Vector neural network signal integration for radar application

Gregory S. Bierman

doi:10.1117/12.179059

6 July 1994 Vector neural network signal integration for radar application

Gregory S. Bierman

Proceedings Volume 2235, Signal and Data Processing of Small Targets 1994; (1994) https://doi.org/10.1117/12.179059
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

The Litton Data Systems Vector Neural Network (VNN) is a unique multi-scan integration algorithm currently in development. The target of interest is a low-flying cruise missile. Current tactical radar cannot detect and track the missile in ground clutter at tactically useful ranges. The VNN solves this problem by integrating the energy from multiple frames to effectively increase the target's signal-to-noise ratio. The implementation plan is addressing the APG-63 radar. Real-time results will be available by March 1994.

Citation Download Citation

Gregory S. Bierman "Vector neural network signal integration for radar application", Proc. SPIE 2235, Signal and Data Processing of Small Targets 1994, (6 July 1994); https://doi.org/10.1117/12.179059

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