Data processing: measuring – calibrating – or testing – Measurement system – Orientation or position
Reexamination Certificate
1999-11-22
2003-03-18
Barlow, John (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system
Orientation or position
C702S152000
Reexamination Certificate
active
06535833
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to positioning systems. More particularly, the present invention pertains to the application of a filter, such as the extended Kalman filter, in such positioning systems, or in systems that provide estimates of one or another aspect besides position of the motion of an object, using information acquired from cellular base stations and from satellites.
BACKGROUND OF THE INVENTION
A satellite positioning system (SATPS) receiver generally determines its positions by triangulating its Line of Sight (LOS) range to several satellites or space vehicles. A GPS receiver, for example, computes a 4-dimensional solution involving latitude, longitude, altitude, and time using the LOS ranges to as few as four satellites. The accuracy of the solution is a direct function of the accuracy of the range measurements.
SATPS receivers are growing rapidly in popularity and application. GPS receivers, for example, are now common in aviation, marine, and terrestrial applications. An increasingly common terrestrial application for GPS receivers is in automobiles. In the automotive context, the vehicle's location is typically displayed on an electronic display of a street map. It is vital in this context, therefore, to provide the driver with continuously updated position solutions, collectively called a “ground track,” that accurately track the vehicle's movement from one moment to the next. Experience shows that consumers consider ground-track fidelity as one of the most important criteria in choosing a receiver. It is extremely important, therefore, that the ground-track displayed on the GPS receiver's electronic map not have spurious jumps, stair steps, spikes, jigs, or jogs that are unrelated to the vehicle's actual path.
There are a number of factors, however, that may cause discontinuities in the position solutions used to determine the ground-track of an automotive SATPS receiver. One source of position solution discontinuity is “Selective Availability” (SA), which restricts the accuracy of civilian GPS receivers to roughly 100 meters. SA is intentionally used by the U.S. Government for purposes of national security. The Department of Defense (DOD) implements SA by purposely injecting error into the satellite range signals.
Another common source of position solution discontinuity is due to the phenomenon known as multi-path, where the true LOS signal from a given satellite reaches the GPS receiver's antenna, along with additional signals providing supposedly the same information, the additional signals caused by reflection from nearby objects, such as buildings or cliffs. The multi-path phenomenon is particularly troublesome for automotive receivers because they are frequently used in cities and surrounded by tall buildings. This environment is sometimes called an “urban canyon” due to the canyon-like setting it resembles. Regardless of source, multi-path can be a very vexing problem because the additional signals may be very strong, but very wrong.
Yet another source of position solution discontinuity is that the constellation of satellites used by a SATPS receiver can change; the SATPS receiver may see a different constellation of satellites from one moment to the next. If the GPS receiver is located in an urban canyon environment, for example, individual satellites may become blocked and later unblocked as the receiver moves past different buildings. The discontinuity arises in this situation because the error in a position solution is based on the constellation of satellites used. (Two satellites located in approximately the same direction will provide position information with larger error than two satellites in very different directions, all other things being equal.) If the position solution provided by a GPS receiver is suddenly based on a different constellation, the different error may cause a jump or discontinuity in position.
It is known in the art to use a Kalman filter to account for the uncertainties in measurement data provided to a positioning system receiver.
FIG. 1
is a simplified flow diagram of a conventional GPS-type positioning system
10
including an RF antenna
11
, a measurement engine
12
and a Kalman filter
14
, providing a position estimate {circumflex over (x)}(k) for position at time instant k. The measurement engine
12
receives RF signals from a plurality of orbiting satellites via the antenna
11
and provides the Kalman filter
14
with measured position and velocity, i.e. measured state information as opposed to the predicted state information provided by the Kalman filter based on the measured values.
The construction of the measurement engine
12
varies from application to application. Generally, the measurement engine
12
contains the analog electronics (e.g. preamplifiers, amplifiers, frequency converters, etc.) needed to pull in the RF signal, and further includes a code correlator for detecting a particular GPS code corresponding to a particular satellite. The measurement engine
12
estimates the line of sight (LOS) range to a detected satellite using a local, onboard GPS clock and data from the satellite indicating when the satellite code was transmitted. The LOS ranges determined this way are called pseudo-ranges because they are only estimates of the actual ranges, based on the local detection time. In the positioning system
10
of
FIG. 1
, the measurement engine
12
converts the pseudo-ranges it acquires over time to measurements z(k) of the state of the process, i.e. to a position and velocity of the moving object whose position is being determined.
In estimating the state x(k) of a process (such as the motion of a vehicle), a (standard) Kalman filter relies on the assumption that the process evolves over time according to a linear stochastic difference equation, such as:
x
(
k
+1)=
A
(
k
)×(
k
)+
Bu
(
k
)+
w
(
k
) (1)
where w(k) is the process noise, A(k) is an n×n matrix relating the state at time step k to the state at time step k+1 in the absence of a driving function, u(k) is a control input to the state x, and B is an n×l matrix that relates the control input to the state x. A standard Kalman filter further relies on the assumption that the measurements used by the Kalman filter in estimating the state of the process are linearly related to the state of the process, i.e. that a measurement z(k) (i.e. the measured position at time instant k) is corresponds to the state x(k) (i.e. the actual position at time instant k) according to an equation of the form:
z
(
k
)=
H
(
k
)×(
k
)+
s
(
k
) (2)
where s(k) is the measurement noise, and the m×n matrix H relates the state x(k) to the measurement z(k). If either of these assumptions do not apply, a standard Kalman filter cannot be used, or at least not used without first deriving from information provided (by e.g. satellites) about the process measurement data that is, at least approximately, linearly related to the state of the process, and at least not without taking measurements at close enough intervals that the effects of any non-linearity in the evolution of the process does not become important from one measurement to the next.
In the case of a positioning system in a vehicle where the positioning system uses information from satellites as the basis for position measurements, the dependence between the state (position, but in general also velocity) of the process (motion of the vehicle hosting the positioning system), and the position measurements is non-linear, i.e. instead of equation (2), the satellite provides a pseudo-range:
ρ
(
k
)
=
∑
i
=
1
3
[
x
i
(
k
)
-
x
i
s
(
k
)
]
2
+
ct
o
in which x
i
(k) is, e.g. the i
th
component of the three-dimensional position of the vehicle, x
i
s
is the same for the satellite, t
o
is a clock offset between the positioning system clock in the vehicle and the satellite clock, and c is used to designate the speed of light.
It is known in t
Barlow John
Nokia Mobile Phones Ltd.
Ware Fressola Van Der Sluys & Adolphson LLP
Washburn Douglas N
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