Multi-target passive tracking method based on wireless sensor network

Abstract

The invention relates to a multi-target passive tracking method based on a wireless sensor network. The technical characteristics are that the multi-target passive tracking method based on the wireless sensor network comprises the following steps that: (1) a measurement model is established according to the receiving signal intensity of the sensor network; (2) according to the established measurement model from the step (1), the variable multi-target positioning and tracking is realized under the indoor environment through the combination of a multi-target Bernoulli filter algorithm and a particle filter algorithm. The multi-target passive tracking method based on the wireless sensor network provided by the invention is reasonable in design; the established measurement model has high accuracy under the indoor environment, and the model forecast value is approximate to the actual observation value; the target detecting and tracking algorithm has high accuracy and stability, and can detect and track a plurality of targets; and the measurement model and the target algorithm are appropriate in calculation complexity, and thus guaranteeing the running real-time performance of the tracking system.

Description

technical field [0001] The invention belongs to the technical field of wireless sensors, in particular to a multi-target passive tracking method based on a wireless sensor network. Background technique [0002] In recent years, the development of information technology and network technology has brought huge and profound changes to various fields of human society and national economy. The information network represented by the Internet has a greater and greater impact on people's lifestyles, and will continue to develop and increase its influence in various fields in the future. Wireless Sensor Networks (WSN) is a new type of network technology that integrates sensor technology, MEMS technology, wireless communication technology and distributed information processing technology. Through the collaboration between nodes, it senses, collects and processes the information of the environment or monitoring objects in the monitoring area in real time, and transmits the processed i...

AI Technical Summary

Problems solved by technology

This type of method has simple system configuration and high tracking accuracy, but there are still some limiting factors: First, the measurement model used in the existing model-based radio frequency tomography method is only suitable for outdoor single-target environments, and cannot deal with indoor environments, especially Indoor environments where multiple targets exist; secondly, due to the unique structure of the RSS passive tracking system, there is still no suitable filtering algorithm for multi-target positioning and tracking in the case of an uncertain number of targets

In summary, so far there is no effective algorithm for multi-target positioning and tracking based on RSS

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