14-05-2012, 03:19 PM
Soft Computing Technique (PLE) for Target Tracking
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INTRODUCTION
The basic problem in target motion
analysis (TMA) is to estimate the
trajectory of an object (i.e., position
and velocity) from noise corrupted
sensor data. In the context of ocean
environment, the moving
observation platform (I.e., receiver,
observer, own ship) passively
monitors sonar bearings from a
single acoustic source (i.e., target),
SENSORS:
In order to understand the
simulator that we have developed in this
project we need to have an understanding
of the sensors that are used in real-time.
Examples of sensors are Radars and
Sonars.
SONAR
SONAR refers to Sound
Navigation And Ranging. It is the
technique for g and determining the
distance and direction of underwater
objects by means, Sound waves emitted or
reflected from the object is processed to
give information about the object (e.g.
Range and Bearing of the Target
ACTIVE TARGET TRACKING:
In the active target tracking, the
observer will send electromagnetic signals
s the air target and acoustic signal towards
the underwater target. Then the reflected
waves will be received by using the
sensors present in the Own ship. The
received signals will be utilized to find the
range of the target, velocity and angles of
its movement.
PASSIVE TARGET TRACKING:
In passive target tracking, the observer
will not send any sort of signal towards
the target, but will trace out the target
by its specific characteristics. Here
observer will receive the signals
emitting from the target by using the
sensor matrix. There by analyze the
nature of the target, its direction of
movement and velocity of it.
INPUTS TO THE SIMULATOR:
Target parameters Range,
Course, Bearing and Speed and Own
ship parameters course and speed are
read and taken as input by the
simulator. Assumed error in bearing
measurement (sigma_b) and range
measurement (sigma_r) are also fed as
input.