Image Processing Reference
In-Depth Information
In the case of a maneuvering target (two legs and a maneuvering time t m that is
known), the state vector becomes 6-dimensional and the calculations become notice-
ably more complicated [LEC 00]. We then obtain:
c
t 1 ,...,t 6
t 1
t 2 t 3
t 4 t 5
t 6 2
det( FIM )
2 t 2 cos 2 β 0
2 t 2
2 t m + t 2 sin 2 β 0 ,
×
2 t 2 β t 2
t 1 + t 1 + t 2 cos 2 β 0 +sin2 β 0 ,
β 2 t 1
sin 2 β 0 ,
t 2 2 t 2
2 t m
t 2 t 1 + t 2 2 cos 2 β 0
+
sin 2 β 0 2 .
t 3 + t 4
t 6 2
t 2 +2 t m + t 2 cos 2 β 0
t 5
This formula might seem disconcertingly complex. We notice, however, that the
predominant term is simply:
2 t 2 cos 2 β 0
2 t 2
2 t m + t 2 sin 2 β 0 .
Again, we reach the conclusion that the optimal strategy consists of focusing the
active measurements on the extremities of the legs. Therefore, as you can see, sim-
ple considerations make it possible for us to grasp the fusion of active and passive
measurements in target motion analysis.
6.9.4. Detection of a moving target in a network of sensors
The problem here is simple. How can we detect a moving target traveling through
a network of sensors? In order to better outline the problem, a few specifics are neces-
sary. We will assume in this case that the detection radius of each sensor is relatively
limited, so as to make it reasonably impossible for it to detect more than one target.
At a given time, a target is only perceivable by a few sensors of the network that are
close enough.
In practice, this means that antenna processing methods are of little use. There is
no concept of antenna gain and we therefore have to rely first and foremost on time
discrimination. As a result, the target motion analysis stage is the core of single sensor
detection. We will not discuss any further the method used, or performance calculation
in detection. For this, see [DON 00, DON 02].
In general, it is actually impossible to achieve detection on the sensor's level at the
output of partial target motion analysis. In practice, this means that the sensor's signal
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