Research on Nonline-of-Sight Positioning Method of Intelligent Mobile Terminal Based on Intelligent Monitoring Architecture of Multimedia Sensor Network

Jianjun Liu

doi:10.1155/2021/6008458

Abstract

With the continuous development of social economy, information resources have become more and more valued resources. Based on the intelligent monitoring architecture of the multimedia sensor network, this article proposes a nonline-of-sight positioning method that can fit the characteristics of autonomous movement for the object of intelligent terminal, that is, first draw the corresponding position trajectory according to the speed attribute of the node. On this basis, according to the relative position trajectory and radio frequency signal positioning, the two-by-two positioning of position and direction is comprehensively realized, and the positioning result is obtained; the positioning accuracy is evaluated according to the positioning of the radio frequency signal, and the false positioning result of the distorted radio frequency signal is stripped out to reduce the error influences. Practical results show that the method is effective and can meet the needs of positioning accuracy.

Highlights

With the development of society and economy, information resources have become more and more valued resources, and location information has become more and more important
With distributed computing technology or wireless signaling technology, positioning based on WiFi and mobile phone signals has become a new way and new means of location information acquisition [7,8,9,10]. e focus is on the avoidance and handling of a large number of obstacles, because this may lead to a decrease in the accuracy of the position accuracy
Aiming at the intelligent monitoring architecture of the multimedia sensor network, this paper combines video, infrared, and other diversified sensor device data to obtain the characteristics of related targets from multiple angles and aspects, forming a diversified feature space dimension, which is more conducive to target identification and extraction [11]. e specific fusion is shown in Figure 1. rough the fusion of image, video, and other data, the characteristics of the target are associated, and the target characteristics are extracted into a vector file for recognition of the target characteristics

Summary

Introduction

With the development of society and economy, information resources have become more and more valued resources, and location information has become more and more important. In the world of intelligent connection of all things, autonomously connected mobile nodes have been more and more used in areas such as manual input or GPS, BEIDOU receiver for position positioning. This part will be restricted by the module, and the positioning accuracy will be insufficient due to the influence of nonviewing distance factors. With distributed computing technology or wireless signaling technology, positioning based on WiFi and mobile phone signals has become a new way and new means of location information acquisition [7,8,9,10]. With distributed computing technology or wireless signaling technology, positioning based on WiFi and mobile phone signals has become a new way and new means of location information acquisition [7,8,9,10]. e focus is on the avoidance and handling of a large number of obstacles, because this may lead to a decrease in the accuracy of the position accuracy

Methods

Results

Conclusion