Error Correction Decoding for Underwater Acoustic Tag Detection
This paper presents a decoding method applied to a set of underwater acoustic tags that employ very short signal beacons periodically transmitted. The tags use the CRC8- Dallas linear block code for error detection originally. Though the CRC8-Dallas is quite weak, syndrome-based error correction is applied to correct the decoding errors. Meanwhile, multi-channel array receivers are utilized to find the common decodes of the tag IDs, and the list of the true tag IDs is used to test the detection accuracy and false alarm rate. The proposed syndrome decoding method is applied to over 2 million files recorded in field experiments. The results demonstrate that the syndrome method yields around 9.85% more true positive decodes at the cost of a 2 - 5 times increase in false positive rates. Further insights are also gained to enable future improvement of the detection algorithms