Title :
Boat-generated acoustic target signal detection by use of an Adaptive Median CFAR and multi-frame integration algorithm
Author :
Cheng, Eric Dahai ; Piccardi, Massimo ; Jan, Tony
Author_Institution :
Dept. of Comput. Syst., Univ. of Technol., Broadway, NSW, Australia
Abstract :
In this paper, an Adaptive Median Constant False Alarm Rate (AMCFAR) and multi-frame post detection integration algorithm is proposed for effective real time automatic target detection of boat-generated acoustic signals, in which, an observation space is created by sampling and dividing input analog acoustic signal into multiple frames and each frame is transformed into the frequency domain. In the created observation space, a Median Constant False Alarm Rate (MCFAR) and post detection integration algorithms have been proposed for an effective automatic target detection of boat generated acoustic signals, in which a low constant false alarm rate is kept with relative high detection rate. The proposed algorithm has been tested on several real acoustic signals from hydrophone sensors, and statistical analysis and experimental results showed it able to provide a very low false alarm rate and a relatively high detection rate in all cases.
Keywords :
acoustic signal detection; object detection; MCFAR; acoustic signal; adaptive median CFAR; adaptive median constant false alarm rate; automatic target detection; boat-generated acoustic target signal detection; frequency domain; hydrophone sensors; median constant false alarm rate; multiframe integration algorithm; multiframe post detection integration algorithm; post detection integration algorithms; real time automatic target detection; statistical analysis; Acoustics; Boats; Filtering algorithms; Frequency-domain analysis; Noise; Object detection; Vectors;
Conference_Titel :
Signal Processing Conference, 2005 13th European
Conference_Location :
Antalya
Print_ISBN :
978-160-4238-21-1