Balanced random walk for binary phase noise waveform design

Bingcheng Li

doi:10.1117/12.2558187

23 April 2020 Balanced random walk for binary phase noise waveform design

Bingcheng Li

Proceedings Volume 11408, Radar Sensor Technology XXIV; 114080J (2020) https://doi.org/10.1117/12.2558187
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

Binary phase noise waveform is difficult to detect due to its thrum nail ambiguity function, has high transmission efficiency due to its constant magnitude, and is simple for implementation. Because of these advantages, binary phase noise waveform is widely used in noise radar. Many techniques have been developed to design binary phase noise waveform including Bernoulli trial, logistic mapping function, neural network optimization, genetic algorithm, kicked rotor chaos, polyphase perturbing, and particle swarm optimization techniques. In this paper, we first discuss the characteristics that good binary phase noise waveform needs to have. Then we introduce Kolmogorov-Smirnov (KS) two sample test in nonparametric statistics and derive balanced random walk. From balanced random walk theory, we propose balanced random based approach for noise waveform design and demonstrate that the noise waveforms generated by balanced random walk approach have zero direct components. We implement the proposed approach for noise waveform design and show that the proposed method is over 10% better on maximum sidelobes, 30% better on sidelobe energy than Bernoulli trial noise waveform design and selection.

Conference Presentation

Citation Download Citation

Bingcheng Li "Balanced random walk for binary phase noise waveform design", Proc. SPIE 11408, Radar Sensor Technology XXIV, 114080J (23 April 2020); https://doi.org/10.1117/12.2558187

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