Naval mines are one of the greatest threats faced by any navy, especially in the current age of asymmetrical warfare. For only a few ten thousands of dollars, a mine can by built and placed that is capable of crippling or even sinking a multimillion dollar warship. De-mining operation are also notorious difficult and expensive. So much so, that there are even some naval mine field from the second world war still standing – being cheaper to simply route ships around them. The United States Navy considers improving its ability to de-mine a stretch of water a top priority, since the supply chain for any large ground operation will rely on the safe and continued operation of at least one harbor.
De-mining a stretch of ocean is particularly difficult. Unlike land mines, ocean mines can drift, be placed much deeper beneath the surface, and the triggers of naval mines can be much more selective and complex. This means that it is not only difficult to find a mine in the first place, but to re-acquire the mine for identification, and again for actual disarmament.
If a better search algorithm can be derived, then the cost of de-mining operations can be reduced. Ideally the algorithm would allow an autonomous vehicle to search a field, while minimizing the total distance the probe needs to travel, and recording the water currents at the time a mine is detected. Such a method would minimize risk to equipment and personnel, and minimize the amount of time and man hours to clear a field.
Using Matlab and R, we were able to minimize the search time of a virtual mine field, without sacrificing detection rates.
