Submarine Detection (Sensor Level)

 





 



Acoustic sensors are the primary sensor of choice to detect threat submarines operating below periscope depth. However, the increasingly quieter nuclear threat and the diesel-electric-on-battery threat limits traditional narrow-band processing, yielding shorter detection ranges and requires more array gain via more sensors and adaptive signal processing to counter the quieting trends. One of the key functionalities of embedded sensor networks is to detect events of interest efficiently.
We have developed new technologies used for undersea submarine detection. Our system is based on the signal cluster trending analysis for submarine detection and statistical model for false alarm mitigation. We have tested our system with DADS data from six sensors placed in two sensor arrays. Based on our test results, we have been able to detect all the targets listed in the ground truth. The system developed in Phase I has three major components: (1) cluster trend construction, (2) abnormal event detection, and (3) false alarm mitigation. The test results have shown that we have been able to detect all targets given in the ground truth. 

 

 

 

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