Needle picking: a sampling based track-before-detection method for small targets

Fatih Porikli

doi:10.1117/12.850452

15 April 2010 Needle picking: a sampling based track-before-detection method for small targets

Fatih Porikli

Proceedings Volume 7698, Signal and Data Processing of Small Targets 2010; 769803 (2010) https://doi.org/10.1117/12.850452
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

We present a computationally efficient track-before-detect algorithm that achieves more than 50% true detection at 10^-6 false alarm rate for pixel sized unknown number of multiple targets when the signal-to-noise ratio is less than 7dB. Without making any assumptions on the distribution functions, we select a small number of cells, so called as needles, and generate motion hypotheses using the target state transition model. We accumulate cell likelihoods along each hypothesis in the temporal window and append the accumulated values to the corresponding queues of the cell positions in the most recent image. We assign a target in case the queue maximum is greater than a threshold that produces the specified false alarm rate.

Citation Download Citation

Fatih Porikli "Needle picking: a sampling based track-before-detection method for small targets", Proc. SPIE 7698, Signal and Data Processing of Small Targets 2010, 769803 (15 April 2010); https://doi.org/10.1117/12.850452

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