A Signal Processing Approach of Fish Abundance Estimation in the Sea

This paper investigates a signal processing approach of fish abundance estimation in the Sea. There is a high demand for underwater fish estimation due to the increase in current importance of sea fishes. These increase our knowledge about the state of a stock and improve assessment of many commercially valuable fish species. The conventional techniques used to estimate fishes in sea are visual sampling technique, RFID tag system, minnow traps etc., are human interactive and complex and the devices used for this technique are very costly. This paper presents an in-depth overview of cross-correlation technique which is an essential statistical tool in various fields of interest in signal processing. It has been used in communication networks to identify and localize nodes and for angle of arrival (AOA) estimations of signals from the nodes in a Wireless Sensor Network (WSN). Here the cross-correlation technique is used to estimate number of fishes in the sea. The fishes in the sea are considered the source of Chirp Signal for this estimation technique. The proposed theory has been verified by simulation in Matlab programming environment.