GNSS Signal Processing Methods and Apparatus with Scaling of Quality Measure

81 Pages·2013·5.74 MB·English

US 20110148698A1
(19) United States
(12) Patent Application Publication (10) Pub. No.: US 2011/0148698 A1
Vollath (43) Pub. Date: Jun. 23, 2011
(54) GNSS SIGNAL PROCESSING METHODS AND (52) US. Cl. ................................................. .. 342657.27
APPARATUS WITH SCALING OF QUALITY (57) ABSTRACT
MEASURE
Methods and apparatus are provided for estimating param
(75) Inventor: Ulrich Vollath, lsmaning (DE) eters, i.e. ambiguities, derived from GNSS signals. Observa
tions of GNSS signals are obtained from each of a plurality of
GNSS satellites (1120). The observations are fed to a ?lter
(73) Assignee: TRIMBLE NAVIGATION
having a state vector at least comprising a ?oat ambiguity for
LIMITED, Sunnyvale, CA (US)
each received frequency of the GNSS signals (1140). The
?lter estimates a ?oat value for each ?oat ambiguity of the
(21) Appl. No.: 13/059,415 state vector. Integer values are assigned to at least a subgroup
of the estimated ?oat values to de?ne a plurality of integer
(22) PCT Filed: Aug. 5, 2009 ambiguity candidate sets (1160). A quality measure is deter
mined for each of the candidate sets. The best quality measure
of the candidate sets is determined. An expectation value of
(86) PCT No.: PCT/US2009/004472
the candidate set having the best quality measure is deter
mined (1 170). An error measure as a ratio of the best quality
§ 371 (0X1),
measure to the expectation value is determined. The quality
(2), (4) Date: Feb. 16,2011
measures of the candidate sets is adapted as a function of the
error measure (1180). A Weighted average of a subgroup of
Related US. Application Data the candidate sets on the basis of the adapted quality measures
is formed, Wherein at least one of selecting the subgroup of
(60) Provisional application No. 61/189,382, ?led on Aug.
the candidate sets and the Weighting of each candidate set in
19, 2008.
the Weighted average is based on the adapted quality measure
(1200). Ambiguities of the Weighted average can be used in
subsequent operations to aid in determining a position of the
Publication Classi?cation
receiver or can be used to prepare data, e.g., in a network
(51) Int. Cl. processor that can be used to augment position information of
G01S 19/44 (2010.01) a rover.
1120 m
\ Observing GNSS signal [
from satellites
observations
1 140
Feeding the observations
into a ?lter
1 140a L ?oat solution
I Optional step:
, Z-transiormation
1160 I ?oat solution (optionally
transformed through Z-iransfurm)
1 170
‘R Assigning integer values to best Candidate Set
the ?oat solution to de?ne r’)
candidate sets
Determine expectation of best
7 candidate set and adapting the
candidate sets quality measures
1 180
Selecting candidate sets
usin thre h id
9 S 0 adapted quality measures
provided to in?uence the
selected candidate sets cand'date set seiecnon
Forming a weighted
average of the selected
candidate sets
1200a t
| _ _ _ _ _ _ _ _ — _ T _ _ ' _ l
l Optional step: I
I reverse Z-transformation l
I parameters = iFlex solution
Patent Application Publication Jun. 23, 2011 Sheet 1 0f 36 US 2011/0148698 A1
Patent Application Publication Jun. 23, 2011 Sheet 2 0f 36 US 2011/0148698 A1
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Patent Application Publication Jun. 23, 2011 Sheet 3 0f 36 US 2011/0148698 A1
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Patent Application Publication Jun. 23, 2011 Sheet 9 of 36 US 2011/0148698 A1
120 m
\ Observing GNSS signal [
from satellites
observations
140 "
\ Feeding the observations
into a ?lter
1403 l ?oat solution
I l
N Optional step: . :
, Z-transformation
l
?oat solution (optionally
transformed through Z-transform)
\ Assigning integer values to
the ?oat solution to de?ne
candidate sets
candidate sets
180
\\ Selecting candidate sets
using threshold based on
reference quality measure
i selected candidate sets
Forming a weighted
\ average of the selected
candidate sets
200a _____ “it ______ __
|
I Optional step:
I reverse Z-transformation
' I parameters = iFlex solution
Fig. 5a