Linear combination of multiple adaptive 2-class classifiers: an efficient, effective approach to airborne target ID

Joan L. Brierton

doi:10.1117/12.280832

28 July 1997 Linear combination of multiple adaptive 2-class classifiers: an efficient, effective approach to airborne target ID

Joan L. Brierton

Author Affiliations +

Proceedings Volume 3068, Signal Processing, Sensor Fusion, and Target Recognition VI; (1997) https://doi.org/10.1117/12.280832
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

Linearly combining multiple, adaptive 2-class classifiers provides the capability to integrate many individual classifiers each of which possesses arbitrarily complex decision boundaries into simple, functioning classification system. Adaptive two classifiers and the linear combination approach are described. In benchmarking studies this approach has been shown to require O(2) magnitude less computational resources when compared to a classical statistical approach. We will present comparative resource requirements for performance equivalent algorithms. The adaptive algorithm used in the above benchmarking study is widely known for its pattern recognition capabilities. This approach can be used on range profile data to perform 1D target ID. In this applications, two characteristics of this approach can be seen to be of particular benefit in an airborne environment. These characteristics are: robust performance in the face of varying SNR and robust performance in the face of rough aspect angle information. We will discuss the theory behind the characteristics of this approach that provide such benefits. Finally, with respect to the cost required to maintain a fielded system, a linear combination approach to adaptive ID algorithms provides special benefits. Chief among the advantages is the ability to rapidly update a fielded system with new information. Using this approach the changes required to add new targets to a given system are equivalent to downloading a new data base. The nature of this algorithm allows for low risk, low cost upgrades. Furthermore, very rapid turn around time will be possible in the case where only a small percentage of new targets are to be added to the capabilities of a fielded system.

Citation Download Citation

Joan L. Brierton "Linear combination of multiple adaptive 2-class classifiers: an efficient, effective approach to airborne target ID", Proc. SPIE 3068, Signal Processing, Sensor Fusion, and Target Recognition VI, (28 July 1997); https://doi.org/10.1117/12.280832

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
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Detection and tracking algorithms

Matrices

Neural networks

Pattern recognition

Evolutionary algorithms

Radar

Signal to noise ratio

Show All Keywords

Keywords/Phrases

Search In:

Publication Years