Design of spectrally adaptive noise radar waveforms

Caden J. Pici; Ram M. Narayanan

doi:10.1117/12.2520004

3 May 2019 Design of spectrally adaptive noise radar waveforms

Caden J. Pici, Ram M. Narayanan

Proceedings Volume 11003, Radar Sensor Technology XXIII; 110030M (2019) https://doi.org/10.1117/12.2520004
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

The emergence of cognitive radar has led to a considerable amount of research into optimizing a radar's waveform to achieve better performance for a desired task. Specifically, optimizing a waveform's energy spectrum to take advantage of interference, noise, and a target's scattering characteristics has led to a number of approaches for design. Noise radar has emerged as a desirable candidate for radar operation in a tactical environment due to its low probability of interception and detection (LPI/LPD) characteristics, along with the ease of wideband waveform generation. This paper attempts to take a step towards the development of a cognitive noise radar by combining these two areas of research. This is studied by looking at adaptive spectral shaping of noise radar pulses to achieve performance gains in the system. Techniques traditionally applied to stochastic process modeling are utilized to derive a pulse shaping filter that takes advantage of the at spectrum of a white noise pulse to shape it to the desired spectral mask.

Citation Download Citation

Caden J. Pici and Ram M. Narayanan "Design of spectrally adaptive noise radar waveforms", Proc. SPIE 11003, Radar Sensor Technology XXIII, 110030M (3 May 2019); https://doi.org/10.1117/12.2520004

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