%0 Journal Article %1 cheng2018marine %A Cheng, Dahai %D 2018 %J Signal Processing: An International Journal (SPIJ) %K (ACFAR) Acoustic Adaptive Alarm Constant Detection, Domain, False Multi-frame Processing, Rate Signal Signature Spectrum Target Time-Frequency %N 1 %P 19-46 %T Marine Vehicle Spectrum Signature Detection Based On An Adaptive CFAR and Multi-Frame Fusion Algorithms %U http://www.cscjournals.org/library/manuscriptinfo.php?mc=SPIJ-287 %V 12 %X Detecting marine vehicle spectrum signature from hydrophone at low false alarm rate and high detection rate in an environment of various interference is a very difficult problem. To overcome this problem, an observation space is created by sampling and dividing input analog acoustic signal into digital signal in multiple frames and each frame is transformed into the frequency domain; then an Adaptive Constant False Alarm Rate (ACFAR) and Post Detection Fusion algorithms have been proposed for an effective automatic detection of marine vehicle generated acoustic signal spectrum signature. The proposed algorithms have been tested on several real acoustic signals. The statistical analysis and experimental results showed that the proposed algorithm has kept a very low false alarm rate and extremely high detection rate.

@article{cheng2018marine, abstract = {Detecting marine vehicle spectrum signature from hydrophone at low false alarm rate and high detection rate in an environment of various interference is a very difficult problem. To overcome this problem, an observation space is created by sampling and dividing input analog acoustic signal into digital signal in multiple frames and each frame is transformed into the frequency domain; then an Adaptive Constant False Alarm Rate (ACFAR) and Post Detection Fusion algorithms have been proposed for an effective automatic detection of marine vehicle generated acoustic signal spectrum signature. The proposed algorithms have been tested on several real acoustic signals. The statistical analysis and experimental results showed that the proposed algorithm has kept a very low false alarm rate and extremely high detection rate.}, added-at = {2018-12-12T07:50:26.000+0100}, author = {Cheng, Dahai}, biburl = {https://www.bibsonomy.org/bibtex/298d2d73a14ac7fd9f5341790d42feb2c/cscjournals}, interhash = {8cff1293f43d8ba19160f5a0630cc02f}, intrahash = {98d2d73a14ac7fd9f5341790d42feb2c}, issn = {1985-2339}, journal = {Signal Processing: An International Journal (SPIJ)}, keywords = {(ACFAR) Acoustic Adaptive Alarm Constant Detection, Domain, False Multi-frame Processing, Rate Signal Signature Spectrum Target Time-Frequency}, language = {English}, month = {April}, number = 1, pages = {19-46}, timestamp = {2018-12-12T07:50:26.000+0100}, title = {Marine Vehicle Spectrum Signature Detection Based On An Adaptive CFAR and Multi-Frame Fusion Algorithms}, url = {http://www.cscjournals.org/library/manuscriptinfo.php?mc=SPIJ-287}, volume = 12, year = 2018 }