Super-resolution techniques for velocity estimation using UWB random noise radar signals

Muhammad Dawood; Nafish Quraishi; Ana V. Alejos

doi:10.1117/12.884132

21 June 2011 Super-resolution techniques for velocity estimation using UWB random noise radar signals

Muhammad Dawood, Nafish Quraishi, Ana V. Alejos

Proceedings Volume 8021, Radar Sensor Technology XV; 802117 (2011) https://doi.org/10.1117/12.884132
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

The Doppler spread pertaining to the ultrawideband (UWB) radar signals from moving target is directly proportional to the bandwidth of the transmitted signal and the target velocity. Using typical FFT-based methods, the estimation of true velocities pertaining to two targets moving with relatively close velocities within a radar range bin is problematic. In this paper, we extend the Multiple Signal Classification (MUSIC) algorithm to resolve targets moving velocities closer to each other within a given range bin for UWB random noise radar waveforms. Simulated and experimental results are compared for various target velocities using both narrowband (200MHz) and wideband (1GHz) noise radar signals, clearly establishing the unbiased and unambiguous velocity estimations using the MUSIC algorithm.

Citation Download Citation

Muhammad Dawood, Nafish Quraishi, and Ana V. Alejos "Super-resolution techniques for velocity estimation using UWB random noise radar signals", Proc. SPIE 8021, Radar Sensor Technology XV, 802117 (21 June 2011); https://doi.org/10.1117/12.884132

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available