Radar target recognition by probabilistic filtering

Anatoliy V. Popov; Oleksiy Pogrebnyak

doi:10.1117/12.558627

26 October 2004 Radar target recognition by probabilistic filtering

Anatoliy V. Popov, Oleksiy Pogrebnyak

Proceedings Volume 5542, Earth Observing Systems IX; (2004) https://doi.org/10.1117/12.558627
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

Abstract

The paper presents a new method of probabilistic filtering for radar target recognition. The classical Bayesian detector/estimator suffers from the insufficient information about target signature probability distributions and their a priory appearance probabilities. If the number of radar image objects to be classified is not known exactly the appeared unknown target may be wrong classified as one of the known targets. To eliminate this type of errors one can use the known probabilistic windows matched by shape to the recognition signature distributions. The combination of the probability window with a non-linear transform of the signature space is proposed in the paper. Such a combination forms a probabilistic filter. The probabilistic filter output is proportional to the likelihood probability of how the sensed object matches to its statistical model. The theoretical background of the probabilistic filtering method and its application to real X-band radar data are presented in the paper. The proposed method reduces the amount of a priory information required for the recognition and detects well the objects of the same nature independently from their size. For example, the probabilistic filter classifies well the different type of vegetation in the radar images.

Citation Download Citation

Anatoliy V. Popov and Oleksiy Pogrebnyak "Radar target recognition by probabilistic filtering", Proc. SPIE 5542, Earth Observing Systems IX, (26 October 2004); https://doi.org/10.1117/12.558627

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