Approximate expressions of target’s scattering information

Manman Zhao; Dazhuan Xu; Tian Liu; Desen Zhang

doi:10.1117/12.2655342

2 November 2022 Approximate expressions of target’s scattering information

Manman Zhao, Dazhuan Xu, Tian Liu, Desen Zhang

Proceedings Volume 12455, International Conference on Signal Processing and Communication Security (ICSPCS 2022); 124550C (2022) https://doi.org/10.1117/12.2655342
Event: International Conference on Signal Processing and Communication Security (ICSPCS 2022), 2022, Dalian, China

Abstract

In this paper, the content related to scattering information is mainly focused in the presence of complex additive Gaussian white noise (CAGWN). In our previous works, the theoretical formula of the scattering information is already derived with integral operation. To get more brief expressions, we derive the approximate expressions in cases where the signal-to-noise ratio (SNR) is high and low separately. Noting that the a posteriori probability density function (PDF) obeys Gaussian distribution in the case of high SNR so it’s natural to derive the expression of the scattering information’s approximate expression on account of information theory. In low SNR regime, an approximate formula can be obtained with the reason of signal is submerged in the noise. Numerical results are presented to verify the effectiveness of the proposed approximation.

Citation Download Citation

Manman Zhao, Dazhuan Xu, Tian Liu, and Desen Zhang "Approximate expressions of target’s scattering information", Proc. SPIE 12455, International Conference on Signal Processing and Communication Security (ICSPCS 2022), 124550C (2 November 2022); https://doi.org/10.1117/12.2655342

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