This paper describes the algorithms Arete is developing for shipboard infrared search and track (SIRST) detection of low-observable targets, such as subsonic, sea-skimming cruise missiles. The key algorithm is Arete's Bayesian (probability) field tracker, which is a track-before-detect algorithm. The basic concept of this tracker is to update in successive time steps the probability of all possible target positions and velocities before thresholding. Sample results are presented for simulated low (approximately 6 dB) signal-to-noise ratio (SNR) targets injected into both simulated and real ocean horizon scenes. More conventional detection algorithms require greater SNR for each temporal update. Since the cruise missile signature decreases with increasing range between the sensor and the cruise missile, our Bayesian tracker can detect subsonic, low-observable cruise missiles at greater ranges. To mitigate false alarms the measurement likelihood is modified to account for non-Gaussian noise/clutter statistics (large intensity outliers). False alarm mitigation is demonstrated for injected signatures into real data.
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