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Precise ground target localization is an interesting problem and relevant not only for military but also for civilian
applications, and this is expected to be an emerging field with many potential applications. Ground Target Location
Using Loitering Munitions (LM) requires estimation of aircraft position and attitude to a high degree of accuracy, and
data derived by processing sensor images might be useful for supplementing other navigation sensor information and
increasing the reliability and accuracy of navigation estimates during this flight phase. This paper presents a method for
high accuracy ground target localization using Loitering Munitions (LM) equipped with a video camera sensor. The
proposed method is based on a satellite or aerial image matching technique. In order to acquire the target position of
ground intelligently and rapidly and to improve the localization accuracy estimating the target position jointly with the
systematic LM and camera attitude measurement errors, several techniques have been proposed. Firstly, ground target
geo-location based on tray tracing was used for comparison against our approach. By proposed methods the calculation
from pixel to world coordinates can be done. Then Hough transform was used to image alignment and a median filter
was applied for removing small details which are visible from the sensed image but not visible from the reference image.
Finally, A novel edge detection method and an image matching algorithm based on bifurcation extraction were proposed.
This method did not require accurate knowledge of the aircraft position and attitude and high performance sensors,
therefore it is especially suitable for LM which did not have capability to carry accurate sensors due to their limited play
weight and power resources. The results of simulation experiments and theory analyzing demonstrate that high accuracy
ground target localization is reached with low performance sensors, and achieve timely. The method is used in
reconnaissance and surveillance missions, or applicable in any other environment with a relevantly structured clutter.
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