Non-linear optimization using classical & evolutionary algorithm for radar detection of targets

Das, N (2014) Non-linear optimization using classical & evolutionary algorithm for radar detection of targets. BTech thesis.



The main objective of this project is to study about the basics of Ground penetrating Radar (GPR) and optimize various multi-variable non-linear functions using the non-linear techniques such as Conjugate Gradient method, Steepest Descent Method. Ground penetrating radar (additionally alluded to as GPR, ground probing radar, or georadar) is a close-surface geophysical device with an extensive variety of requisitions. In the course of recent years, GPR has been utilized effectively to help within compelling issues in various fields, for example, archaeology, environmental site characterization, glaciology, hydrology, land mine/unexploded law identification, sedimentology, and structural topography. By and large, nonetheless, GPR reviews have been arranged or executed with next to zero understanding of the physical premise by which GPR works and is compelled. The objectives of this preparation are to (1) give a prologue to the essential variables related to GPR and (2) to clarify the pertinent parts of these variables in GPR securing, trying to give key information to enhancing GPR use later on.

Item Type:Thesis (BTech)
Uncontrolled Keywords:GPR; Conjugate Gradient Method; Steepest Descent Method; Global Reflection Coefficient
Subjects:Engineering and Technology > Electronics and Communication Engineering > Wireless Communications
Divisions: Engineering and Technology > Department of Electronics and Communication Engineering
ID Code:6281
Deposited By:Hemanta Biswal
Deposited On:09 Sep 2014 09:29
Last Modified:09 Sep 2014 09:29
Supervisor(s):Maiti, S

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