft. There are several models that can
be used for this, but there is only one or two at present that have
passed the FAA requirements for primary navigation equipment on-board an
aircraft.
[0037] The weather radar 8 which is also equipment that will already be
on-board the aircraft is, according to the invention, as will be
discussed below modified. For example, the Honeywell Primus 870 made by
Honeywell may be employed. This radar is a non-coherent radar so it would
have to be modified with a new receiver and transmitter to make it
coherent. The weather radar 8 provides a range R, and range rate R'
outputs to the Processor. The weather radar 8 receives a radar frequency
control signal from the Processor 16 which will be discussed below in
connection with the radar modification shown in FIG. 3.
[0038] The scene data base 10 is a data base created by going to different
airports that will use the system and making flights during which the
radar signatures of the ground returns are measured. Further, aerial
p
hotographs are taken to use together with the radar data to make
references which would then be used to compare against the radar returns
that will occur when the actual low visibility landing is taking place.
[0039] The display generator 12 and the display 14 are typically supplied
by the manufacturer of the device known as a Head-Up Display (HUD), which
is what the APALS uses as a see through device that allows the pilot to
view the outside world, and see the APALS display in front of him or her.
The pilot will see a virtual runway even when the actual runway is
obscured by, for example, clouds or fog. Suitable HUD's are currently
built by GEC Avionics (Great Britain), Flight Dynamics, Inc. (Portland,
Oregon) and Sextant Avionique (France). The actual APALS output is a
vector labeled {circumflex over (X)} and consists of the position,
velocity and attitude information of the aircraft as best determined by
the APALS system. The display generator typically takes that information
and generates what the outside world scene would look like from the
currently estimated state of the aircraft, {circumflex over (X)}.
[0040] The processor 16 receives inputs from elements 2, 4, 6, 8 and 10
and outputs vector {circumflex over (X)}. There are a number of known
processors that can be used for APALS.
A. Modified Weather Radar
[0041] The radar modification consists of applying randomized stepped
frequency pulse compression to allow a range resolution of 4 meters (even
though a pulse length of 2 .mu.sec would normally limit range resolution
to 300 meters). The waveform consists of a series of pulses at the normal
higher Pulse Repetition Frequency (PRF) of the weather radar (.about.3000
Hz). The first 160 pulses are randomly stepped in frequency so that each
pulse is at a different frequency. Any one pulse, however, stays at a
constant frequency for its entire 2 .mu.s duration. This is important
because it allows the precision measurements to be made without modifying
the band-pass characteristics of the radar receiver. The frequencies are
such that there are 160 different frequencies spanning 40 Mhz in 250 Khz
steps. Over the time of each set of 160 pulses, the 40 Mhz spectrum is
completely filled. The order of the steps is randomized to avoid
ambiguities. A diagram of the waveform is shown in FIG. 2. The step size
is 250 Khz which corresponds to a 4 .mu.s or 600 meter "coarse" range
bin. This wider (than 2 .mu.s) coarse bin was chosen to eliminate any
ambiguities from adjacent pulse "spillover" energy. The waveform can be
as long as necessary to integrate returns for a precise Doppler
measurement.
[0042] The waveform is extended to multiples of 160 pulses because 160 is
the number of pulses required to cover the 40 MHz bandwidth needed for 4
meters range resolution. In this case the integration time is limited to
0.25 seconds since, at X-band, it will yield a velocity resolution of
0.07 m/sec. which is a sufficient accuracy to update the navigation
Kalman filter.
[0043] FIG. 3 shows a typical implementation of generating the waveform by
adding a steppable frequency oscillator 17 to the weather radar. As shown
in FIG. 3, the majority of the circuits of radar (transmitter 18,
frequency multipliers, dividers and mixers 20, receiver 22, duplexer 24)
remain unchanged. The integration of the modified waveform into the
weather radar from each of the different radar manufacturers will be
unique.
[0044] Processing the waveform to achieve the desired resolution (4 m in
range and 0.07 m/sec. in Doppler) is accomplished in a highly efficient
manner because the image is being taken of just one short segment of
range (where the beam intersects the ground). The "picture" or map will
extend 160 meters or 40 pixels in range and therefore is contained in one
600 meter "coarse range". This is in effect "zoom processing" of the
region which is very efficient. The application of zoom processing to
this unique waveform allows very high resolution to be achieved with very
minor physical modifications to a normally low resolution radar.
[0045] Motion Compensation: The Synthetic Aperture Radar (SAR) map that is
required for this system to work well covers a small area and the
accuracy of the vehicle motion required is within the bounds of the
knowledge of the system. This is because the navigation portion of the
system will have very precise knowledge of the state of the vehicle's
motion relative to the earth as will be discussed below.
[0046] The following delineates the steps required for the two dimensional
zoom processing of APALS.
[0047] As described in the waveform of FIG. 2, during the integration of
0.25 seconds there are 4000 pulses. This large integration time is broken
down into 25 sub-intervals or "words" of 160 pulses each (FIG. 2). During
each sub-interval, the full bandwidth of 40 MHz is transmitted by having
each pulse at a different frequency taken, at random, from a set of 160
frequencies spaced 250 KHz apart. If the lowest frequency were 9 GHz, the
sequence of frequencies would be: 9.000 GHZ, 9.00025 GHz, 9.005 GHz,
9.00075 GHz, 9001 GHz . . . 9.040 GHz. The order is scrambled randomly
for reasons which will be explained below.
[0048] FIG. 4(a ) is a wave diagram for explaining a coarse range bin.
With a 2.mu.s pulse (1), if the receive signal (2) and (3) is sampled the
same time delay after the transmit pulse, those returns will all
represent targets or ground clutter from the same range. Since the pulse
is 2 .mu.s wide, the energy at the time of the sample will come from 150
meters in front of to 150 meters behind the point on the ground with a
time delay of the sample center. The processing chosen covers a 600 meter
region centered at the time of the central return. While there should be
no return in any area beyond .+-.150 meters, there may be spill-over from
other bright reflectors and by processing the wider coarse bin, the
possibility of ambiguous foldover is eliminated.
[0049] To simplify the explanation, a "linear" rather than a random
frequency sequence is examined. In FIG. 4(b) it is seen that the samples,
each being from a different pulse in the chain of 4000 pulses, range in
frequency from f.sub.1 to f.sub.160 and then f.sub.1 to f.sub.160 is
repeated for the next 160 Pulse Repetition Intervals (PRI's) and so on
for 25 sub-intervals until 4000 pulses have been transmitted and 4000
receive samples have been gathered. As shown from FIG. 4(b), processing
the 4000 samples into a range profile of fine 4 meter bins is nothing
more than summing the sample values that come from the same frequency
(there are 25 of them) and using the sum as one of the inputs to an
Inverse Digital Fourier Transform (IDFT), and representing that process
for all 160 frequencies. A Fourier transform is a process of taking
samples in time of a waveform and determining how much energy there is at
each frequency and the inverse of the process is taking samples of energy
content at different frequencies and producing what the waveform looks
like as a function of time (time is equivalent to range for a radar
echo).
[0050] The example given above and in FIG. 4(b) is a simplification that
would work well if there were no motion between the radar and ground. In
order to describe what is necessary for APALS to accommodate motion, it
is necessary to introduce the concepts of phase and phase compensation.
[0051] The phase of a radar signal depends on two items, the frequency or
wavelength of the signal and the distance from the transmitter. This is
shown in FIG. 4(c). Radar waves are variations in local electric and
magnetic fields which can be represented by the sine wave shown in FIG.
4(c).
[0052] The distance from one peak to another is called the wavelength and
is determined by the frequency of the transmitted signal. FIG. 4(c) shows
a Receiving Object whose distance is 51/4 wavelengths away from the
Transmitter. The whole number of wavelengths is not important to phase
but the remainder or fractional part is the phase difference between what
is sent and what is received. In FIG. 4(c), the phase difference is 1/4
of one wavelength or 90.degree. (one wavelength is characterized by one
full cycle of 360.degree.). If the receiving object simply reflected the
signal back to a Receiver co-located with the transmitter, as is the case
with radar, the distance and, therefore, the phase shift is doubled to
180.degree..
[0053] The phase of the returns from different samples but off of the same
stationary object will change with a frequency hopped radar such as
APALS. FIG. 4(d) shows the effect of changing wavelength on phase. In
FIG. 4(d), even though the transmitter and the receiving object are the
same distance apart as they are in FIG. 4(c), the phase has increased to
180.degree., one way. In FIG. 4(d) there are 51/2 wavelengths in the
single path-length.
[0054] As the frequency of the pulses increases (FIG. 4(b)), the
wavelength gets shorter and the phase difference increases. It is
precisely this change in phase as a function of frequency that allows the
IDFT to discern the ranges of object from the frequency content of the
return samples. The samples, by their nature, contain both a measure of
the energy and a measure of the phase difference of the return from a
pulse of a particular frequency.
[0055] Relative motion between the Transmitter and the Reflecting Object
causes a phase shift with time which causes a phase shift from pulse to
pulse as shown in FIG. 4(e).
[0056] This phase shift as a function of time is known as the Doppler
effect. The measurement of this rate of change of phase or Doppler is
what allows APALS to update range rate as well as range for the inertial
system after each map-match. It is also what creates the need for phase
compensation.
[0057] It is important to note that the phase changes due to increasing
frequency have the same characteristic as the phase changes due to
increasing distance between the transmitter and the reflecting object. In
both cases, the phase changes will increase steadily with time. This is
the ambiguity that was mentioned earlier. As long as the frequencies are
stepped in order from pulse to pulse, the IDFT will not be able to
distinguish between distance of the Reflecting Object and the speed of
the Reflecting Object. This is because the distance information is
contained in the phase differences of the reflections off a single object
at different transmit frequencies.
[0058] To obviate this ambiguity problem, the frequencies are not stepped
in order of increasing frequency as shown in FIG. 4(b), but rather
randomly. This breaks the linearity of the phase changes with time due to
frequency shifting so that it can be separated from the always linear
changing phase that is due to constant velocity motion. It is still
necessary to present the sampled values of the return signal to the IDFT
in order of increasing frequency so the order of frequencies transmitted
must be kept track of. This is accomplished in APALS by using a
pre-stored pseudo-random frequency order which is 4000 elements long.
[0059] Once the relationships between distance, phase, and velocity are
understood in the context of the APALS waveform as described above, the
phase compensation and processing for APALS can be concisely explained in
the following steps:
[0060] 1) The received waveform is converted to a set of digital samples
which preserves both signal strength and phase difference. This process
is well known in the art as in-phase and quadrature sampling or I & Q
sampling. The digital samples are stored temporarily and tagged both with
their order in time of reception and with their frequency order.
[0061] 2) The coarse range of interest is identified by the system based
on the desired map area, and the samples which come from the
corresponding delay are singled out for processing.
[0062] 3) The Doppler frequencies are determined for the desired map area,
and the center frequencies for the Doppler bins to be processed are
determined.
[0063] 4) For each Doppler bin, the set of samples is arranged in order of
the transmit frequency which generated it, and presented for phase
compensation prior to being sent to the IDFT.
[0064] 5) For each Doppler bin the phase rotation for each transmit
frequency and each receive time is calculated and that phase is
subtracted from each sample according to its time order and adjusted for
its wavelength based on its transmitted frequency. The net effect is that
motion is taken out of the samples that are moving at the precise
velocity that is the designated center of the Doppler bin or filter.
Objects that are moving faster or slower will not "add up" because the
phases of their samples will not be recognized by the IDFT.
[0065] In order to prevent smearing, due to accelerations which change the
velocity during the 0.25 second dwell, the compensating phase rotations
must be calculated based, not on a constant velocity, but on a velocity
modified by the aircraft's accelerations. These acceleration values are
readily available in the APALS system because they are part of the
accurate state vector which is calculated by the navigation filter.
B. Area Correlation
[0066] The APALS system uses the Scene Data Base 10 for pre-stored scenes
as references with which to compare the radar maps that are produced
through the weather radar. The radar maps can be thought of as comprising
resolution "cells" whose dimensions are range resolution in the down
range direction and range rate resolution in the cross range dimension.
Down range direction is simply the radial distance from the aircraft. In
a radar system the normal way of mapping with a radar is to cut the
return up into pieces that are returns coming from different ranges. This
is because the radar is capable of measuring range by the time delay of
the return. The down range dimension is always the distance radially away
from the radar. The present system is typically looking at 45.degree.
right or left and so the down range dimension is a line going 45.degree.
off the nose of the aircraft. The cross range dimension is the dimension
that is directly orthogonal or at 90.degree. to the down range dimension.
It is not always exactly 90.degree., in the present system it is measured
by changes in the doppler frequency of the return. The frequency of the
return is dependent on the relative velocity in the direction of that
return.
[0067] The contextual information in the radar map is compared to that of
the reference. When a match is found for each point of ground represented
by a cell in the reference, the range and range rate of the sensed scene
are known with respect to the aircraft. Since the location of at least
one point in the scene is known precisely with respect to the desired
touch down point, by simple vector subtraction, the range rate to the
touch down point is calculated. There are two aspects to generating this
important information:
[0068] 1) Generating a reference which will allow a locally unique match
to the radar map.
[0069] 2) Using a correlation algorithm that efficiently "fine-tunes" the
match point to a 1-cell accuracy and provides a "measure of goodness" or
confidence in the match.
[0070] The references for APALS are generated from aerial p
hotographs that
have been digitized or scanned into a computer and from SAR maps. The SAR
maps are taken in two swaths, one on either side of the final approach
trajectory, that are centered 1 mile offset of the aircraft's trajectory
(ground projection). Software is used to match points in the aerial p
hoto
with coordinates of a pre-stored navigation grid so that the location of
any point in the p
hoto is known relative to the runway touch down point
(no matter how far the scene is away from the runway). The key features
of these references are that they are simple and that they rely on
prominent cultural and natural features which produce consistent radar
returns that are distinguishable as lines with a unique shape. The two
types of features to have these characteristics consistently are the
corners made by a building face and the ground, and roads.
[0071] FIG. 5 shows a typical reference and the corresponding radar map.
In this case the dots represents a specific pattern of a highway
crossing. Such simple references are found to work well when used with
the map matching algorithm well known in the art as the "generalized
Hough transform" which is described below.
[0072] The correlation algorithm used for map matching in the APALS system
is the well known generalized Hough transform. The Hough transform is
incorporated in several image processing techniques in use today,
especially in military applications. In general, the Hough transform is a
computer method typically used to find a line or other simple
shapes/patterns in a complex picture. This scene matching algorithm is
advantageous in that:
[0073] a) It requires very few points to be compared, (i.e., much less
than the total in the scene).
[0074] b) It requires the computer to perform only the mathematical
operation of adding and avoids the other more time consuming mathematical
operations.
[0075] In FIG. 6(A) a simple reference is shown to the left and a very
sparse sensed scene (just two points) is shown to the right. The
algorithm works such that every point in the sensed scene is operated on
in the following manner:
[0076] 1) Each point in the reference is tried as the particular sensed
point.
[0077] 2) As each point in the reference is tried, the position that the
"nominated point" (black point in the reference) occupies in the sensed
scene is recorded. This is shown in the sequence of scenes in FIG. 6b.
After all the points in the reference are used, the set of recorded
"nominated" points in the sensed scene is an "upside-down and backwards"
replica of the reference scene, rotated about the "nominated point". This
reversed image is shown above the last block of FIG. 6b.
[0078] 3) As all the points in the reference are operated on, the point in
the scene with the most accumulated nominations is designated as the
match point. This is illustrated in FIG. 6c.
C. Range/Range Measurements Integrated Into Kalman Filter
[0079] The measurements being made by the radar are the magnitude of the
range vector and the magnitude of the range-rate vector from the aircraft
to a specific point in the map match scene. If at least three of these
measurements were being made simultaneously, one could solve for the
three elements of aircraft velocity explicitly. This solution is shown in
FIG. 7. The sequence of measurements being made in FIG. 7 are the range
and range-rate to known points on the ground. The way in which these are
used is exactly analogous to the way the global positioning system works
with satellite measurements. For example, consider three satellites that
are displaced in the sky angularly. If the range and the range rate to
those satellites are known, then the components of both the position
vector and the velocity vector of the position relative to those three
satellites can be solved. Beyond that, it is necessary to depend on
information stored on the satellites and transmitted down so that it can
be determined where they are. Then the position can be deduced. The
difference in APALS is that the APALS system takes pictures of the actual
ground and compare the taken pictures to stored maps. Once it compares
them to stored maps and finds the match point, the match point is
immediately known in terms of its range and range rate at that point of
time. As APALS progresses it measures its range and range rate relative
to known points on the ground. Once it measures three different points,
it can form a deterministic solution of where it is, in what direction it
is heading and how fast it is going. The sequence in APALS is a little
different in that it does not obtain a good geometric case in close time
proximity. Rather, it flies along mapping from side to side but not
getting that third one. It repetitively gets the range and range rates on
each side, and over time forms a very accurate solution iteratively to
the equation that allows it to know its position vector and velocity
vector.
[0080] Since, however, the measurements being made by radar are separated
in time by as much as 4 seconds, it is necessary to solve for the
components of the vectors recursively, over time, through the use of a
Kalman statistical filter. The Kalman filter uses data from an inertial
navigation system INS, or an inertial measurement unit (IMU) 4(FIG. 1) to
determine the motion of the aircraft between measurement times. The INS
or IMU 4 is more than just the inertial instruments, but the complete
collection of inertial instruments and computer that result in a
navigation solution including position and velocity. An INS is typically
only used on commercial aircraft today that traverse the ocean.
D. Situational Awareness Display Format
[0081] The raw output of the APALS system is a very accurate estimate of
the "state vector" of the aircraft in a coordinate system that has its
origin at the desired touch down point on the particular runway that is
targeted. This knowledge of position, velocity and attitude are provided
as a "situational awareness" display which the pilot can effectively use
to safely land the aircraft. This is accomplished primarily by displaying
a conformal, properly positioned runway outline in proper perspective to
the pilot on a Head-up Display (HUD). In clear weather the image will
overlay that of the actual runway edges as the pilot views the runway
through the wind screen. The appropriate touch-down zone will also be
displayed (conformably), thereby providing the pilot situational
awareness such that (s)he may land his/her aircraft in the same manner as
(s)he would in visual meteorological conditions (VMC). The use of the HUD
allows the pilot the earliest possible view of the actual visual scene on
the way to touchdown. The precise navigational knowledge of the APALS
system together with the radar altimeter allows for the generation of a
"flare cue" to tell the pilot when and how to flare for a precise, slow
descent-rate touchdown.
[0082] The key aspect in being able to land using situational awareness is
the display of the conformal runway symbol and extended center-line in a
context which also includes conformal symbols of the horizon line, flight
path vector, and 3.degree. glide slope indicator. The display of these
symbols can be derived from APALS navigation knowledge or from other
aircraft instruments. FIG. 8 shows a particular symbol set with the
addition of the synthetic runway image.
[0083] True ground speed information in the APALS system is sufficient to
generate moving segments in the extended center-line to create a
sensation of "speed" for the pilot.
[0084] A secondary aspect of APALS is that the X-band radar together with
APALS enhanced resolution can detect runway incursions prior to landing
in low visibility conditions. This is accomplished with a broad sweeping
ground map just prior to landing which is similar to the "ground map
mode" of a conventional weather radar. The notable exception is that the
range resolution is two orders magnitude sharper than that of the
conventional weather radar. This allows large objects, such as a taxiing
aircraft to be resolved into more than one pixel. As a result, the APALS
is able to correctly distinguish and separate larger and smaller objects
from each other. When this is coupled with the precise navigational
knowledge of APALS, any radar returns can be related to their precise
location in the airport scene to determine if they are a hazard.
[0085] As set forth above, the APALS system does not depend on ground
equipment installed at a particular airport. It therefore offers the
potential of low-visibility landings at many airports than are currently
unavailable for such landings because they do not have the ground
equipment of sufficient reliability to support the automatic landing
systems.
[0086] Further, APALS does not require the addition of any new vision
sensors on the aircraft or installations on the ground and therefore
installation costs are minimum. The accuracy and reliability of the
display can be checked and verified during normal visual operations. It
can also be routinely used for training at any airport during normal
visual operations. In addition, it can detect runway obstacles prior to
landing without adding any sensors.
[0087] The display for APALS can be either head-up or head-down.
[0088] The waveform can be varied in PRF (Pulse Repetition Frequency),
pulse width, bandwidth, and integration time to affect changes in
resolution and processing dynamic range. The Pulse Repetition Frequency
is the number of pulses per second that the radar transmits. This is
important because the PRF determines the amount of average power that the
radar receives. It also determines what kind of ambiguities there are in
range.
[0089] Those skilled in the art will understand that variations and
modifications can be made to system described above, and that such
variations and modifications are within the scope of the invention. For
example, different scene match correlation algorithms and different
navigation filters (other than Kalman) such as neural net "intelligent"
estimators can be used without changing the nature or concept of the
present invention.
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