continuous wavelet transform and hidden markov model based target detection

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ID: 144518
2014
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Abstract
Standard tracking filters perform target detection process by comparing the sensor output signal with a predefined threshold. However, selecting the detection threshold is of great importance and a wrongly selected threshold causes two major problems. The first problem occurs when the selected threshold is too low which results in increased false alarm rate. The second problem arises when the selected threshold is too high resulting in missed detection. Track-before-detect (TBD) techniques eliminate the need for a detection threshold and provide detecting and tracking targets with lower signal-to-noise ratios than standard methods. Although TBD techniques eliminate the need for detection threshold at sensor’s signal processing stage, they often use tuning thresholds at the output of the filtering stage. This paper presents a Continuous Wavelet Transform (CWT) and Hidden Markov Model (HMM) based target detection method for employing with TBD techniques which does not employ any thresholding.
Reference Key
tua2014radioengineeringcontinuous Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;S. Tuğaç;M. Efe
Journal molecular therapy : the journal of the american society of gene therapy
Year 2014
DOI DOI not found
URL
www.radioeng.cz/fulltexts/2014/14_01_0096_0103.pdf
Keywords
continuous wavelet transform track-before-detect target detection hmm electronics nuclear engineering sea clutterelectrical engineering

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