Fish stock quantity estimating method based on probability hypothesis density particle filtering algorithm

Abstract

The invention discloses a fish stock quantity estimating method based on a probability hypothesis density particle filtering algorithm; the method includes steps of (1), fixing dual-frequency identifying sonar; (2), performing underwater detection through wall navigation, and acquiring acoustic data; (3), processing the acoustic data, and counting the fish body by using the probability hypothesis density particle filtering algorithm; (4), calculating the volume of the sweeping water body, and solving the density of the fish stock; (5), according to the water storage of the known water domain, estimating the fish body number in the whole water domain. By using the probability hypothesis density particle filtering algorithm based on a random set theory, the fish body is counted one by one, and the fish stock number in the water body identified by dual-frequency and swept by sonar is counted; the method is simple and easy to practice, high-efficient and cannot damage the fish resource, and others; compared with the traditional method of integrating by using the target intensity, the method has higher precision, and provides a new way for the fish resource evaluation.

Description

technical field [0001] The invention belongs to the technical field of fishery resources assessment, and in particular relates to a method for estimating the number of fish schools based on a probability hypothesis density particle filter algorithm. Background technique [0002] The assessment of fishery resources is an important link in the process of modern fishery development, and the statistics of fish stocks is the most basic requirement of fishery resources assessment. The traditional method mainly relies on sampling fishing, which is harmful to the fish resources itself; or using a metering fish finder, using the echo integration method or echo counting method for measurement, which can only roughly estimate the number of fish schools, with large errors. Modern society puts forward higher requirements for improving the quality and output of fishery resources, effectively protecting marine ecosystems, and realizing the sustainable development of marine resources. For ...

AI Technical Summary

Problems solved by technology

The traditional method mainly relies on sampling fishing, which is harmful to the fish resources itself; or using a metering fish finder, using the echo integration method or echo counting method for measurement, which can only roughly estimate the number of fish schools, and the error is large

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