Enhanced real time kinematics determination method and apparatus
View Patent ↗A method of and computer-readable medium containing instructions for high accuracy, reliable position determination. A high precision GPS-RTK system using the present novel techniques is initialized instantaneously or near instantaneously. To improve the computational efficiency and to improve the reliability of the procedure, advances in data functional and stochastic modeling, validation criteria, adaptation and system design were achieved. A position estimate using an integrated method is determined. Ambiguity resolution of the position estimate is enhanced by applying a quality control procedure using derived validation criteria. A second position estimate based on the enhanced ambiguity resolution is derived.
1. A method of providing the validation criteria including improved real time kinematics determination, comprising the steps of:
determining a position estimate using an integrated method;
determining validation criteria, comprising the steps of:
tuning a stochastic model of observations;
selecting a typical data set for baselines;
setting validation criteria to preset values and executing an RTK process;
summarizing RTK process results as a function of (1) fixing percentage over total resets and (2) wrong fix percentage over total fixes for each number of satellites, for each of ionosphere activity and environment type;
derive validation criteria values for each preset reliability for each baseline having a different number of satellites;
fitting a function of baseline length and time-to-try classified based on ionosphere activity and environment condition for each preset reliability; and
selecting a validation criteria set based on ionosphere activity and environment type;
enhancing ambiguity resolution of the position estimate by applying a quality control procedure using the derived validation criteria; and
deriving a second position estimate based on the enhanced ambiguity resolution.
2. The method as claimed in claim 1 , wherein the validation criteria include baseline length, time-to-try, number of satellites, present reliability, ionosphere activity, and environment type.
3. The method as claimed in claim 1 , wherein the integrated method uses signals received by a GPS receiver.
4. The method as claimed in claim 3 , wherein the signals are received at an update rate of 1 Hz or lower.
5. The method as claimed in claim 1 , wherein the integrated method comprises the steps of:
determining the position estimate in a coordinate domain;
determining the position estimate in an observation domain;
determining the position estimate in an estimated ambiguity domain; and
integrating the determined position estimates.
6. The method as claimed in claim 1 , wherein the quality control procedure comprises the steps of:
improving a stochastic model for a double-differenced functional model in real-time;
discriminating between an integer ambiguity sets generating the minimum quadratic form of the residuals and a second minimum one; and
performing a fault detection, identification, and adaptation procedure.
7. The method as claimed in claim 6 , wherein the fault detection, identification, and adaptation procedure comprises the steps of:
evaluating a global measure;
evaluating receiver autonomous integrity monitoring methods; and
if the ambiguity resolution is unsuccessful, eliminating the identified outlier observations and updating the double-differenced functional model or executing a different type Kalman filtering resets.
8. The method as claimed in claim 1 , further comprising the step of:
selecting a maximum and minimum value as a function of number of satellites and pre-set reliability.
9. The method as claimed in claim 1 , further comprising the step of:
calculating validation criteria value using the selected maximum and minimum values as a function of the baseline length and time-to-try.
10. The method as claimed in claim 1 , wherein the function of baseline length and time-to-try is:
F
(
t
,
d
)
=
{
f
(
d
)
t
<=
t
1
f
(
d
)
-
2
·
(
f
(
d
)
-
f
(
0
)
)
(
t
2
-
t
1
)
3
·
t
1
<
t
<
t
2
(
3
2
(
t
2
-
t
1
)
(
t
-
t
1
)
2
-
(
t
-
t
1
)
3
)
f
(
0
)
t
>=
t
2
.
11. The method as claimed in claim 9 , wherein the function of baseline length is:
f
(
d
)
=
{
f
min
d
<=
d
1
f
min
+
2
·
(
f
max
-
f
min
)
(
d
2
-
d
1
)
3
·
d
1
<
d
<
d
2
(
3
2
(
d
2
-
d
1
)
(
d
-
d
1
)
2
-
(
d
-
t
1
)
3
)
f
max
d
>=
d
2
.
12. The method as claimed in claim 1 , further comprising the steps of:
determining a position estimate using an integrated method;
enhancing ambiguity resolution of the position estimate by applying a quality control procedure using the derived validation criteria; and
deriving a second position estimate based on the enhanced ambiguity resolution.
13. The method as claimed in claim 12 , wherein the quality control procedure using the validation criteria comprises discriminating between the integer ambiguity sets generating the minimum quadratic form of the residuals and the second minimum one.
14. A method of determining validation criteria used to identify a correct integer ambiguity set from more than one integer ambiguity set in an estimated ambiguity domain, the method comprising the steps of:
tuning a stochastic model of observations;
selecting a typical data set for baselines;
setting validation criteria to preset values and executing an RTK process;
summarizing RTK process results as a function of (1) fixing percentage over total resets and (2) wrong fix percentage over total fixes for each number of satellites, for each of ionosphere activity and environment type;
determining validation criteria values for each preset reliability for each baseline having a different number of satellites;
fitting a function of baseline length and time-to-try classified based on ionosphere activity and environment condition for each preset reliability; and
selecting a validation criteria set based on ionosphere activity and environment type.
15. The method as claimed in claim 14 , further comprising the step of:
selecting a maximum and minimum value as a function of number of satellites and pre-set reliability.
16. The method as claimed in claim 15 , further comprising the step of:
calculating validation criteria value using the selected maximum and minimum values as a function of the baseline length and time-to-try.
17. The method as claimed in claim 15 , wherein the function of baseline length is:
f
(
d
)
=
{
f
min
d
<=
d
1
f
min
+
2
·
(
f
max
-
f
min
)
(
d
2
-
d
1
)
3
·
d
1
<
d
<
d
2
(
3
2
(
d
2
-
d
1
)
(
d
-
d
1
)
2
-
(
d
-
t
1
)
3
)
f
max
d
>=
d
2
.
18. The method as claimed in claim 14 , wherein the function of baseline length and time-to-try is:
F
(
t
,
d
)
=
{
f
(
d
)
t
<=
t
1
f
(
d
)
-
2
·
(
f
(
d
)
-
f
(
0
)
)
(
t
2
-
t
1
)
3
·
t
1
<
t
<
t
2
(
3
2
(
t
2
-
t
1
)
(
t
-
t
1
)
2
-
(
t
-
t
1
)
3
)
f
(
0
)
t
>=
t
2
.
19. A computer readable medium comprising:
at least one sequence of machine executable instructions in machine form, wherein execution of the instructions by a processor cause the processor to:
determine a position estimate using an integrated method; and
derive validation criteria, wherein the validation criteria determination comprises a sequence of machine executable instructions which, when executed by a processor, cause the processor to:
tune a stochastic model of observations;
select a typical data set for baselines;
set validation criteria to preset values and executing an RTK process;
summarize RTK process results as a function of (1) fixing percentage over total resets and (2) wrong fix percentage over total fixes for each number of satellites, for each of ionosphere activity and environment type;
determine validation criteria values for each preset reliability for each baseline having a different number of satellites;
fit a function of baseline length and time-to-try classified based on ionosphere activity and environment condition for each preset reliability; and
select a validation criteria set based on ionosphere activity and environment type;
enhance ambiguity resolution of the position estimate by applying a quality control procedure using derived validation criteria; and
derive a second position estimate based on the enhanced ambiguity resolution.
20. The medium as claimed in claim 19 , wherein the validation criteria include baseline length, time-to-try, number of satellites, present reliability, ionosphere activity, and environment type.
21. The medium as claimed in claim 19 , wherein the quality control procedure comprises a sequence of machine executable instructions which, when executed by a processor, cause the processor to:
improve the stochastic model for the double-differenced functional model in real-time;
discriminate between the integer ambiguity sets generating the minimum quadratic form of the residuals and the second minimum one; and
perform a fault detection, identification, and adaptation procedure.
22. An apparatus for providing improved, real time kinematics determination, the apparatus comprising:
determining means for determining a position estimate using an integrated method;
determining validation criteria, comprising the steps of:
tuning a stochastic model of observations;
selecting a typical data set for baselines;
setting validation criteria to preset values and executing an RTK process;
summarizing RTK process results as a function of (1) fixing percentage over total resets and (2) wrong fix percentage over total fixes for each number of satellites, for each of ionosphere activity and environment type;
derive validation criteria values for each preset reliability for each baseline having a different number of satellites;
fitting a function of baseline length and time-to-try classified based on ionosphere activity and environment condition for each preset reliability; and
selecting a validation criteria set based on ionosphere activity and environment type;
enhancing means for enhancing ambiguity resolution of the position estimate by applying a quality control procedure using derived validation criteria; and
deriving means for deriving a second position estimate based on the enhanced ambiguity resolution.
23. The apparatus as claimed in claim 22 , wherein the validation criteria include baseline length, time-to-try, number of satellites, present reliability, ionosphere activity, and environment type.
24. The apparatus as claimed in claim 22 , wherein the integrated method comprises:
determining means for determining a position estimate in the coordinate domain, a position estimate in the observation domain, and a position estimate in the estimated ambiguity domain; and
determining means for integrating the determined position estimates.
25. The apparatus as claimed in claim 22 , wherein the integrated method uses signals received by a GPS receiver.
26. The apparatus as claimed in claim 25 , wherein the signals are received at an update rate of 1 Hz or lower.
27. A method of determining validation criteria for real time kinematics determination, comprising the steps of:
tuning a stochastic model of observations;
selecting a typical data set for baselines;
setting validation criteria to preset values and executing an RTK process;
summarizing RTK process results as a function of (1) fixing percentage over total resets and (2) wrong fix percentage over total fixes for each number of satellites, for each of ionosphere activity and environment type;
deriving validation criteria values for each preset reliability for each baseline having a different number of satellites;
fitting a function of baseline length and time-to-try classified based on ionosphere activity and environment condition for each preset reliability; and
selecting a validation criteria set based on ionosphere activity and environment type;
wherein the validation criteria set includes baseline length, time-to-try, number of satellites, present reliability, ionosphere activity, and environment type.