U.S. patent application number 17/194797 was filed with the patent office on 2022-09-08 for systems and methods for simulating performance of receivers in realistic interference scenarios.
This patent application is currently assigned to The Aerospace Corporation. The applicant listed for this patent is The Aerospace Corporation. Invention is credited to David W. Allen.
Application Number | 20220283315 17/194797 |
Document ID | / |
Family ID | 1000006149085 |
Filed Date | 2022-09-08 |
United States Patent
Application |
20220283315 |
Kind Code |
A1 |
Allen; David W. |
September 8, 2022 |
SYSTEMS AND METHODS FOR SIMULATING PERFORMANCE OF RECEIVERS IN
REALISTIC INTERFERENCE SCENARIOS
Abstract
Systems and methods for simulating performance of receivers in
realistic interference scenarios are provided herein. A method for
simulating the performance of a receiver may include (a) generating
a set of observables that a receiver in a truth state would ideally
see; (b) adding interference to the set of observables to generate
a set of corrupted observables; and (c) generating a position,
navigation, and timing (PNT) solution using the set of corrupted
observables.
Inventors: |
Allen; David W.; (Fairfax,
VA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
The Aerospace Corporation |
El Segundo |
CA |
US |
|
|
Assignee: |
The Aerospace Corporation
El Segundo
CA
|
Family ID: |
1000006149085 |
Appl. No.: |
17/194797 |
Filed: |
March 8, 2021 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01S 19/23 20130101;
G01S 19/21 20130101 |
International
Class: |
G01S 19/23 20060101
G01S019/23; G01S 19/21 20060101 G01S019/21 |
Claims
1. A method for simulating the performance of a receiver, the
method comprising: (a) generating a set of observables that a
receiver in a truth state would ideally see; (b) adding
interference to the set of observables to generate a set of
corrupted observables; and (c) generating a position, navigation,
and timing (PNT) solution using the set of corrupted
observables.
2. The method of claim 1, wherein the truth state comprises one or
more of a position, geometry, kinematics, and dynamics of the
receiver.
3. The method of claim 2, wherein the truth state further comprises
one or more of a position, geometry, kinematics, and dynamics of
one or more transmitters.
4. The method of claim 1, wherein the truth state comprises a
previous PNT solution of the receiver.
5. The method of claim 1, wherein generating the set of observables
comprises applying a signal transmission model to the truth
state.
6. The method of claim 5, wherein the signal transmission model
comprises a global positioning system (GPS) constellation model, a
Galileo constellation model, a GLONASS constellation model, or a
Doppler orbitography and radiopositioning integrated by satellite
(DORIS) constellation model.
7. The method of claim 1, wherein the set of observables comprises
one or more of: pseudorange, range, time-delay-of-arrival (TDOA),
navigation data, carrier phase, code phase, Doppler, and
signal-to-noise ratio (SNR).
8. The method of claim 1, wherein adding interference to the set of
observables comprises applying a signal disruption model to the set
of observables.
9. The method of claim 8, wherein the signal disruption model
applies one or more errors selected from the group consisting of
simulated unintentional interference, jamming, and spoofing, to the
set of observables.
10. The method of claim 9, wherein one or more of the errors are
scaled or correlated based on the truth state.
11. The method of claim 9, further comprising validating the errors
against actual receiver hardware.
12. The method of claim 1, wherein generating the PNT solution
comprises applying a receiver model to the set of corrupted
observables.
13. The method of claim 12, further comprising: outputting the PNT
solution to a simulation of a vehicle; producing a new truth state
based on the simulation of the vehicle; and repeating steps (a)
through (c) using the new truth state.
14. The method of claim 1, further comprising using the PNT
solution to validate that flight software will function as expected
under a possible flight condition.
15. A system for simulating the performance of a receiver, the
system comprising a processor and a computer-readable medium
storing instructions for causing the processor to perform
operations including: (a) implementing a signal transmission model
to generate a set of observables that a receiver in a truth state
would ideally see; (b) implementing a signal disruption model to
add interference to the set of observables to generate a set of
corrupted observables; and (c) implementing a receiver model to
generate a position, navigation, and timing (PNT) solution using
the set of corrupted observables.
16. The system of claim 15, wherein the truth state comprises one
or more of a position, geometry, kinematics, and dynamics of the
receiver.
17. The system of claim 16, wherein the truth state further
comprises one or more of a position, geometry, kinematics, and
dynamics of one or more transmitters.
18. The system of claim 15, wherein the truth state comprises a
previous PNT solution of the receiver.
19. The system of claim 15, wherein the signal transmission model
comprises a global positioning system (GPS) constellation model, a
Galileo constellation model, a GLONASS constellation model, or a
Doppler orbitography and radiopositioning integrated by satellite
(DORIS) constellation model.
20. The system of claim 15, wherein the set of observables
comprises one or more of: pseudorange, range, time-delay-of-arrival
(TDOA), navigation data, carrier phase, code phase, Doppler, and
signal-to-noise ratio (SNR).
21. The system of claim 15, wherein the signal disruption model
applies one or more errors selected from the group consisting of
simulated unintentional interference, jamming, and spoofing, to the
set of observables.
22. The system of claim 21, wherein one or more of the errors are
scaled or correlated based on the truth state.
Description
FIELD
[0001] This application relates to receivers, such as may be used
with navigational satellites, that may be exposed to
interference.
BACKGROUND
[0002] Receivers may estimate the position, navigation, and timing
(PNT) of vehicles using navigational radio frequency (RF) signals
received from ground-based sources and/or from a space-based global
navigation satellite system (GNSS), such as the global positioning
system (GPS), Galileo, GLONASS, or Doppler orbitography and
radiopositioning integrated by satellite (DORIS). For example, a
vehicle may include a receiver that receives satellite signals and
estimates the PNT of the vehicle based on such signals. If the
vehicle is moving, then its estimated PNT may need to be updated
frequently, and the estimated PNT even may be used in a feedback
loop to guide further movement of the vehicle.
[0003] However, receivers may suffer from interference that may
cause errors in the receiver's accuracy in estimating the vehicle's
PNT. Such interference may be intentional or unintentional.
Intentional interference that disrupts the receiver's reception of
the intended signal may be referred to as jamming, while
intentional interference including false signals that mimic a GNSS
or other navigational RF signal and leads the receiver to believe
it is at a false location may be referred to as spoofing. Duplicate
signals, which may be intentional or unintentional, may be referred
to as multipath interference. In some circumstances, navigational
errors caused by interference may cause a moving vehicle to go off
of its intended course, which may be catastrophic. Illustratively,
the ground based augmentation system (GBAS) transmits PNT
corrections to landing airplanes but may become unusable if
subjected to jamming or other interference.
[0004] It is therefore useful to simulate the effects of
interference upon receiver performance in different scenarios. Such
interference has been simulated by adding noise and offsets to a
receiver's PNT solution to simulate degraded tracking, but this is
an imprecise approach. Alternatively, the receiver may be
physically tested in a test event where realistic interference is
broadcast and the receiver's PNT solution in that scenario is
evaluated, which is an expensive and time-consuming approach.
SUMMARY
[0005] Systems and methods for simulating performance of receivers
in realistic interference scenarios are provided herein.
[0006] Some examples herein provide a method for simulating the
performance of a receiver. The method may include (a) generating a
set of observables that a receiver in a truth state would ideally
see. The method further may include (b) adding interference to the
set of observables to generate a set of corrupted observables. The
method further may include (c) generating a position, navigation,
and timing (PNT) solution using the set of corrupted
observables.
[0007] In some examples, the truth state includes one or more of a
position, geometry, kinematics, and dynamics of the receiver. In
some examples, the truth state further includes one or more of a
position, geometry, kinematics, and dynamics of one or more
transmitters.
[0008] In some examples, the truth state includes a previous PNT
solution of the receiver.
[0009] In some examples, generating the set of observables includes
applying a signal transmission model to the truth state. In some
examples, the signal transmission model includes a global
positioning system (GPS) constellation model, a Galileo
constellation model, a GLONASS constellation model, or a Doppler
orbitography and radiopositioning integrated by satellite (DORIS)
constellation model.
[0010] In some examples, the set of observables includes one or
more of: pseudorange, range, time-delay-of-arrival (TDOA),
navigation data, carrier phase, code phase, Doppler, and
signal-to-noise ratio (SNR).
[0011] In some examples, adding interference to the set of
observables includes applying a signal disruption model to the set
of observables. In some examples, the signal disruption model
applies one or more errors selected from the group consisting of
simulated unintentional interference, jamming, and spoofing, to the
set of observables. In some examples, one or more of the errors are
scaled or correlated based on the truth state. In some examples,
the method further includes validating the errors against actual
receiver hardware.
[0012] In some examples, generating the PNT solution includes
applying a receiver model to the set of corrupted observables.
[0013] In some examples, the method further includes outputting the
PNT solution to a simulation of a vehicle; producing a new truth
state based on the simulation of the vehicle; and repeating steps
(a) through (c) using the new truth state.
[0014] In some examples, the method further includes using the PNT
solution to validate that flight software will function as expected
under a possible flight condition.
[0015] Some examples herein provide a system for simulating the
performance of a receiver. The system may include a processor and a
computer-readable medium storing instructions for causing the
processor to perform operations. The operations may include (a)
implementing a signal transmission model to generate a set of
observables that a receiver in a truth state would ideally see. The
operations may include (b) implementing a signal disruption model
to add interference to the set of observables to generate a set of
corrupted observables. The operations may include (c) implementing
a receiver model to generate a position, navigation, and timing
(PNT) solution using the set of corrupted observables.
BRIEF DESCRIPTION OF DRAWINGS
[0016] FIG. 1 schematically illustrates a system for simulating the
performance of a receiver in a realistic interference scenario,
according to some examples provided herein.
[0017] FIG. 2 illustrates a flow of operations in a method for
simulating the performance of a receiver in a realistic
interference scenario, according to some examples provided
herein.
DETAILED DESCRIPTION
[0018] Systems and methods for simulating performance of receivers
in realistic interference scenarios are provided herein. More
specifically, the performance of a receiver may be simulated
beginning with a desired "truth" state of the receiver that
corresponds to a known, estimated, assumed, or calculated PNT of
the receiver. The truth state is used to generate a set of
observables that simulates the signals that the receiver would
ideally receive, e.g., without any corruption caused by
interference. Illustratively, the set of observables may include
simulated signals from a constellation of satellites, such as GPS,
Galileo, GLONASS or DORIS satellites; any relative location and
motion of such satellites relative to the receiver may be included
in the truth state. Interference then is added to the set of
observables so as to create a set of corrupted observables that
realistically simulates the signals that the receiver in the truth
state would actually receive. A PNT solution then is generated
using the set of corrupted observables, that simulates the
processing that the receiver would perform in this interference
scenario. As described in greater detail further below, the
resulting PNT solution may be used in a variety of practical
applications, such as evaluating the navigation of a vehicle that
would be controlled using the receiver in the interference
scenario, evaluating the function of flight software that would be
controlled using the receiver in the interference scenario,
evaluating the design of the receiver in the interference scenario,
or evaluating the design of counter-interference measures in the
interference scenario. As such, the present systems and methods are
expected to be significantly more accurate than merely adding noise
and offsets to a receiver's PNT solution to simulate degraded
tracking, and may be readily validated by laboratory testing which
may involve significantly less time and expense than physically
taking the receiver to a test event where realistic interference is
broadcast.
[0019] FIG. 1 schematically illustrates a system for simulating the
performance of a receiver in a realistic interference scenario,
according to some examples provided herein. System 100 illustrated
in FIG. 1 includes circuitry implementing signal transmission model
101, circuitry implementing signal disruption model 102, and
circuitry implementing receiver model 103. The circuitry
implementing signal transmission model 101 may receive as input a
truth state, and may generate a set of observables that a receiver
in the truth state would ideally see. The circuitry implementing
signal disruption model 102 may receive the set of observables from
signal transmission model 101, and may add interference to the set
of observables to generate a set of corrupted observables. The
circuitry implementing receiver model 103 may receive the set of
corrupted observables from signal disruption model 102, and may
generate a PNT solution using the set of corrupted observables. The
PNT solution may simulate the performance of the receiver that is
modeled using receiver model 103 that is simulated to be in the
truth state and to receive signals as simulated by signal
transmission model 101, which signals are simulated to be corrupted
as simulated by signal disruption model 102.
[0020] The circuitry of system 100 may be implemented using any
suitable combination of hardware and software. For example, signal
transmission model 101, signal disruption model 102, and/or
receiver model 103 may be implemented using a suitably programmed
field-programmable gate array (FPGA) or application-specific
integrated circuit (ASIC). FPGAs and ASICs are commercially
available, and methods of programming same to achieve desired
logical programming are known in the art. In still other
embodiments, one or more of such models can be implemented by a
suitably programmed computer, e.g., a personal computer including a
processor and a non-transitory computer-readable medium storing
instructions to cause the processor to perform the steps of the
present methods or to implement the models. Alternatively, the
processor can include a digital processor, such as a central
processing unit (CPU) or graphics processor unit (GPU), or an
analog processor.
[0021] As noted further above, the truth state that may be input to
signal transmission model 101 may correspond to a known, estimated,
assumed, or calculated PNT of the receiver. The truth state may,
for example, include coordinates of an actual position at which the
receiver is implemented, e.g., coordinates that are obtained using
information independent of the receiver's PNT estimate.
Alternatively, the truth state may, for example, include
coordinates of an estimated position at which the receiver is
implemented, e.g., a PNT solution that the receiver calculates
using navigational RF signals. Alternatively, the truth state may,
for example, include coordinates of an actual position at which the
receiver is planned to be implemented. In still other examples, the
truth state may include coordinates of a position that is
calculated in a manner such as described herein, e.g., a previous
PNT solution of the simulated receiver that is fed back from the
receiver model 103 as the truth state into signal transmission
model 101 in a manner such as illustrated in FIG. 1. It will be
appreciated that the truth state additionally, or alternatively,
may include more than a position. For example, the receiver may
have a geometry, kinematics, and dynamics relative to the
environment in which it is simulated to be located, and such
parameters may be included in the truth state. Additionally, the
transmitters sending simulated signals to the receiver also may
have a geometry, kinematics, and dynamics relative to the
environment in which the receiver is simulated to be located, and
such parameters may be included in the truth state. As such, the
truth state of the simulated receiver, which includes such
information as to sufficiently define the position and velocity of
a receiver at a specific time or provide sufficient information
that realistic approximations may be produced, may express the PNT
of the receiver, as well as of any relevant signal sources
transmitting navigational signals to the receiver or sources of
interference impacting the receiver. The truth state may be stored
in any suitable non-transitory computer-readable medium coupled to
the circuitry implementing signal transmission model 101, or may be
input as a signal to such circuitry.
[0022] As noted above, applying signal transmission model 101
illustrated in FIG. 1 to the truth state input thereto generates a
set of observables that a receiver in the truth state would ideally
see. For example, signal transmission model 101 may include a
global positioning system (GPS) constellation model, a Galileo
constellation model, a GLONASS constellation model, or a DORIS
constellation model. Such constellation models may be commercially
available, e.g., as part of GPS, GNSS, or DORIS simulators. Such
constellation models may be implemented in software, and may
function by taking the truth PVT of the receiver, and determining
the state of the receiver when it sent the signal that the receiver
sees at the truth PVT. That is, such constellation models may
provide a model for time delays of arrival of signals. The
particular signal transmission model 101 used may be selected based
on the particular type of receiver model 103 being used.
Illustratively, a GPS constellation model 101 would be used with a
GPS receiver model 103; a Galileo constellation model 101 would be
used with a Galileo receiver model 102; a GLONASS constellation
model 101 would be used with a GLONASS receiver model 102; or a
DORIS constellation model would be used with a DORIS receiver
model.
[0023] As used herein, an "observable" is intended to mean any
characteristic of a signal that can be used to produce a navigation
solution. Pseudorange and carrier phase both provide complementary
information about the range, while Doppler is essentially a measure
of the rate of change of the range. Other example measurements that
are sometimes used for specific purposes include Carrier-to-Noise
ratio, inter-channel and inter-frequency biases, and the like.
Illustratively, the set of observables used in the present systems
and methods may include any suitable combination of pseudorange,
range, time-delay-of-arrival (TDOA), navigation data, carrier
phase, code phase, Doppler, and signal-to-noise ratio (SNR). For
example, time and atmospheric effects may generate noise that
impacts the pseudorange of signals received by the receiver. As
such, applying the signal transmission model 101 to the truth state
may quantitatively simulate the pseudorange, range, TDOA,
navigation data, carrier phase, code phase, Doppler shift, SNR, and
the like of each of the different simulated signals in the
collection of signals that the receiver would receive, without any
corruption of such signals by interference.
[0024] In order to realistically simulate the impact of an
interference scenario on the receiver, the set of observables
output by signal transmission model 101 is provided to signal
disruption model 102. Signal disruption model 102 may apply one or
more errors to the set of observables, such as simulated
unintentional interference, jamming, and/or spoofing. One or more
of the errors may be scaled or correlated based on the truth state.
For example, if the receiver has a particular position, geometry,
kinematics, or dynamics relative to a given interference source
then signal disruption model 102 may scale or correlate the
error(s) caused by that interference source appropriately. Note
that the errors readily may be validated against actual receiver
hardware.
[0025] The set of corrupted observables then is provided to
receiver model 103, which generates a PNT solution based thereon.
The receiver model 103 emulates how a receiver would respond to the
set of corrupted observables and produce a PNT solution. Receiver
models 103 are commercially available, such as the GNSS-SDR
open-source receiver model. Depending on the particular algorithms
implemented, the receiver model may only utilize a subset of the
available observables. Illustratively, in some examples the signal
disruption model 102 may apply errors to either the
geometry-related observables or to the demodulated observables, so
that the receiver model may be tested for both data-demodulation
and navigation filter performance. Additionally, the signal
disruption model may introduce additional observables related to
false or duplicated signals, e.g., from multipath reflections.
[0026] It will be appreciated that system 100 described with
reference to FIG. 1 may be implemented in any suitable method. For
example, FIG. 2 illustrates a flow of operations in a method for
simulating the performance of a receiver in a realistic
interference scenario, according to some examples provided herein.
Method 200 illustrated in FIG. 2 may include generating a set of
observables that a receiver in a truth state would ideally see
(operation 202). For example, generating the set of observables may
include applying a signal transmission model to the truth state in
a manner such as described with reference to FIG. 1. Method 200
illustrated in FIG. 2 also may include adding interference to the
set of observables to generate a set of corrupted observables
(operation 204). For example, adding interference to the set of
observables may include applying a signal disruption model to the
set of observables in a manner such as described with reference to
FIG. 1. Illustratively, the signal disruption model may apply one
or more errors selected from the group consisting of simulated
unintentional interference, jamming, and spoofing, to the set of
observables. One or more of the errors may be scaled or correlated
based on the truth state, and/or may be validated against actual
receiver hardware. Method 200 illustrated in FIG. 2 also may
include generating a position, navigation, and timing (PNT)
solution using the set of corrupted observables (operation 206).
For example, generating the PNT solution may include applying a
receiver model to the set of corrupted observables in a manner such
as described with reference to FIG. 1.
[0027] It will be appreciated that system 100 described with
reference to FIG. 1 and method 200 described with reference to FIG.
1 may be used for any suitable practical application.
[0028] For example, vehicles may include receivers using
navigational RF signals (e.g., GPS) to guide the vehicles. As such,
interference with the navigational RF signals potential can cause a
catastrophic loss of the vehicle and its passengers, as well as any
payload. The present systems and methods may be used to help
understand how different interference scenarios may affect guidance
of a vehicle, such as a launch vehicle--for example, whether
certain signal types or geometries of jamming or spoofing signals
may cause the vehicle to crash or otherwise may require the flight
to be terminated. Additionally, the present systems and methods may
be used to help improve design of compensating for different
interference scenarios may be compensated for--for example, whether
suitable anti-jamming signals may be usable to cancel the
interference or whether suitable interference-suppression
techniques may be usable to cancel the interference from the RF
signals while leaving adequate SNR for use in guiding the vehicle.
Illustratively, the PNT solution calculated using system 100 or
method 200 may be output to a simulation of a vehicle that, for
example, describes guidance of the vehicle based on that PNT
solution. Based on such simulation (e.g., based on a time step of
that simulation that causes a change in position, geometry,
kinematics, or dynamics of the vehicle) a new truth state may be
generated and may be used as input to the signal transmission model
to generate a new set of observables that then is processed using
the signal disruption model and receiver model in a manner such as
described elsewhere herein. As such, system 100 and method 200 may
be used as part of a closed-loop simulation in which the vehicle
simulation may react to the PNT solution.
[0029] It will be appreciated that the present systems and methods
suitably may be applied to a wide range of other applications. For
example, the PNT solution may be used to validate that flight
software will function as expected under a possible flight
condition, and the software may be modified if it is found that it
does not function as expected. Such an application may be referred
to as a "software-in-the-loop" (SIL) simulation. As another
example, the present systems and methods may be used in receiver
algorithm development, e.g., as a tool to test receiver algorithms
under a wide range of scenarios without having to build
hardware.
[0030] It will further be appreciated that the present systems and
methods may be used to simulate receivers for any suitable
radio-navigation system (such as eLORAN), optical-navigation
system, or any radio-communication service. These systems would
function in much the same way as for GNSS. For example, optical
navigation systems, e.g., laser cross-linked satellites, function
by using light (typically with wavelengths less then 2000 nm) to
transmit timing information and data. In such a system, the present
signal disruption model may include effects from phenomena like
scattering and atmospheric seeing. Furthermore, any
radio-communication signal may be used for navigation. These
so-called "Signals of Opportunity" carry some information that can
be used for navigation, albeit at significantly lower fidelity than
dedicated radio-navigation services.
[0031] It will be appreciated that the present systems and methods
may realistically simulate a receiver's PNT solutions under
hundreds, thousands, tens of thousands, or even more, different
interference scenarios and different truth states. Illustratively,
the present systems and methods may be used to simulate the effect
upon a receiver of realistically degraded signals, both from noise
and jamming; analyze the accuracy of different signals in different
environments (e.g., L1C/A vs. L1P(Y) accuracy); the effects of
spoofing; signal reception degradation, such as code versus carrier
tracking and bit errors; the influence of receiver dynamics;
different navigation filters; and/or the impact of specific
threats. In comparison, physically taking the receiver to a test
event where realistic interference is broadcast may have a
significantly constrained set of different interference scenarios
that may not explore a sufficient number of variables to predict an
outcome of using the receiver in a range of possible scenarios.
[0032] While preferred embodiments of the invention are described
herein, it will be apparent to one skilled in the art that various
changes and modifications may be made. The appended claims are
intended to cover all such changes and modifications that fall
within the true spirit and scope of the invention.
* * * * *