Airborne target identification from low-crossrange-resolution ISAR imagery

Bruce I. Hauss; Hiroshi H. Agravante; C. D. Eberhard; Karen M. Luebkemann; Thomas K. Samec; Thomas M. Wagner; August W. Rihaczek; Stephen J. Hershkowitz; R. L. Mitchell; E. Perahia; Donald Arnush; Sridhar Lakshmanan

doi:10.1117/12.257215

5 November 1996 Airborne target identification from low-crossrange-resolution ISAR imagery

Bruce I. Hauss, Hiroshi H. Agravante, C. D. Eberhard, Karen M. Luebkemann, Thomas K. Samec, Thomas M. Wagner, August W. Rihaczek, Stephen J. Hershkowitz, R. L. Mitchell, E. Perahia, Donald Arnush, Sridhar Lakshmanan

Author Affiliations +

Proceedings Volume 2845, Radar Processing, Technology, and Applications; (1996) https://doi.org/10.1117/12.257215
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

In a target-rich battlefield environment, a shipboard or an airborne radar must maintain situational awareness while tracking and identifying targets. Often the opportunity to dwell on each target long enough for confident identification via high resolution SAR/ISAR imaging will not exist, especially for those engagement geometries where the relative translational motion of the aircraft does not result in large rotation rates. Inadvertent aircraft tactical dither often generates enough target rotational during a brief imaging interval to allow the formation of an ISAR image with low crossrange resolution. We have developed an automated identification procedure that utilizes this resolution, along with high range resolution, to produce confident target identification. The advanced signal processing algorithms employed extract feature measurements from the complex ISAR image. including accurate measurements of the two-dimensional positions, amplitudes and range extents of the dominant target scatterers. A deformable template matching procedure is used to correlate these 'measured features' with those predicted for each candidate aircraft in a database generated from readily available diagrams, photographs and CAD models. After obtaining the optimal fit between the measured and predicted features for each candidate aircraft, the 'most likely' candidate is selected using a conventional Bayes classifier.

Citation Download Citation

Bruce I. Hauss, Hiroshi H. Agravante, C. D. Eberhard, Karen M. Luebkemann, Thomas K. Samec, Thomas M. Wagner, August W. Rihaczek, Stephen J. Hershkowitz, R. L. Mitchell, E. Perahia, Donald Arnush, and Sridhar Lakshmanan "Airborne target identification from low-crossrange-resolution ISAR imagery", Proc. SPIE 2845, Radar Processing, Technology, and Applications, (5 November 1996); https://doi.org/10.1117/12.257215

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
13 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image resolution

Radar

Scatter measurement

Target recognition

Data modeling

Antennas

Image segmentation

Show All Keywords

Keywords/Phrases

Search In:

Publication Years