Dr. Garfield R. Mellema Profile

Dr. Garfield R. Mellema

at Defense R&D Canada

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Proceedings Article | 19 May 2006 Paper

Improving the passive sonar picture through reverse-time tracking

Garfield Mellema

Proceedings Volume 6236, 62360O (2006) https://doi.org/10.1117/12.668907

KEYWORDS: Signal detection, Sensors, Acoustics, Passive sonar, Signal processing, Target detection, Data acquisition, Receivers, Data conversion, Data processing

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Passive sonar depends on signals of opportunity to detect, track, and localize targets. These signals, typically from the target itself, are often very weak relative to the ambient sound levels, making them difficult to detect and track, resulting in a sonar picture cluttered with many intermittent track segments. An accurate estimate of the position, course, and speed of a target depends on the characteristics, including duration, of the available track. In early sonar systems, where operators detected signals visually and tracked them manually, the time of detection was ambiguous since operators searched for repetitive events and visually followed them as far backward as possible. In modern tracking systems using an m out of n detector, the arrival of the m^th event is considered the time of detection. A tracker is initiated at this time and updated as new data is acquired. Data prior to the detection is discarded and localization is delayed until sufficient post-detection data has been acquired to produce a suitable track often tens of minutes later. Initiating a second tracker in reverse time can reduce the localization delay by gleaning additional track information from the acoustic data acquired prior to the time of detection and often prior to the data that triggered the detection. Implementing reverse-time tracking requires a large data cache and significant processing power as well as data association to fuse sequential and/or concurrent forward-time and reverse-time tracks, but it can be an effective tool to rapidly extract additional information from narrowband passive sonar data.

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