Charles River Analytics Develops ATD/T Performance Predictor for AMRDEC

Charles River Analytics received follow on funding from the U.S. Army’s Aviation and Missile Research, Development and Engineering Center (AMRDEC) to continue developing the Evaluation Testbed for ATD/T Performance Prediction (ETAPP). ETAPP predicts the performance of automatic target detection/tracking (ATD/T) algorithms, constructing models of performance prediction that are more comprehensive than those commonly employed (such as quick-look models), and are less computationally expensive than using detailed exhaustive simulation.

Dr. Scott K. Ralph, a Senior Scientist at Charles River Analytics, explained ETAPP’s benefit to ATD/T performance prediction: “ATD systems process imagery to detect and locate targets in imagery in support of a variety of military missions. Accurate prediction of ATD performance would assist in system design and trade studies, collection management, and mission planning. A need exists for ATD performance prediction based exclusively on information available from the imagery and its associated metadata. We present a predictor based on image measures quantifying the intrinsic ATD difficulty on an image.”

Dr. Ralph continued, “The modeling effort consists of two phases: a learning phase, where image measures are computed for a set of test images, the ATD performance is measured, and a prediction model is developed; and a second phase to test and validate performance prediction.”

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