PULSED RADAR TARGET RECOGNITION BASED ON MICRO-DOPPLER SIGNATURES USING WAVELET ANALYSIS

Radar based automatic target recognition systems are commonly used in perimeter protection and surveillance applications. These systems determine the nature of a target moving in the radar's field of view using its echo signal. Such an echo signal contains the target's micro-Doppler (μ-D) signature as well as its macro-motion related parameters. This thesis presents and compares three different approaches to develop such a system to distinguish between humans, dogs and background clutter using a low power pulsed radar. Each of these approaches rely on one among three different joint time-frequency transforms such as the short-time Fourier transform, the wavelet packet transform and the Haar transform to extract key μ-D signature related features from the time-frequency plane representation of the echo signal. These μ-D signature based features are combined with relative range profile based ones that characterize the detected target's motion at a gross level. These features, extracted from a variety of field data, are used to train and test different classifiers that finally declare the type of the target. The comparative performances of these three methods have been discussed. The Haar transform based approach, in particular, seems to show promise for implementation on computationally constrained platforms like motes used in wireless sensor network applications.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor dc:publisher

The Ohio State University

Year dc:date

2013

Author dc:creator

• Kizhakkel, Vinit Rajan

Contributors dc:contributor

• Krishnamurthy, Ashok

• Electrical Engineering
• Computer Science
• Engineering
• radar
• pulsed radar
• target recognition
• wavelet
• micro-Doppler

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=osu1366033578

OAI identifier oai:identifier

oai:etd.ohiolink.edu:osu1366033578