Research On Signal Identification And Position For 2.4GHz Frequency Band

The 2.4GHz frequency band is a public band commonly used in the world,and is currently widely used in household,commercial and industrial fields.Due to its open,unlicensed nature,several different common signals are often coexisted simultaneously on the 2.4 GHz band.In this situation the user experience are greatly effected,and it also brings unsafe factors.Therefore,it is necessary to identify and locate the common signals existing in the 2.4GHz frequency band.Since the birth of signal recognition technology,academia and industry have developed a mature system that can meet the needs of most situations;however,the existing signal recognition technology has high requirements for the sampling process,which brings a lot of system overhead and is a huge challenge to the system.Therefore,this paper proposes a high-speed,high-recognition,low-overhead signal recognition and positioning algorithm.At the same time,the support vector machine theory is introduced to further improve the recognition performance.The main work completed in this article includes:Firstly,the common signals in the 2.4GHz band are summarized and analyzed,and the types and parameters of common signals are introduced and analyzed.Secondly,theoretical analysis and simulation verification of existing signal recognition algorithms are carried out.Existing algorithms mainly construct the classifier by extracting modulation-related parameter information such as signal amplitude,frequency,and phase,or high-order cumulative information of the signal to complete the modulation recognition of the signal.This paper analyzes and simulates the existing algorithm principles.Then,a signal recognition algorithm based on the signal frame length and frequency spectrum is proposed.This paper analyzes and demonstrates that the existing algorithms are difficult to use in the 2.4GHz band signal identification,and proposes a new identification algorithm.The proposed algorithm builds a classifier based on the frame length and spectrum characteristics of the signal,which can effectively identify the common signal types in the 2.4GHz frequency band.The recognition rate is up to 90%,and for some signals it can reaches 100%.The proposed algorithm has a strong adaptability and low calculation complexity,which is conducive to real-time monitoring and classification.Furthermore,a signal classification algorithm based on support vector machine is proposed.As an emerging intelligent pattern recognition algorithm,support vector machine is widely used in various classification scenarios.In this paper,based on support vector machine theory,and using some feature parameters as training samples to train the classification plane,the signal recognition rate is further improved.Finally,a triangular positioning and centroid algorithm based on Received Signal Strength Indicator(RSSI)is proposed to achieve accurate positioning of the signal source.The triangular positioning algorithm based on RSSI has the advantages of low calculation cost and high positioning accuracy.In this paper,the centroid algorithm is introduced to further improve the positioning accuracy.