An Image Compression Approach to Cooperative Processing for Swarming Autonomous Underwater Vehicles

Current wireless underwater communication technologies—i.e. underwater acoustic modems—are extremely bandwidth limited as compared to land-based wireless technologies. Additionally, acoustic modem technologies are not advancing at the same high rate as computing technologies. Therefore, it is proposed that image compression techniques be applied to sonar maps. This will both reduce the amount of information that must be transferred by these modems which in turn reduces the amount of time required to send information across acoustic channels. After compression is performed on one platform's map, the information is transformed into the coordinate system of the uncompressed second, non-collocated platform's map and the two maps are additively compared. If returns are common in both maps, they will be show up with higher energy than the individual maps' returns. This thesis proves that application of image compression techniques on range-angle maps allow for target detection, down to a minimum target strength value of 0 dB, independent of target return strength.