U.S. patent application number 15/946063 was filed with the patent office on 2021-07-01 for system and method for intercepting an exo-atmospheric target using passive ranging estimation.
This patent application is currently assigned to RAYTHEON COMPANY. The applicant listed for this patent is RAYTHEON COMPANY. Invention is credited to Eric Blake, Pradyumna Kannan, Huy P. Nguyen, Elliot Schwartz.
Application Number | 20210199752 15/946063 |
Document ID | / |
Family ID | 1000005278535 |
Filed Date | 2021-07-01 |
United States Patent
Application |
20210199752 |
Kind Code |
A1 |
Nguyen; Huy P. ; et
al. |
July 1, 2021 |
SYSTEM AND METHOD FOR INTERCEPTING AN EXO-ATMOSPHERIC TARGET USING
PASSIVE RANGING ESTIMATION
Abstract
A target intercept system for guiding an interceptor to a target
using passive ranging includes an EO/IR sensor that provides target
azimuth and elevation angles, target irradiance, target area and
target length. A dual Kalman Filter architecture is implemented
where, prior to a target image becoming resolved, i.e., prior to
endgame, a first Kalman Filter provides guidance as a function of
target azimuth and elevation angles and target irradiance
measurements. After the target image becomes resolved, i.e., at
endgame, a second Kalman Filter provides guidance as a function of
target azimuth and elevation angles, target area and, optionally,
target length, instead. The dual Kalman Filter approach improves
the estimates of time-to-go by optimizing the on-board EO/IR sensor
measurements at the optimal times.
Inventors: |
Nguyen; Huy P.; (Waltham,
MA) ; Schwartz; Elliot; (Waltham, MA) ; Blake;
Eric; (Waltham, MA) ; Kannan; Pradyumna;
(Waltham, MA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
RAYTHEON COMPANY |
Waltham |
MA |
US |
|
|
Assignee: |
RAYTHEON COMPANY
Waltham
MA
|
Family ID: |
1000005278535 |
Appl. No.: |
15/946063 |
Filed: |
April 5, 2018 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
F41G 7/2226 20130101;
G01S 7/021 20130101; F41G 7/2293 20130101; F41G 7/2253
20130101 |
International
Class: |
G01S 7/02 20060101
G01S007/02; F41G 7/22 20060101 F41G007/22 |
Claims
1. A system for guiding an interceptor toward a target using
passive ranging estimation, the system comprising: an EO/IR sensing
device configured to: detect the target and output corresponding
target azimuth information, target elevation information, target
irradiance information, target length information, target area
information and a respective validity indicator for each of the
target azimuth information, target elevation information, target
irradiance information, target length information and target area
information; determine that the target irradiance information is
valid and the target area information is invalid only when the
target is detected as a point source; and determine that the target
irradiance information is invalid and the target area information
is valid only when an image of the target has been resolved,
wherein the target area information and the target irradiance
information cannot both be indicated as being valid at a same time;
a passive ranging target state estimator, coupled to the EO/IR
sensing device and configured to generate interceptor guidance
information, comprising: a first Kalman Filter configured to
generate the interceptor guidance information as a function of the
target azimuth information, the target elevation information and
the target irradiance information; and a second Kalman Filter
configured to generate the interceptor guidance information as a
function of the target azimuth information, the target elevation
information and the target area information, wherein the first
Kalman Filter is operative to generate the interceptor guidance
information only when the target irradiance information is
indicated as being valid, wherein the second Kalman Filter is
operative to generate the interceptor guidance information only
when the target area information is indicated as being valid; and
an interceptor guidance module, coupled to the passive ranging
target state estimator, configured to control movement of the
interceptor as a function of the generated interceptor guidance
information.
2. The system of claim 1, wherein the second Kalman Filter is
further configured to generate the interceptor guidance information
as a function of the target length information.
3. (canceled)
4. The system of claim 1, wherein the EO/IR sensing device is
further configured to determine that the target is detected as a
point source when the target is detected as a single pixel.
5. A method of guiding an interceptor toward a target using passive
ranging estimation, the method comprising: detecting the target
with an EO/IR sensing device and outputting corresponding target
azimuth information, target elevation information, target
irradiance information, target length information, target area
information and a respective validity indicator for each of the
target azimuth information, target elevation information, target
irradiance information, target length information and target area
information; determining a range from the interceptor to the target
as a function of one or more of: the target azimuth information,
target elevation information, target irradiance information, target
length information, target area information and the respective
validity indicators; determining that the range is greater than a
first predetermined distance only when the target is detected by
the EO/IR sensing device as being a point source; and determining
that the range is less than or equal to the first predetermined
distance only when the EO/IR sensing device has resolved an image
of the target, wherein the EO/IR sensing device cannot have both
detected the target as a point source and resolved the image of the
target at the same time; generating interceptor guidance
information by one of: when the determined range is greater than
the first predetermined distance, implementing a first Kalman
Filter configured to generate the interceptor guidance information
as a function of the target azimuth information, the target
elevation information and the target irradiance information; or
when the determined range is less than or equal to the first
predetermined distance, implementing a second Kalman Filter
configured to provide the interceptor guidance information as a
function of the target azimuth information, the target elevation
information and the target area information; and controlling
movement of the interceptor as a function of the generated
interceptor guidance information.
6. The method of claim 5, wherein the second Kalman Filter is
further configured to generate the interceptor guidance information
as a function of the target length information.
7. (canceled)
8. The method of claim 5, wherein determining that the range is
greater than the first predetermined distance, further comprises:
indicating that the target irradiance information is valid and the
target area information is invalid.
9. The method of claim 5, wherein determining that the range is
less than or equal to the first predetermined distance further
comprises: indicating that the target irradiance information is
invalid and the target area information is valid.
10. The method of claim 5, wherein the EO/IR sensing device
determines that the target is a point source when the target is
detected as a single pixel.
11. A system for guiding an interceptor toward a target using
passive ranging estimation, comprising: an EO/IR sensing device
configured to detect the target and output corresponding target
azimuth information, target elevation information, target
irradiance information, target length information, target area
information and a respective validity indicator for each of the
target azimuth information, target elevation information, target
irradiance information, target length information and target area
information; a passive ranging target state estimator coupled to
the EO/IR sensing device configured to: determine a range from the
interceptor to the target as a function of one or more of: the
target azimuth information, target elevation information, target
irradiance information, target length information, target area
information and the respective validity indicators; determine that
the range is greater than a first predetermined distance only when
the target is detected by the EO/IR sensing device as being a point
source; and determine that the range is less than or equal to the
first predetermined distance only when the EO/IR sensing device has
resolved an image of the target, wherein the EO/IR sensing device
cannot have both detected the target as a point source and resolved
the image of the target at the same time; the passive ranging
target state estimator further configured to generate interceptor
guidance information by one of: when the determined range is
greater than the first predetermined distance, implementing a first
Kalman Filter configured to generate the interceptor guidance
information as a function of the target azimuth information, the
target elevation information and the target irradiance information;
or when the determined range is less than or equal to the first
predetermined distance, implementing a second Kalman Filter
configured to provide the interceptor guidance information as a
function of the target azimuth information, the target elevation
information and the target area information; and an interceptor
guidance control module, coupled to the passive ranging target
state estimator, configured to control movement of the interceptor
as a function of the generated interceptor guidance
information.
12. The system of claim 11, wherein the second Kalman Filter is
further configured to generate the interceptor guidance information
as a function of the target length information.
13. (canceled)
14. The system of claim 11, wherein determining that the range is
greater than the first predetermined distance further comprises:
indicating that the target irradiance information is valid and the
target area information is invalid.
15. The system of claim 11, wherein determining that the range is
less than or equal to the first predetermined distance further
comprises: indicating that the target irradiance information is
invalid and the target area information is valid.
16. The system of claim 11, wherein the EO/IR sensing device is
further configured to determine that the target is a point source
when the target is detected as a single pixel.
Description
GOVERNMENT RIGHTS
[0001] N/A
BACKGROUND
[0002] With modern threats becoming increasingly complex and agile,
area-defense systems now include missiles with a GNC (Guidance,
Navigation and Control) architecture to ensure success. One aspect
of a known GNC architecture is a Passive Ranging Estimator for
providing time-to-go (t.sub.go) information to missile systems
during a terminal phase of flight. Accurate time-to-go is critical
for zero-effort miss (ZEM) based guidance laws in order to achieve
a small miss distance and for enhancing lethality either by
enabling a target detection device or by detonating a warhead at
the proper time, i.e., the point of closest approach to the
target.
[0003] There are known approaches such as that described in U.S.
Pat. No. 6,714,155B1 for "Method Of Passively Estimating An
Emitter's Position And Velocity Using Bearings-only Without
Requiring Observer Acceleration," where passive ranging is
performed with only angle measurements that do not require own-ship
observability maneuvers.
[0004] U.S. Pat. No. 3,789,410 for "Passive Ranging Technique"
describes a system for passively determining range to a target
based upon the rate of change in phase difference between two
signals received by widely separated pairs of antennas on an
aircraft. The signals received by each antenna are identical in
frequency but slightly different in phase due to the angle of
intercept. It is the rate of the change in phase difference that
yields the information required for passive ranging.
[0005] U.S. Pat. No. 5,282,013 for "Passive Ranging Technique For
Infrared Search And Track (IRST) Systems" teaches that atmospheric
transmittance and background spectral radiance is estimated from
available meteorological data and then, at each scan of a sequence
of consecutive scans, the contrast irradiance in the direction of a
target is measured as well as the azimuth and elevation of the
target. A target type is selected from a library of target types
that store signatures for the target types when considering the
measured contrast irradiance as well as the measure of the contrast
irradiance of a previous scan (if any). The range of the target is
then calculated considering the selected target type, the estimated
atmospheric parameters and the measured contrast irradiance.
[0006] What is needed is an improved passive ranging estimator for
providing guidance control in order to intercept the target.
SUMMARY
[0007] According to one aspect of the disclosure, a system for
guiding an interceptor toward a target using passive ranging
estimation comprises an EO/IR sensing device configured to detect
the target and output corresponding target azimuth information
target elevation information, target irradiance information, target
length information, target area information and respective validity
indicators; a passive ranging target state estimator, coupled to
the EO/IR sensing device and configured to generate interceptor
guidance information, comprising: a first Kalman Filter configured
to generate the interceptor guidance information as a function of
the target azimuth information, the target elevation information
and the target irradiance information; and a second Kalman Filter
configured to generate the interceptor guidance information as a
function of the target azimuth information, the target elevation
information and the target area information, wherein the first
Kalman Filter is operative to generate the interceptor guidance
information when the target irradiance information is indicated as
being valid and the second Kalman Filter is operative to generate
the interceptor guidance information when the target area
information is indicated as being valid, and wherein the target
area information and the target irradiance information are not
indicated as being valid at a same time; and an interceptor
guidance module, coupled to the passive ranging target state
estimator, configured to control movement of the interceptor as a
function of the generated interceptor guidance information.
[0008] In another aspect of the present disclosure, a method of
guiding an interceptor toward a target using passive ranging
estimation comprises: detecting the target with an EO/IR sensing
device and outputting corresponding target azimuth information,
target elevation information, target irradiance information, target
length information, target area information and respective validity
indicators; determining a range from the interceptor to the target
as a function of one or more of: the target azimuth information,
target elevation information, target irradiance information, target
length information, target area information and respective validity
indicators; generating interceptor guidance information by one of:
when the determined range is greater than a first predetermined
distance, implementing a first Kalman Filter configured to generate
the interceptor guidance information as a function of the target
azimuth information, the target elevation information and the
target irradiance information; or when the determined range is less
than or equal to the first predetermined distance, implementing a
second Kalman Filter configured to provide the interceptor guidance
information as a function of the target azimuth information, the
target elevation information and the target area information; and
controlling movement of the interceptor as a function of the
generated interceptor guidance information.
[0009] In another aspect of the present disclosure, a system for
guiding an interceptor toward a target using passive ranging
estimation comprises: an EO/IR sensing device configured to detect
the target with an EO/IR sensing device and output corresponding
target azimuth information, target elevation information, target
irradiance information, target length information, target area
information and respective validity indicators; a passive ranging
target state estimator coupled to the EO/IR sensing device
configured to determine a range from the interceptor to the target
as a function of one or more of: the target azimuth information,
target elevation information, target irradiance information, target
length information, target area information and respective validity
indicators; the passive ranging target state estimator further
configured to generate interceptor guidance information by one of:
when the determined range is greater than a first predetermined
distance, implementing a first Kalman Filter configured to generate
the interceptor guidance information as a function of the target
azimuth information, the target elevation information and the
target irradiance information; or when the determined range is less
than or equal to the first predetermined distance, implementing a
second Kalman Filter configured to provide the interceptor guidance
information as a function of the target azimuth information, the
target elevation information and the target area information; and
an interceptor guidance control module, coupled to the passive
ranging target state estimator, configured to control movement of
the interceptor as a function of the generated interceptor guidance
information.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] Various aspects of the disclosure are discussed below with
reference to the accompanying figures. It will be appreciated that
for simplicity and clarity of illustration, elements shown in the
drawings have not necessarily been drawn accurately or to scale.
For example, the dimensions of some of the elements may be
exaggerated relative to other elements for clarity or several
physical components may be included in one functional block or
element. Further, where considered appropriate, reference numerals
may be repeated among the drawings to indicate corresponding or
analogous elements. For purposes of clarity, not every component
may be labeled in every drawing. The Figures are provided for the
purposes of illustration and explanation and are not intended as a
definition of the limits of the disclosure. In the Figures:
[0011] FIG. 1 is a conceptual representation of an interceptor
pursuing a target;
[0012] FIG. 2 is a representation of the passive ranging
problem;
[0013] FIG. 3 is a functional block diagram of a system
incorporating a passive ranging target state estimator in
accordance with an aspect of the present disclosure;
[0014] FIG. 4 is a functional block diagram of an interceptor
incorporating the passive ranging target state estimator of FIG.
3;
[0015] FIG. 5 is a graph of a Kalman Frame corresponding to an
aspect of the present disclosure;
[0016] FIG. 6 is a representation of mapping Kalman Frame
Line-of-Sight (LOS) Angles to Seeker Boresight Errors;
[0017] FIG. 7 is a flowchart of a method of passive ranging
determination in accordance with an aspect of the present
disclosure; and
[0018] FIG. 8 is a block diagram of a computer system.
DETAILED DESCRIPTION
[0019] Details are set forth in order to provide a thorough
understanding of the aspects of the disclosure. It will be
understood by those of ordinary skill in the art that these may be
practiced without some of these specific details. In other
instances, well-known methods, procedures, components and
structures may not have been described in detail so as not to
obscure the aspects of the disclosure.
[0020] Generally, and as will be described in more detail below,
aspects of the present disclosure are directed to a system for
implementing passive ranging determinations. In one non-limiting
example, such a system can be used in a target intercept system
where the target is, for example, an exo-atmospheric ballistic,
non-maneuvering missile. The system may employ an EO/IR sensor to
determine target azimuth and elevation angles, target irradiance
and target area, as will be discussed in more detail below.
Extended Kalman Filter (EKF) techniques are used in an
implementation of the passive ranging of the present disclosure to
provide a more accurate time-to-go determination than previously
known.
[0021] In one approach, as described below, an aspect of the
present disclosure uses a dual Kalman Filter architecture. A first
Kalman Filter is implemented prior to endgame and a second Kalman
Filter is implemented thereafter. Generally, as known to one of
ordinary skill in the art, typically the "end game" is the phase in
which the "discrimination" algorithms have identified the specific
target to track and intercept. In other words, at this point, the
system is focused on the one object to pursue.
[0022] Thus, prior to endgame, the first Kalman Filter processes
target irradiance measurements to provide direction control toward
the target. The irradiance measurements of a target, however,
become poor and, therefore, provide less guidance accuracy, as the
distance to the target becomes smaller. Advantageously, in
accordance with an aspect of the present disclosure, after a target
image has become resolved, i.e., at endgame, a second Kalman Filter
is used to provide direction control by processing target area
measurements and, optionally, target length measurements, instead
of the target irradiance measurements. Thus, the guidance
information is more accurate as the distance to the target becomes
smaller in the endgame phase of target acquisition.
[0023] Advantageously, the dual Kalman Filter approach improves the
estimates of time-to-go by optimizing the on-board EO/IR sensor
measurements at the optimal times.
[0024] Further, aspects of the present disclosure improve on the
traditional "bearings-only" passive ranging approach by
incorporating irradiance, target area and, optionally, target
length, measurements into the state estimate. In addition, the
irradiance measurement bias is estimated and incorporated.
[0025] More effective passive ranging, per the present disclosure,
provides accurate time-to-go (t.sub.go) information to missile
systems, particularly intercept systems, during the terminal phase
of flight, thereby improving endgame performance, e.g., increasing
miss distance accuracy.
[0026] Generally, referring to FIG. 1, the intention of a defense
system is to have an interceptor 102, often a missile, intercept an
incoming target 104, also often a missile. As is known, the
interceptor 102 will include, among other elements, navigation
systems, a flight control system and a tracking system.
[0027] An issue with guiding an interceptor 102 on a collision
course with the target 104 is referred to as the "passive ranging
problem." As shown in FIG. 2, the interceptor 102, using an EO/IR
sensor, will make two different line-of-sight (LOS) measurements at
two different times, shown as being at angles .lamda..sub.1 and
.lamda..sub.2. An issue arises in that these two LOS measurements
could have come from either of the two trajectories 204, 208
depicted, noting that the range to the target 104 is ambiguous.
Thus, the target 104 can either be closer to the interceptor 102
and moving relatively slowly or be farther away from the
interceptor 102 and moving relatively quickly. One of ordinary
skill in the art will understand that an infinite number of tracks
can be generated by using only the LOS measurement angle sequence
depicted in FIG. 2.
[0028] In one aspect of the present disclosure, representing an
improved solution to the passive ranging problem, an improved
passive ranging algorithm is implemented in a system, for example,
a missile, employing an EO/IR sensor. More specifically, the system
implements Kalman Filters that operate on target irradiance, target
length, and target area measurements to improve over the
traditional "bearings only" passive ranging approach that only uses
target azimuth and elevation angle measurements. The Kalman Filters
are utilized based on the phase of flight of the interceptor 102,
i.e., how close to the target 104 or endgame, as will be described
in more detail below.
[0029] Generally, as shown in FIG. 3, in accordance with an aspect
of the present disclosure, an EO/IR sensor 302 provides signals
representative of the target 104 to a signal processor 304. As
known, the EO/IR sensor 302 comprises a plurality of sensing
pixels. The signal processor 304, per known operations, processes
the received signals from the EO/IR sensor 302. The signal
processor 304 provides target azimuth information
(.epsilon..sub.az), target elevation information
(.epsilon..sub.el), target irradiance information (J), target
length information (L) and target area information (A). The signal
processor 304 also outputs a corresponding validity signal
indicating the validity of each of the aforementioned information
signals. The EO/IR sensor 302 and signal processor 304 are shown as
separate elements for explanatory purposes only and one of ordinary
skill in the art will understand that they may be combined into a
single EO/IR sensing device.
[0030] When the target 104 is relatively far away from the
interceptor 102 the EO/IR sensor 302 will detect the target 104 as
a point source in that only one pixel of the sensor 302 is "lit
up." In this situation, only the target azimuth information
(.epsilon..sub.az), target elevation information (.epsilon..sub.el)
and target irradiance information (J) will be valid and identified
as such. The remaining information signals will be indicated as not
valid.
[0031] When the target 104 is relatively closer to the interceptor
104, and the signal processor 304 can validate a resolved image,
the target azimuth information (.epsilon..sub.az), the target
elevation information (.epsilon..sub.el), target length information
(L) and target area information (A) are provided and indicated as
being valid while the target irradiance information (J) is
indicated as being not valid. In other words, the signal processor
304 indicates when the target 104 is detected as being a point
source or that a resolved image of the target 104 has been
obtained.
[0032] As is known, the EO/IR sensor 302 always provides irradiance
and angle information. Thus, from relatively far away, as only one
pixel is "lit up" then the target 104 presents as a point source.
Once the target 104 is closer to the interceptor 102, then the
target 104 becomes resolved and "fills up" more than one pixel. At
this point, the sensor 302 provides valid angle, area and length
measurements.
[0033] In one approach, the target image becoming resolved is
defined as when the target projected area is greater than one pixel
although one of ordinary skill in the art will understand that a
different threshold number of pixels can be chosen. This is related
to the time-to-go (t.sub.go) and the physical size of the target
104. For example, a very large target, such as an aircraft carrier,
will become resolved at a larger time-to-go (t.sub.go) than a small
target, such as a jet ski. Although it is highly unlikely that
either of these two vehicles would be on an exo-atmospheric
ballistic, non-maneuvering approach as the target 104 is
contemplated herein.sup.1. .sup.1 The inventors note that there may
be other issues to deal with if either an aircraft carrier or a jet
ski were approaching in such a fashion.
[0034] A passive ranging target state estimator 306, in accordance
with an aspect of the present disclosure, receives the output
information from the signal processor 304. The passive ranging
target state estimator 306 includes a first Kalman Filter (KF) 308
that operates as a Point Source Passive Ranging Kalman Filter and a
second Kalman Filter 310 that operates as a Resolved Image Passive
Ranging Kalman Filter.
[0035] Accordingly, when the signal processor 304 indicates that
the target 104 is far enough away that it appears as a point
source, then the first KF 308 processes the target azimuth
information (.epsilon..sub.az), (target elevation information
(.epsilon..sub.el), and target irradiance information (J) to
provide the azimuth line-of sight rate ({dot over
(.lamda.)}.sub.az) and elevation line-of-sight rate ({dot over
(.lamda.)}.sub.el), a range rate ({dot over (r)}) and a time-to-go
value (t.sub.go) for use in guiding the interceptor 102 toward the
target 104.
[0036] When the signal processor 304 indicates that the target 104
is close enough to resolve an image, then the second KF 308
processes the target azimuth information (.epsilon..sub.az), target
elevation information (.epsilon..sub.el), the target area
information A and, optionally, the target length information L, to
provide the azimuth line-of sight rate and elevation line-of-sight
rate {dot over (.lamda.)}az, {dot over (.lamda.)}.sub.el the range
rate of change ({dot over (r)}) and the time-to-go value (t.sub.go)
for use in guiding the interceptor 102 toward the target 104.
[0037] The azimuth and elevation line-of-sight rates ({dot over
(.lamda.)}), the range rate ({dot over (r)}) and the time-to-go
value (t.sub.go) are parameters that are needed for basic
Proportional Navigation Guidance or basic Zero-Effort Miss Guidance
used by exo-atmospheric interceptors, or missiles, to handle
ballistic targets, as is known to one of ordinary skill in the
art.
[0038] Thus, the presently described system determines when the
range from the interceptor 102 to the target 104 is less than or
equal to a predetermined distance, i.e., a distance where the EO/IR
sensor 102 is no longer detecting it as a point-source. At that
point, and thereafter, the second Kalman Filter is used to generate
the guidance information.
[0039] A system 400 incorporating the state estimator 306 will now
be discussed with respect to FIG. 4. Generally, the system 400 is
provided within the interceptor 102 although it is envisioned that
some components, and their respective functions, may be provided
from outside of the interceptor 102.
[0040] As discussed above, the EO/IR sensor 302 detects the target
dynamics, i.e., characteristics, of the target 104 and provides
information to the signal processor 304 which provides the
information to the state estimator 306.
[0041] The system 400 includes a known inertial measurement
unit/global positioning system (IMU/GPS) module 402 coupled to a
navigation unit 404. In addition, a known guidance module 406, a
known autopilot module 408, at least one known actuator 412 and a
missile dynamics module 416 are included. Generally, IMU/GPS module
402, navigation unit 404, guidance module 406, autopilot module
408, actuator 412 and missile dynamics module 416 are components
for operating the interceptor missile 102 but are not, otherwise,
germane to the inventive aspects of the present disclosure.
[0042] The IMU/GPS module 402 and the EO/IR sensor 302 receive
inputs from the missile dynamics module 416. The IMU/GPS module 402
provides missile position, velocity, acceleration, attitude and the
associated covariances to the state estimator 306. As above, the
state estimator 306 provides the control parameters to the guidance
module 406 which provides data to the autopilot module 408 to then
control the actuator module 412. The missile dynamics module 416
receives information from the actuator module 412 and the system
400 operates in a feedback loop.
[0043] As set forth above, the state estimator 306 implements the
first and second Kalman Filters 308, 310.
[0044] The following is a discussion of the Kalman Filters where it
should be noted that, in the present disclosure the following
assumptions are present: the target is ballistic and
non-maneuvering; any engagement has a short time of flight; the
system is operating within a linear collision triangle engagement
geometry; the time-to-go t.sub.go has a slope of -1; the change in
closing velocity is very small ({umlaut over (R)}.apprxeq.0); and
the target intensity is constant.
[0045] Initially, an overview of the Kalman frame for passive
ranging will be set forth here.
[0046] The Kalman frame, as shown in FIG. 5, is an "instantaneous"
inertial reference frame to be used by the passive ranging
algorithm described herein. An origin is initialized to an estimate
of the interceptor 102 position taken from the navigation module
404.
[0047] After initialization, the Kalman frame is updated in order
to translate with the interceptor 102 and maintain its rotation
relative to the Earth-Centered Inertial (ECI) frame. The positive X
axis of the Kalman frame lies on the vector from the interceptor's
position to the interceptor's best estimate of the target's
position. The positive Y axis is defined as the cross-product of
the positive X axis in the Kalman frame and the missile position
vector in the Earth-centered, Earth-fixed (ECEF) frame ([Kalman
frame X-axis] X [ECEF missile position vector]). The positive Z
axis is defined as the cross-product of the positive X and Y axes
in the Kalman frame, thus completing a right-handed orthogonal
coordinate system.
[0048] The (i, j, k) unit vectors are along the (x, y, z) axes,
respectively, of a certain coordinate frame. So (i.sup.ECEF,
j.sup.ECEF, k.sup.ECEF) are unit vectors along the (x, y, z) axes
of the ECEF frame and likewise for the Kalman frame. The ECI frame
is the same frame as the ECEF frame at time=0. For t>0, the ECEF
frame rotates but the ECI frame does not.
[0049] Accordingly, prior to an image of the target 104 becoming
resolved, i.e., prior to endgame, the first Kalman Filter 308
incorporates target irradiance measurements J, which obeys the
following physics where the irradiance J of an object at a distance
R and intensity I is given by:
J = I R 2 Eq . 1 ##EQU00001##
[0050] For Kalman filtering purposes, the derivative of Eq. 1 is
also needed:
d dt ( J ) = j = I . R 2 - 2 I R 2 R . R = I . R 2 - 2 J R . R Eq .
2 ##EQU00002##
[0051] For a constant intensity model, =0. Therefore, any changes
in irradiance are attributed to range closure. Furthermore, for a
constant closing velocity condition ({umlaut over (R)}.apprxeq.0,
R.apprxeq.-{dot over (R)}t.sub.go), Eq. 2 can also be written
as:
J . = 2 J 1 t go Eq . 3 ##EQU00003##
[0052] Advantageously, although a constant intensity target model
is assumed, the algorithm achieves accurate t.sub.GO estimates even
when presented with a non-constant intensity target.
[0053] After the target image becomes resolved (at endgame), the
target irradiance measurements no longer obey Eq. 1
[0054] Thus, in order to maintain accurate t.sub.GO estimates at
endgame, the second Kalman Filter 310 is used to incorporate the
area measurement and, optionally, the target length.
[0055] Assuming a linear engagement at endgame, which is true if
the interceptor 102 is on a collision course with the target 104,
then the following relates measured target length and area at two
points in time:
L = R o L o R Eq . 4 A = R o 2 A o R 2 Eq . 5 ##EQU00004##
[0056] For Kalman filtering purposes, the derivatives of Eq. 4 and
5 are also needed:
d dt ( L ) = L . = - R o L o R . R 2 = L t go Eq . 6
##EQU00005##
d dt ( A ) = A . = - 2 R o 2 A o R . R 3 = 2 A t go Eq . 7
##EQU00006##
[0057] The equations of motion for the first Kalman Filter 308 are
as follows:
x .fwdarw. = [ .lamda. az .lamda. . az .lamda. el .lamda. . el t go
r . J J b ] T ##EQU00007## x .fwdarw. . = [ .lamda. . az .lamda. az
.lamda. . el .lamda. el t . go r J . J . b ] = [ .lamda. . az 2
.lamda. . az t go - .eta. M .perp. , az r . t go .lamda. . el 2
.lamda. . el t go - .eta. M .perp. , el r . t go - 1 0 2 J 1 t go 0
] = [ x 2 2 x 2 x 5 - .eta. M .perp. , az x 6 x 5 x 4 2 x 4 x 5 -
.eta. M .perp. , el x 6 x 5 - 1 0 2 x 7 1 x 5 0 ]
##EQU00007.2##
[0058] The equations of motion for the second Kalman Filter 310 are
as follows:
x .fwdarw. = [ .lamda. az .lamda. . az .lamda. el .lamda. . el t go
r . L A ] T ##EQU00008## x .fwdarw. . = [ .lamda. . az .lamda. az
.lamda. . el .lamda. el t . go r L . A . ] = [ .lamda. . az 2
.lamda. . az t go - .eta. M .perp. , az r . t go .lamda. . el 2
.lamda. . el t go - .eta. M .perp. , el r . t go - 1 0 L t go 2 A t
go ] = [ x 2 2 x 2 x 5 - .eta. M .perp. , az x 6 x 5 x 4 2 x 4 x 5
- .eta. M .perp. , el x 6 x 5 - 1 0 x 7 1 x 5 2 x 8 1 x 5 ]
##EQU00008.2##
[0059] In order to better understand aspects of the present
disclosure, a discussion of the derivation of the Kalman Filters
and related state equations is provided.
[0060] Common Derivations
[0061] Line of Sight Rate and its Derivative
[0062] In order to obtain the state equations for a Line of
Sight/Line of Sight Rate (LOS/LOSR) filter, the second derivative
of the equation for arc length is taken to obtain the equation for
tangential acceleration.
S=.lamda.R Eq. A1
{umlaut over (S)}={umlaut over (.lamda.)}R+2{dot over
(.lamda.)}{dot over (R)}+.lamda.{umlaut over (R)} Eq. A2
[0063] Tangential acceleration M is equal to the total acceleration
(from both interceptor and target) perpendicular to the LOS.
.DELTA..eta..sub..perp..sub.LOS={umlaut over (.lamda.)}R+2{dot over
(.lamda.)}{dot over (R)}+.lamda.{umlaut over
(R)}=n.sub.M.sub..perp.-.eta..sub.T.sub..perp. Eq. A3
[0064] If it is assumed that the target is non-maneuvering
(.eta..sub.T.sub..perp..apprxeq.0), and the change in closing
velocity is very small ({umlaut over (R)}.apprxeq.0), then:
.lamda. = - 2 .lamda. . R . R + .eta. M .perp. R Eq . A4
##EQU00009##
[0065] As it was assumed that the change in closing velocity is
negligible, then the following holds:
R=-{dot over (R)}T.sub.go Eq. A5
[0066] and substituting Eq. A5 into Eq. A4 provides:
.lamda. = - 2 .lamda. . T go + .eta. M .perp. R . T go Eq . A6
##EQU00010##
[0067] True Irradiance And Its Derivative
[0068] The true irradiance of an object at a distance R and
intensity I is given by:
J = I R 2 Eq . A7 ##EQU00011##
[0069] Taking the time derivative of Eq. A7 yields:
d dt ( J ) = J . = I . R 2 - 2 I R 2 R . R = I . R 2 - 2 J R . R Eq
. A8 ##EQU00012##
[0070] For a constant intensity model, =0. Therefore, any changes
in irradiance are attributed to range closure. Furthermore, for a
constant closing velocity condition ({umlaut over (R)}.apprxeq.0,
R.apprxeq.-{dot over (R)}t.sub.go), Eq. A8 can also be written
as:
J . = 2 J 1 t go Eq . A9 ##EQU00013##
[0071] True Area And Its Derivative
[0072] The current area of an object at a distance R as it relates
to a previous area and distance is given by:
A = R o 2 A o R 2 Eq . A10 ##EQU00014##
[0073] Taking the time derivative of Eq. A10 yields:
d dt ( A ) = A . = - 2 R o 2 A o R . R 3 = 2 A t go Eq . A11
##EQU00015##
[0074] True Length and its Derivative
[0075] The current length of an object at a distance R as it
relates to a previous length and distance is given by:
L = R o L o R Eq . A12 ##EQU00016##
[0076] and taking the time derivative of Eq. A12 yields:
d dt ( L ) = L . = - R o A o R . R 2 = L t go Eq . A13
##EQU00017##
[0077] Measurement Models
[0078] Irradiance Measurement Model
[0079] The irradiance measurement can be summarized as:
J.sub.meas=(1+J.sub.SF)J+J.sub.b+J.sub.RN Eq. B1
[0080] where J.sub.SF is the irradiance scale factor error, J.sub.b
is the irradiance bias error, and J.sub.RN is the irradiance random
noise.
[0081] Mapping Kalman Frame LOS Angles to Seeker Boresight
Errors
[0082] With reference to FIG. 6, the unit vector to the target in
the seeker frame as a function of the boresight errors
.epsilon..sub.az and .epsilon..sub.el (assuming small angles)
is:
u .fwdarw. S = 1 1 + tan ( az ) 2 + tan ( el ) 2 [ 1 tan ( az ) -
tan ( el ) ] .apprxeq. [ 1 az - el ] Eq . B2 ##EQU00018##
[0083] The tracker performs state estimation in the inertial Kalman
Frame. The missile-to-target unit vector in the Kalman Frame as a
function of the LOS angles .lamda..sub.az and .lamda..sub.el
(assuming small angles) is:
u .fwdarw. K = 1 1 + tan ( .lamda. az ) 2 + tan ( .lamda. el ) 2 [
1 tan ( .lamda. az ) - tan ( .lamda. el ) ] .apprxeq. [ 1 .lamda.
az - .lamda. el ] Eq . B3 ##EQU00019##
[0084] and the Kalman-to-Seeker DCM is defined as:
C K S = [ c 11 c 12 c 13 c 21 c 22 c 23 c 31 c 32 c 33 ] Eq . B4
##EQU00020##
[0085] To rotate the missile-to-target position vector from the
Kalman frame to the seeker frame:
u .fwdarw. S = C K S u .fwdarw. K [ 1 az - el ] .ident. z = C K S [
1 .lamda. az - .lamda. el ] .ident. K = [ c 11 + c 12 .lamda. az -
c 13 .lamda. el c 21 + c 22 .lamda. az - c 23 .lamda. el c 31 + c
32 .lamda. az - c 33 .lamda. el ] Eq . B5 ##EQU00021##
[0086] and the linearized observation matrix is then given by:
H = [ .differential. az .differential. .lamda. ax .differential. az
.differential. .lamda. el .differential. el .differential. .lamda.
ax .differential. el .differential. .lamda. el ] = [ c 22 - c 23 -
c 32 c 33 ] Eq . B6 ##EQU00022##
[0087] Modified Irradiance Coupled Los/Los Rate Passive Ranging
[0088] Kalman Filter State Vector (Prior to Image Resolution)
[0089] This filter formulation couples various states (LOS, LOS
rate, t.sub.go, range rate and irradiance) to maximize
observability for passive ranging and this state vector is
expressed as:
{right arrow over (x)}=[.lamda..sub.az{dot over
(.lamda.)}.sub.az.lamda..sub.el{dot over
(.lamda.)}.sub.elt.sub.go{dot over (r)}JJ.sub.b].sup.T Eq. C1a
where J.sub.b is the irradiance bias.
[0090] Now, taking the derivative of Eq. C1a (and using Eq. A6 and
Eq. A9) results in:
f ( x .fwdarw. , u ) = x .fwdarw. . = [ .lamda. . az .lamda. ax
.lamda. . el .lamda. el t . go r j . j . b ] = [ .lamda. . az 2
.lamda. . az t go - .eta. M .perp. , az r . t go .lamda. . el 2
.lamda. . el t go - .eta. M .perp. , el r . t go - 1 0 2 j 1 t go 0
] = [ x 2 2 x 2 x 5 - .eta. M .perp. , az x 6 x 5 x 4 2 x 4 x 5 -
.eta. M .perp. , el x 6 x 5 - 1 0 2 x 7 1 x 5 0 ] Eq . C2a
##EQU00023##
[0091] Kalman Filter State Vector (Post Image Resolution)
[0092] This filter formulation couples various states (LOS, LOS
rate, t.sub.go, range rate, target length and target area) to
maximize observability for passive ranging and this state vector is
expressed as:
{right arrow over (x)}=[.lamda..sub.az{dot over
(.lamda.)}.sub.az.lamda..sub.el{dot over
(.lamda.)}.sub.elt.sub.go{dot over (r)}LA].sup.T Eq. C1b
where J.sub.b is the irradiance bias.
[0093] Now, taking the derivative of Eq. C1b (and using Eq. A6 and
Eq. A9) results in:
f ( x .fwdarw. , u ) = x .fwdarw. . = [ .lamda. . az .lamda. ax
.lamda. . el .lamda. el t . go r L . A . ] = [ .lamda. . az 2
.lamda. . az t go - .eta. M .perp. , az r . t go .lamda. . el 2
.lamda. . el t go - .eta. M .perp. , el r . t go - 1 0 L t go A t
go ] = [ x 2 2 x 2 x 5 - .eta. M .perp. , az x 6 x 5 x 4 2 x 4 x 5
- .eta. M .perp. , el x 6 x 5 - 1 0 x 7 1 x 5 2 x 8 1 x 5 ] Eq .
C2b ##EQU00024##
[0094] Linearized State Dynamics Matrix and State Transition Matrix
(Prior to Image Resolution)
[0095] The linearized state dynamics matrix is given by:
F = .differential. f ( x .fwdarw. , u .fwdarw. ) .differential. x
.fwdarw. = [ ? ] = [ 0 1 0 0 0 0 0 0 0 ? 0 0 ? ? 0 0 0 0 0 1 0 0 0
0 0 0 0 ? ? ? 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ? 0 ? 0 0
0 0 0 0 0 0 0 ] ? indicates text missing or illegible when filed Eq
. C3a ##EQU00025##
and the remaining non-zero terms of the linearized state dynamics
matrix are given by:
.differential. .lamda. az .differential. x 2 = 2 x 5 .differential.
.lamda. el .differential. x 5 = - 2 x 4 x 5 2 + .eta. M .perp. , el
x 6 x 5 2 .differential. .lamda. az .differential. x 5 = - 2 x 2 x
5 2 + .eta. M .perp. , az x 6 x 5 2 .differential. .lamda. el
.differential. x 6 = .eta. M .perp. , el x 6 2 x 5 .differential.
.lamda. az .differential. x 6 = .eta. M .perp. , az x 6 2 x 5
.differential. J . .differential. x 5 = - 2 x 7 x 5 2
.differential. .lamda. el .differential. x 4 = 2 x 5 .differential.
J . .differential. x 7 = 2 x 5 Eq . C4a ##EQU00026##
[0096] A two term Taylor series expansion is used to obtain the
state transition matrix:
.PHI..sub.k.apprxeq.I+FT.sub.s Eq. C5a
where T.sub.s is the sampling time.
[0097] Linearized State Dynamics Matrix And State Transition Matrix
(Post Image Resolution)
[0098] The linearized state dynamics matrix is given by:
F = .differential. f ( x .fwdarw. , u .fwdarw. ) .differential. x
.fwdarw. = [ ? ] = [ 0 1 0 0 0 0 0 0 0 ? 0 0 ? ? 0 0 0 0 0 1 0 0 0
0 0 0 0 ? ? ? 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ? 0 ? 0 0
0 0 0 ? 0 0 ? ] ? indicates text missing or illegible when filed Eq
. C3a ##EQU00027##
[0099] The remaining non-zero terms of the linearized state
dynamics matrix are given by:
.differential. .lamda. az .differential. x 2 = 2 x 5 .differential.
.lamda. el .differential. x 5 = - 2 x 4 x 5 2 + .eta. M .perp. , el
x 6 x 5 2 .differential. .lamda. az .differential. x 5 = - 2 x 2 x
5 2 + .eta. M .perp. , az x 6 x 5 2 .differential. .lamda. el
.differential. x 6 = .eta. M .perp. , el x 6 2 x 5 .differential. A
. .differential. x 5 = - 2 x 8 x 5 2 .differential. .lamda. az
.differential. x 6 = .eta. M .perp. , az x 6 2 x 5 .differential. L
. .differential. x 5 = - x 7 x 5 2 .differential. A .
.differential. x 8 = 2 x 5 .differential. .lamda. el .differential.
x 4 = 2 x 5 .differential. L . .differential. x 7 = 1 x 5 Eq . C4a
##EQU00028##
[0100] A two term Taylor series expansion is used to obtain the
state transition matrix:
.PHI..sub.k.apprxeq.I+FT.sub.s Eq. C5a
where T.sub.s is the sampling time.
[0101] Process Noise Matrix
[0102] The continuous process noise matrix is given by:
w .fwdarw. = [ w 1 w 2 w 3 w 4 w 5 w 6 w 7 w 8 ] T Q = E [ w _ w _
T ] Eq . C6 ##EQU00029##
[0103] The discrete process noise matrix is given by:
Q k = .intg. 0 T z .PHI. ( .tau. ) Q .PHI. T ( .tau. ) d .tau. Eq .
C7 ##EQU00030##
[0104] Measurements, Predicted Measurements, and Linearized
Observation Matrix (Prior to Image Resolution)
[0105] The measurement vector is given by:
{right arrow over (z)}=[ .sub.az .sub.elJ].sup.T Eq. C8a
[0106] The predicted measurements in terms of the state vector are
(refer to Eqs. B1, B4 and B5):
h ( x .fwdarw. ^ k | k - 1 ) = [ ^ az ^ el J ^ ] T ^ az = c 21 + c
22 .lamda. az - c 23 .lamda. el ^ el = - ( c 31 + c 32 .lamda. az -
c 33 .lamda. el ) J ^ = J + J b Eq . C9a ##EQU00031##
where the c.sub.ij's are the components of the Kalman-to-Seeker DCM
(see Eq. B4).
[0107] The linearized observation matrix is then given by:
H = .differential. h ( x .fwdarw. ^ k | k - 1 ) .differential. x
.fwdarw. ^ k | k - 1 = [ ? ] = [ c 22 0 - c 23 0 0 0 0 0 - c 32 0 c
33 0 0 0 0 0 0 0 0 0 0 0 1 1 ] ? indicates text missing or
illegible when filed Eq . C10a ##EQU00032##
[0108] Measurements, Predicted Measurements, and Linearized
Observation Matrix (Post Image Resolution)
[0109] The measurement vector is given by:
{right arrow over (z)}=[ .sub.az .sub.elLA].sup.T Eq. C8b
[0110] The predicted measurements in terms of the state vector are
(referring to Eqs. B1, B4 and B5):
h({circumflex over ({right arrow over
(x)})}.sub.k|k-1)=[.epsilon..sub.az.epsilon..sub.el{circumflex over
(L)}A].sup.T
.epsilon..sub.az=c.sub.21+c.sub.22.lamda..sub.az-c.sub.23.lamda..sub.el
{circumflex over
(.epsilon.)}.sub.el=-(c.sub.31+c.sub.32.lamda..sub.az-c.sub.33.lamda..sub-
.el)
{circumflex over (L)}=L
A=A
where the c.sub.ij's are the components of the Kalman-to-Seeker DCM
(see Eq. B4).
[0111] The linearized observation matrix is given by:
H = .differential. h ( x .fwdarw. ^ k | k - 1 ) .differential. x
.fwdarw. ^ k | k - 1 = [ ? ] = [ c 22 0 - c 23 0 0 0 0 0 - c 32 0 c
33 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 ] ? indicates text
missing or illegible when filed Eq . C10b ##EQU00033##
[0112] EKF Propagate/Update Equations
[0113] The state equations are propagated by any suitable
integration method such as Runge-Kutta or Euler integration (Euler
integration shown below). Thus the state vector x is propagated
according to:
x .fwdarw. ^ k | k - 1 = x .fwdarw. ^ k - 1 | k - 1 + .intg. t k t
k - 1 x .fwdarw. . ^ ( .tau. ) d .tau. .apprxeq. x .fwdarw. ^ k - 1
| k - 1 + x .fwdarw. . ^ k - 1 | k - 1 T 5 Eq . C11
##EQU00034##
[0114] The covariance matrix P is propagated according to:
P.sub.k|k-1=.PHI..sub.kP.sub.k-1|k-1.PHI..sub.k.sup.T+Q.sub.k Eq.
C12
[0115] The measurement residual and corresponding covariance are
given by:
{tilde over ({right arrow over (y)})}.sub.k={right arrow over
(z)}.sub.k-h({circumflex over ({right arrow over (x)})}.sub.k|k-1)
Eq. C13
[0116] It should be noted that the components on the right side of
Eq. C13 have to be time-aligned. The state vector has to be
propagated to the "time of validity" (TOV) of the measurement z.
Generally, when a sensor provides a measurement, it also provides a
TOV, i.e., a "time stamp," indicating the time at which the
measurement was made in order to be used to indicate when it is
valid.
S.sub.k=H.sub.kP.sub.k|k-1H.sub.k.sup.T+R.sub.k Eq. C4
[0117] The optimal Kalman gain is given by:
K.sub.k=P.sub.k|k-1H.sub.k.sup.TS.sub.k.sup.-1 Eq. C15
[0118] Lastly, the updated state vector and corresponding
covariance are given by:
{circumflex over ({right arrow over (x)})}.sub.k|k={circumflex over
({right arrow over (x)})}.sub.k|k-1+K.sub.k{tilde over ({right
arrow over (y)})}.sub.k Eq. C16
P.sub.k|k=(I-K.sub.kH.sub.k)P.sub.k|k-1=(I-K.sub.kH.sub.k)P.sub.k|k-1(I--
K.sub.kH.sub.k).sup.T+K.sub.kR.sub.kK.sub.k.sup.T Eq. C17
[0119] A method 700 of passive ranging estimation, implemented in
the passive ranging target state estimator 306, and in accordance
with an aspect of the present disclosure, is presented in FIG. 7.
Once started, step 702, the state vector x and covariance matrix P
are initialized, step 704. At step 706, a determination is made as
to whether the target 104 has been intercepted. If interception has
occurred, then control passes to the end, step 708. Effectively, at
"interception" both the interceptor 102 and target 104 are
destroyed. As the exemplary embodiment is implemented onboard the
interceptor 102, the "yes" branch from step 706 would not occur but
is included for completeness.
[0120] If the target 104 has not been intercepted, control passes
to step 710 where the Jacobian matrix F, per Eqs. C3a and C4a
above; the state transition matrix .PHI., per Eq. C5a above; and
the process noise matrix Q, per Eqs. C6 and C7 above, are computed.
Subsequently, at step 716, the state vector x and the covariance
matrix P are propagated per Eq. C11 and Eq. C12, respectively.
[0121] As set forth above, the passive ranging target state
estimator 306 receives output information from the signal processor
304 that includes indications of validity. Accordingly, at step
718, a determination is made as to the validity of the received
angle measurements. If not valid, control passes to step 722. If
the angle measurements are valid, control passes to step 720 where
each of the state vector x, per Eqs. C8a-C10a, and the covariance
matrix P, per Eqs. C13-C17, is updated with valid angle
measurements, i.e., the first Kalman Filter is implemented.
[0122] At step 722, a determination is made as to the validity of
the received irradiance measurements. If not valid, indicating that
the target 103 is too close, i.e., not a point source, then control
passes to step 726. If the received irradiance measurements are
valid, i.e., far enough away to still be a point source, control
passes to step 724 where each of the state vector x and the
covariance matrix P is updated with valid irradiance measurements,
i.e., the first Kalman Filter is implemented.
[0123] A determination is then made at step 726 as to the validity
of the received area measurements. If not valid, i.e., a point
source, control passes to step 730. If the area measurements are
valid, i.e., close enough to be a resolved image, control passes to
step 728 where each of the state vector x and the covariance matrix
P is updated with valid area measurements, i.e., the second Kalman
Filter is implemented.
[0124] If the length measurements are being used, an option as
discussed above, and if determined valid at step 730, i.e., close
enough to be a resolved image, then control passes to step 732
where each of the state vector x and the covariance matrix P is
updated with valid length measurements, i.e., the second Kalman
Filter is implemented. If the length measurements are not valid,
then control passes back to step 706.
[0125] While the present disclosure uses an example of a missile
defense system to describe its operation, the present system need
not be used just for intercepting or defensive purposes and is,
therefore, not to be construed as so limited.
[0126] Various implementations of the above-described systems and
methods described may be provided in digital electronic circuitry,
in computer hardware, firmware, and/or software. An implementation
can be as a computer program product, e.g., a computer program
tangibly embodied in an information carrier. The implementation
can, for example, be in a machine-readable storage device, for
execution by, or to control the operation of, data processing
apparatus. The implementation can, for example, be a programmable
processor, a computer, and/or multiple computers.
[0127] The above-described implementations generally depict a
computer implemented system employing at least one processor or
processing unit executing program steps out of at least one memory
to obtain the functions herein described. It should be recognized
that the presently described methods may be implemented via the use
of software, firmware or alternatively, implemented as a dedicated
hardware solution such as an FPGA (field programmable gate array)
and/or an ASIC (application specific integrated circuit). Modules,
subroutines, and software agents can refer to portions of the
computer program, the processor or processing unit, the special
circuitry, software, and/or hardware that implements that
functionality.
[0128] Referring to FIG. 8, the target state estimator 306 may be
implemented as a system that may comprise a CPU 6404, RAM 6408, ROM
6412, a mass storage device 6416, for example, a disk drive, an I/O
interface 6420 to couple to, for example, display, keyboard/mouse
or touchscreen, or the like and a network interface module 6424.
All of these modules are in communication with each other through a
bus 6428. The CPU 6404 executes an operating system to operate and
communicate with these various components.
[0129] A computer program can be written in any form of programming
language, including compiled and/or interpreted languages, and the
computer program can be deployed in any form, including as a
stand-alone program or as a subroutine, element, and/or other unit
suitable for use in a computing environment.
[0130] As utilized, the one or more processing units may represent,
for example, a CPU-type processing unit, a GPU-type processing
unit, a field-programmable gate array ("FPGA"), digital signal
processor(s) ("DSP"), or other hardware logic components that may,
in some instances, be driven by a central processing unit
("CPU").
[0131] The computer-readable medium may store instructions
executable by the one or more processing units and may include
computer storage media and/or communication media. Computer storage
media may include one or more of volatile memory, nonvolatile
memory, and/or other persistent and/or auxiliary computer storage
media.
[0132] It is to be understood that the disclosure is not limited in
its application to the details of construction and the arrangement
of the components set forth herein or illustrated in the drawings
as it is capable of implementations or of being practiced or
carried out in various ways. Also, it is to be understood that the
phraseology and terminology employed herein are for the purpose of
description only and should not be regarded as limiting.
[0133] Certain features, which are, for clarity, described in the
context of separate implementations, may also be provided in
combination in a single implementation. Conversely, various
features, which are, for brevity, described in the context of a
single implementation, may also be provided separately or in any
suitable sub-combination.
[0134] The present disclosure is illustratively described in
reference to the disclosed implementations. Various modifications
and changes may be made to the disclosed implementations by persons
skilled in the art without departing from the scope of the present
disclosure as defined in the appended claims.
* * * * *