False track discrimination in a 3D signal/track processor

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Abstract
Long range detection and tracking of moving targets against clutter requires advanced signal and track processing techniques in order to exploit the ultimate capabilities of modern electro-optical sensors. These include three- dimensional filtering and multiple hypothesis tracking. Unfortunately, features present in real backgrounds can lead to false alarms which must be recognized in order to achieve a low false track rate. This paper describes one approach which was successful at mitigating clutter-induced false tracks while maintaining the low thresholds necessary for the detection of weak targets. This technique uses information derived in the signal processor describing the local background as additional discriminants in the track processor to identify false tracks caused by clutter leakage. We present an overview of the 3D signal track/processor, the false track mitigation methodology, and experimental results against real background data.

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