Detection of UXO contaminated land fields using hidden Markov models in the SAR images generated by airborne radar system

Thyagaraju Damarla; Lam H. Nguyen; Kenneth I. Ranney

doi:10.1117/12.438163

22 August 2001 Detection of UXO contaminated land fields using hidden Markov models in the SAR images generated by airborne radar system

Thyagaraju Damarla, Lam H. Nguyen, Kenneth I. Ranney

Author Affiliations +

Proceedings Volume 4374, Radar Sensor Technology VI; (2001) https://doi.org/10.1117/12.438163
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

We present an algorithm based on hidden Markov models (HMM) to detect several types of unexploded ordinance (UXO). We use the synthetic aperture radar (SAR) images simulated for 155 mm artillery shell, 2.75 in rocket and 105 mm mortar to generate the codebook. The algorithm is used on the data collected at Yuma Proving ground (YPG). YPG is seeded with several types of UXOs for testing purposes. The data is collected using an ultra wideband SAR mounted on a telescoping boom to simulate the airborne radar. The algorithm has detected all the targets for which it is trained for and it also detected other UXOs that are similar in shape.

Citation Download Citation

Thyagaraju Damarla, Lam H. Nguyen, and Kenneth I. Ranney "Detection of UXO contaminated land fields using hidden Markov models in the SAR images generated by airborne radar system", Proc. SPIE 4374, Radar Sensor Technology VI, (22 August 2001); https://doi.org/10.1117/12.438163

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