TR 2010-136 A1b
Defence Research and Recherche et d?veloppement Development Canada pour la d?fense Canada
Copy No. _____
DEFENCE
&
D?FENSE
Aural classification and temporal robustness
Stefan M. Murphy Paul C. Hines
Defence R&D Canada ? Atlantic
Technical Report DRDC Atlantic TR 2010-136
November 2010
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Aural classification and temporal robustness
Stefan M. Murphy Paul C. Hines
Defence R&D Canada ? Atlantic
Technical Report DRDC Atlantic TR 2010-136 November 2010
Principal Author
Original signed by Stefan M. Murphy
Stefan M. Murphy Defence Scientist
Approved by
Original signed by Garry Heard for
Daniel Hutt Head/Underwater Sensing
Approved for release by
Original signed by Ron Kuwahara for
Calvin Hyatt Head/Document Review Panel
? Her Majesty the Queen in Right of Canada, as represented by the Minister of National Defence, 2010
? Sa Majest? la Reine (en droit du Canada), telle que repr?sent?e par le ministre de la D?fense nationale, 2010
Abstract
Active sonar systems are used to detect underwater manmade objects of interest (targets) that are too quiet to be reliably detected with passive sonar. In coastal waters, the performance of active sonar is degraded by false alarms caused by echoes returned from geological seabed structures (clutter) found in these shallow regions. To reduce false alarms, a method of distinguishing target echoes from clutter echoes is required. Research has demonstrated that perceptual signal features similar to those employed in the human auditory system can be used to automatically discriminate between target and clutter echoes, thereby improving sonar performance by reducing the number of false alarms.
An active sonar experiment on the Malta Plateau was conducted during the Clutter07 sea trial and repeated during the Clutter09 sea trial. Broadband sources were used to transmit linear FM sweeps (600?3400 Hz) and a cardioid towed-array was used as the receiver. The dataset consists of over 95 000 pulse-compressed echoes returned from two targets and many geological clutter objects.
These echoes are processed using an automatic classifier that quantifies the timbre of each echo using a number of perceptual signal features. Using echoes from 2007, the aural classifier is trained to establish a boundary between targets and clutter in the feature space. Temporal robustness is then investigated by testing the classifier on echoes from the 2009 experiment.
Re? sume?
Les sonars actifs servent a` de?tecter sous l'eau des objets d'inte?re^t artificiels (cibles) trop silencieux pour e^tre de?tecte?s efficacement par un sonar passif. En eaux co^tie`res, les e?chos provenant de structures ge?ologiques du fond marin (clutter) causent des fausses alarmes qui alte`rent les performances des sonars actifs dans ces eaux peu profondes. Une me?thode permettant de distinguer les e?chos de cibles et les e?chos de clutter est ne?cessaire pour re?duire le taux de fausses alarmes. Des recherches ont montre? que des caracte?ristiques perceptuelles du signal, semblables a` celles utilise?es par l'oreille humaine, peuvent servir a` distinguer automatiquement entre les e?chos des cibles et le clutter, ce qui permet d'ame?liorer le rendement du sonar en re?duisant le nombre de fausses alarmes. Une expe?rience a e?te? effectue?e au moyen d'un sonar actif sur le plateau de Malte au cours des essais en mer Clutter07 et Clutter09. Des sources a` large bande ont servi a` e?mettre des balayages FM line?aires (de 600 a` 3 400 Hz), et un re?seau remorque? cardio?ide a servi de re?cepteur. L'ensemble de donne?es est compose? de plus de 95 000 e?chos a` compression d'impulsion provenant de cibles actives et de nombreux objets ge?ologiques produisant le clutter.
Les e?chos sont traite?s a` l'aide d'un classificateur auditif automatique qui quantifie la sonorite? de chaque e?cho a` partir d'un nombre de caracte?ristiques perceptuelles du signal. On
DRDC Atlantic TR 2010-136
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