Target tracking and identification device and method based on entropy-weighted gray correlation

Abstract

The invention provides target tracking and identification device and method based on entropy-weighted gray correlation. The target tracking and identification device comprises a sensor network, a serial port chip, a field programmable gate array (FPGA), a digital signal processor (DSP) and a synchronous dynamic random access memory (SDRAM), wherein the DSP is used for carrying out entropy weighting, gray correlation, target state updating and target identification to data; the FPGA is used for preprocessing the data transmitted by the serial port chip and controlling the communication of the DSP and the serial port chip; the serial port chip is used for transmitting the data of the sensor network to the FPGA; and the SDRAM is used for storing target tracking and identifying results. The invention obtains the entropy-weighted gray correlation by utilizing target feature information provided by the sensor network to carry out state updating and identity identification to targets, and can still track and identify the targets under the condition that the sensor generates failures or the targets are lost.

Description

Target tracking and recognition device and method based on entropy weight gray relation technical field The invention relates to a target tracking and identification technology. Specifically, it is a target tracking and recognition device based on a sensor network. The invention also relates to a target tracking and identification method. Background technique The tracking and recognition of targets is one of the main uses of sensor networks, and it is also a difficult and key issue. It has broad application prospects in many fields such as traffic monitoring, agency security, and battlefield situation acquisition. Great progress has been made in single-sensor motion target tracking and recognition, and many classic algorithms have been obtained, such as the nearest neighbor method (NN), set theory description method, generalized correlation method, classical distribution method, multiple hypothesis method, probability Data association (PDA) method, joint data interconne...

AI Technical Summary

Problems solved by technology

However, due to the limitations of many hardware resources in sensor nodes, they are often affected by external environmental interference, the wireless link is susceptible to interference, and the network topology changes dynamically, while the moving target tracking and recognition applications of sensor networks have strong real-time performance requirements, therefore, many traditional tracking and identification algorithms are not suitable for sensor networks

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