Multi-variety multi-objective passive locating method based on migration compression perception

Abstract

The invention discloses a multi-variety multi-objective passive locating method based on migration compression perception. The method specifically comprises the following steps: 1, deploying a sensor node; 2, collecting data to prepare for transfer function determination; 3, determining transfer functions of different varieties and objectives; 4, transferring a perception matrix by using the transfer function obtained in the step 3; 5, locating the objectives. The method disclosed by the invention can meet needs of sparse network deployment, low quantity of data acquisition and low energy consumption for wildlife conservation based on the migration compression perception. In comparison with the existing passive locating method, a locating model (perception matrix) is not required to be reconstructed for a newly emerged objective, and then high-precision locating can be finished. The locating method comprises the following outstanding advantages that reconstruction of the locating model, namely the perception matrix usually needs to cost a lot of manpower and material resources, however, the method disclosed by the invention can save the manpower and material resources, and meet the requirement for multi-variety multi-objective wildlife positioning.

Description

technical field [0001] The invention relates to the application of wireless networks, in particular to a multi-target passive positioning method for various wild animals. Background technique [0002] Wild animals have important ecological status and ecological functions in nature, and are one of the indispensable links in the entire ecological chain. How to effectively monitor and protect them is particularly important. Traditional wild animal protection uses manual recording and statistics. Therefore, the traditional method has many disadvantages, such as: lack of long-term and real-time performance, and also has certain difficulties and dangers. Comprehensive analysis of time, space and phenomena. The emergence of wireless sensor networks provides technical support for solving the above problems. [0003] The wireless sensor network is composed of a large number of distributed sensor nodes deployed in the monitored area. It integrates various technologies such as sensor...

AI Technical Summary

Problems solved by technology

However, the positioning model (perception matrix) of this method can only be used for the same type of target, and the positioning model (perception matrix) needs to be re-established for other types of targets.

[0012] To sum up, these three types of positioning methods do not take into account the diversity of wild animals (different types of targets have different shapes, resulting in different RSS interference, and it is necessary to establish an unventilated positioning model), that is, use one type of wild animal to establish The positioning model (the prior knowledge base of Zhang Dian et al., the tomographic image library of Joseph Wilson et al., the perception matrix of Fang Dingyi et al.), cannot be used to locate other types of wild animals

At the same time, it is extremely complicated, manpower-intensive, and unrealistic to establish a unique positioning model for each species of wild animals in reality. Therefore, passive positioning in the face of multiple types of wild animals requires new technologies to support

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