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Fish and mammals have an enormous impact on marine ecosystems. A proper estimation of their population size is necessary, not only for their ecological values but also for commercial purposes. Most conventional techniques for estimating fish population are visual sampling techniques, the environmental DNA (eDNA) technique, minnow traps, the removal method of population estimation, and echo integration techniques, all of which are sometimes complex and costly, require human interaction, and can be harmful for marine species. In order to overcome these limitations, in this paper, a passive acoustic fishery monitoring technique is proposed as an alternative. The method is based on a statistical signal processing technique called “cross-correlation” and different types of sounds—namely, chirps, grunts, growls, clicks, and so forth—produced by fish and mammals. Our goal was not only to propose an efficient technique for fish population estimation but also to measure its performance for different fish sounds by using numerical simulations. From the analyses of simulated results, we found that the chirp sound-generating species produced better results than the other two types of sound-generating species—the grunt- and growl-generating species.

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