Terminal Cluster Indoor Positioning Method Based on Time-Frequency Analysis

The method of indoor positioning of terminal cluster based on time-frequency analysis is proposed, which uses time-frequency domain to characterize and analyze signals, and gets rid of the limitation of traditional single time-domain or frequency-domain description of signal characteristics. The time domain and frequency domain are combined to describe and observe the time-frequency characteristics of the signal, and how the spectrum content of the signal changes with time is analyzed through the time spectrum diagram. The hybrid precoding based on geometric mean decomposition is introduced to decompose the channel matrix into channels with the same diagonal element values. All diagonal element values are equal to the geometric mean of the eigenvalues of the channel matrix, so that the subchannel can obtain equal gain and avoid complex bit allocation. Finally, the weighted distance vector hop ranging method is adopted, and the signal intensity factor is introduced to weight the minimum hop number and average hop distance, so as to reduce the error caused by the minimum hop number and average hop distance in the conventional distance vector hop section.

I. Introduction

With the rapid increase of data services and multimedia services, people have increasing demands for positioning day by day. Especially in complex indoor environments, such as airport halls, supermarkets, libraries and underground parking lots, it is often necessary to determine the indoor position information of mobile terminals or mobile terminal holders, facilities and articles [1], [2], [3]. At present, most of positioning algorithms only focus on the research for wireless two-dimensional networks. However, in practical application, wireless network nodes may also be often in a three-dimensional environment. In these occasions, it is necessary to provide three-dimensional position information of the mobile terminals. At present, researchers have proposed many various indoor positioning solutions based on radio frequency identification.