Hidden Markov based target detection for track-before-detect

A tracking filter using conventional methods perform target detectios by setting a threshold at the output of the sensor´s signal processor. The result of using thresholding brings out that, targets with low signal-to-noise ratio (SNR) may not be detected if the signal power is below the required threshold. Track-before-detect (TBD) techniques avoid the usage of a detection threshold and provide detecting and tracking targets with lower signal-to-noise ratios. 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 Hidden Markov Model (HMM) based target detection method for employing with TBD techniques which does not use any of the thresholding method.