IEEE Transactions on Consumer Electronics, Vol. CE-27, No. 4, November 1981
TV GHOST CANCELLING BY LMS-RAT DIGITAL FILTER
Mohammad Reza Asharif*, Kazuo Murano**, and Mitsutoshi Hatori*
*Department of Electrical Engineering, Faculty of Engineeirng,
University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113, JAPAN
**Transmission Systems Laboratory, Fujitsu Laboratories Ltd.
1015 Kamikodanaka, Nakahara-ku, Kawasaki 211, JAPAN
I. INTRODUCTION
Recently several methods for automatic TV
ghost cancelling are under active research.
Generally speaking, these methods are
Categorized into two substantial groups: 1) TV
ghost cancelling at RF stages including
antenna method. 2) Cancellation at video
stage.
In both of the mentioned above methods,
there are many articles[P-33. As we know,
there are two parameters for ghost evaluation
i.e. the attenuation R and the delay r . The
ghost parameters are dependent on TV channel,
location of the receiver antenna, and the
weather condition which is a function of time
and season. Therefore, the ghost parameters
are variable and the method of cancellation
should be capable of following these
variations. Ghost may be produced by many
multi-directional reflected signals, in this
case, multi-ghosts appear on TV picture. It
is difficult to treat multi-ghosts by the
method of antenna or the method which is
applied at RF stages"2J. Therefore, the method
of cancelling at video stage is thought to be
more prospective, not only for its ability to
process multi-ghosts or to construct a digital
filter which is convenient for LSI, but also
for its adaptive control nature. Therefore,
this research is focused on the utilization of
the adaptive digital filters for TV ghost
cancelling. There are two types of digital
filter:
The feedback and the feedforward types. The
feedforward type generates the "grand-child"
ghost if the filter does not have sufficient
number of taps, while the feedback type does
not have this kind of ghosts. In order to
adjust the taps of the filter, the adaptive
control technique is preferable for the
simplicity of the control circuits. The Least
Mean Square (LMS) algorithm is the original
concept for the adaptation of the filter in
the present work.
The joint optimizations of ghost and white
noise is also considered. If one uses the
inverse type of filter for TV ghost cancelling
the input S/N will decrease that is the noise
power will increase.
While, as we discuss later, by using the
suitable test signal in the adaptive digital
filter the joint optimizations of ghost and
white noise will be obtained that is the noise
power will not increase. Specially, the
feedforward path in the digital filter is
necessary for noise minimization[4]. While the
feedback path is needed to avoid the "grand-
child" ghost.
In the realization of the adaptive recursive
LMS digital filter for TV ghost cancellation
the error samples have delay with respect to
instantaneous input signal samples therefore
the system may be over compensated. Here we
have proposed a new method in order to avoid
over compensation. This method is based on
Random Access Tapping (RAT) control. It will
be shown that the RAT method also prevents the
system to enter into any pseudo optimum
condition. In order to guarantee the stability
of the RAT control we define a new function for
signature operation in the LMS algorithm. The
computer simulation results also confirm the
capability of the recursive LMS algorithm and
its improvement by RAT method for TV ghost
cancellation.
The hardware design of the adaptive
recursive LMS-RAT digital filter for TV ghost
cancellation is described in detail. At the
end the experimental results are given.
[5, 6, 7, 8]
II ADAPTIVE RECURSIVE LMS FILTER
Assuming the tapped delay line (TDL) filter
with both the feedforward and the feedback
paths as is shown in Fig. 1. If A and B are
the vertical vectors of non-recursive and
recursive tap coefficients, respectively and
X, Y are column vector of the input, output
signal samples series in the filter then we
have:
A(n) [aO(n)al (n)a2(n) aNF (n)] (1-a)
B(n) = [b (n)b2 (n)b3 (n) . bNB(n) ] (1-b)
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1981 IEEE
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