Pulse or digital communications – Bandwidth reduction or expansion – Television or motion video signal
Reexamination Certificate
2000-11-16
2003-05-13
Britton, Howard (Department: 2613)
Pulse or digital communications
Bandwidth reduction or expansion
Television or motion video signal
C375S240280, C714S020000
Reexamination Certificate
active
06563871
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates to a device for calculating estimated time stamps ì, the device comprising processor means provided with an output, and with an input for receiving true times Y
t
of a data packet number t having the linear form:
Y
t
=Y
t−1
+&bgr;
t
,
&bgr;
t
=&bgr;
t−1
+&eegr;
t
,
with &eegr;
t
being a small perturbation relative to the linear relation between time and packet number, whereby the processor means are arranged:
to observe the true time of data packet number t as:
o
t
=Y
t
+&egr;
t
,
where &egr;
t
is an observational error, and
to produce at its output the estimated time stamps according to:
ì
t
=ì
t−1
+&bgr;
t
.
The present invention also relates to a method set out in the preamble of claim 5.
Such a device and method are known from “Bayesian forecasting and dynamic models”, by West, M. and J. Harrison, in particular section 7.3, Springer, 1998. Described therein is the Bayesian Kalman model, which is a dynamic linear model for predicting time stamps ì
t
, based on true times Y
t
of an input data packet number t. This technique is applied in Digital Videocommunication Systems used in the distribution and combination of for example video signals for multiplexing, re-multiplexing and de-multiplexing in particular MPEG (=Moving Picture Encoded Group) transport streams. Usually the relation between time and packet number is linear in e.g. MPEG streams. In practise the specifications of these streams allow for small deviations from linearity, whereby the coefficients of the linear relation may vary slowly in time. The true times Y
t
of data packet number t can be described in the linear form as:
Y
t
=Y
t−1
+&bgr;
t
,
&bgr;
t
=&bgr;
t−1
+&eegr;
t
,
with &eegr;
t
being a small perturbation relative to the linear relation between time and packet number, that holds in the vicinity of packet t−1. The true time of data packet number t is observed as:
o
t
=Y
t
+&egr;
t
,
where &egr;
t
is an observational error. &egr;
t
and &eegr;
t
are stochastic variables having a normal distribution in the standard theoretical development of the model. Now based on prior knowledge about (&bgr;
0
, Y
0
), an explicit Bayesian analysis can be performed leading to a posterior distribution of (&bgr;
t
, Y
t
) after observing o
t
. This leads to the known Bayesian Kalman filter as a means for revealing ì
t
as an estimate for the true time Y
t
, given the observed time (o
1
, . . . , o
t
) of packet t. West and the Harringtons give a full formal derivation thereof in section 7.3. Two Bayesian Kalman, to be referred to as BK, estimates are proposed. The ordinary BK is optimal with respect to a tracking error &dgr;
(t)
, defined by: #Y
t
−ì
t
#<&dgr;
(t)
, whereas a smoothed BK estimate is optimal with respect to smoothness, defined by: #ì
t
−2ì
t−1
+ì
t−2
#<&dgr;
(s)
.
It is a disadvantage of the standard Bayesian Kalman device and method that, either tracking or smoothing constraints can only be complied with.
SUMMARY OF THE INVENTION
Therefore it is an object of the present invention to provide an improved Bayesian Kalman device and method, which can simultaneously comply with both the above tracking constraint and the above smoothing constraint.
Thereto the device according to the present invention is characterised in that the computation by the processing means is such that the value of &bgr;
t
is made dependent on the exceeding by #o
t
−ì
t−1
−&bgr;
t−1
# of max[&egr;
t
].
It is an advantage of the device according to the invention that the values of &egr;
t
are made conditional on the difference between the observed true time o
t
and the estimated time stamps ì
t
. If tracking becomes a problem the maximum value of &egr;
t
(which is max[&egr;
t
]), is exceeded by that difference and then &bgr;
t
can be chosen to have a different value, such that tracking will no longer be a problem. Thus the result is a sequence of time stamps, which is both smooth and accurate, which is especially but not exclusively important in an SW-MUX (SoftWare encoding and MUltipleXing), TokenMux or DTS (Decode Time Stamp) environment, where observed time stamps in data, samples and/or packets can be very noisy or are provided with jitter.
As time stamps are very important in devices and apparatus that time, multiplex, demultiplex or remultiplex program components, such as program encoders, splicers etcetera, an improved timing accuracy also improves the video image quality and synchronisation capabilities. It also shortens the acquisition time in transport stream equipment, such as with MPEG-2 transport streams.
Another embodiment of the device according to the invention is characterised in that the computation by the processing means is such that:
&bgr;
t
equals &bgr;
t
(i)
if #
o
t
−ì
t−1
−&bgr;
t−1
#≦max[&egr;
t
], else
&bgr;
t
equals &bgr;
t−1
+sign(
o
t
−ì
t−1
−&bgr;
t−1
)max[&eegr;
t
], with
&bgr;
t
(i)
=&bgr;
t−1
+rA,
A
=(
o
t
−ì
t−1
−&bgr;
t−1
)/var[
o
t
],
r being the prior—i.e before observing o
t
—correlation between &bgr;
t
and Y
t
; and that:
ì
t
=ì
t−1
+&bgr;
t−1
+A
*var[Y
t
].
Advantageously in case of tracking problems the values of &bgr;
t
are updated at the maximum rate that is allowed by the specifications, whereby this boosted estimate replaces the smooth Bayesian Kalman estimate of &bgr;
t
in the Kalman recursion relations. The filter thus devised approaches to some extend the known Bayesian Kalman filter device as a special case, which may be achieved by setting max[&egr;
t
]=∞. Advantageously the device according to the invention has three degrees of freedom: max[&egr;
t
] which usually is the upper bound to the magnitude of the noise, max[&eegr;
t
] which is the upper bound to the maximum nonlinearity that is allowed, and var[&egr;
t
] or &sgr;
2
[&egr;
t
] being the variance of the statistical noise distribution.
One embodiment of the device according to the invention is characterised in that the processing means are programmable processing means, which are programmed to perform said computations. It is an advantage of the device according to the invention that no essential hardware is necessary and that the computations can be done by an ordinary computer, such as a PC, whereon the advanced BK filter can be software implemented.
Easy and flexible programming is realised in a further embodiment of the device according to the invention, which is characterised in that the computations are programmed in the C programming language.
Similarly the method according to the present invention has the characterising features outlined in claim 5, and the advantages set out above.
REFERENCES:
patent: 5778387 (1998-07-01), Wilkerson et al.
patent: 5884249 (1999-03-01), Namba et al.
Denteneer Theodorus Jacobus Johannes
Dijkhof Antonie
Britton Howard
Gathman Laurie E.
Koninklijke Philips Electronics , N.V.
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