Empirical performance of the spectral independent morphological adaptive classifier

Joel B. Montgomery; Christine T. Montgomery; Richard B. Sanderson; John F. McCalmont

doi:10.1117/12.778704

17 April 2008 Empirical performance of the spectral independent morphological adaptive classifier

Joel B. Montgomery, Christine T. Montgomery, Richard B. Sanderson, John F. McCalmont

Proceedings Volume 6968, Signal Processing, Sensor Fusion, and Target Recognition XVII; 69681M (2008) https://doi.org/10.1117/12.778704
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

Effective missile warning and countermeasures continue to be an unfulfilled goal for the Air Force including the wider military and civilian aerospace community. To make the necessary detection and jamming timeframes dictated by today's proliferated missiles and near-term upgraded threats, sensors with required sensitivity, field of regard, and spatial resolution are being pursued in conjunction with advanced processing techniques allowing for detection and discrimination beyond 10 km. The greatest driver of any missile warning system is detection and correct declaration, in which all targets need to be detected with a high confidence and with very few false alarms. Generally, imaging sensors are limited in their detection capability by the presence of heavy background clutter, sun glints, and inherent sensor noise. Many threat environments include false alarm sources like burning fuels, flares, exploding ordinance, and industrial emitters. Spectral discrimination has been shown to be one of the most effective methods of improving the performance of typical missile warning sensors, particularly for heavy clutter situations. Its utility has been demonstrated in the field and on-board multiple aircraft. Utilization of the background and clutter spectral content, coupled with additional spatial and temporal filtering techniques, have yielded robust adaptive real-time algorithms to increase signal-to-clutter ratios against point targets, and thereby to increase detection range. The algorithm outlined is the result of continued work with reported results against visible missile tactical data. The results are summarized and compared in terms of computational cost expected to be implemented on a real-time field-programmable gate array (FPGA) processor.

Citation Download Citation

Joel B. Montgomery, Christine T. Montgomery, Richard B. Sanderson, and John F. McCalmont "Empirical performance of the spectral independent morphological adaptive classifier", Proc. SPIE 6968, Signal Processing, Sensor Fusion, and Target Recognition XVII, 69681M (17 April 2008); https://doi.org/10.1117/12.778704

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
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Missiles

Sensors

Detection and tracking algorithms

Field programmable gate arrays

Target detection

Aerospace engineering

Sensor fusion

Show All Keywords

Keywords/Phrases

Search In:

Publication Years