RSSD-based 3-D localization of an unknown radio transmitter using weighted least square and factor graph

Liyang Zhang,Taihang Du,Chundong Jiang

doi:10.1186/s13638-018-1329-5

Abstract

Realizing accurate detection of an unknown radio transmitter (URT) has become a challenging problem due to its unknown parameter information. A method based on received signal strength difference (RSSD) fingerprint positioning technique and using factor graph (FG) for 2-D scenario has been developed. However, the URT positioning under 3-D scenario is more difficult with the large number of unknown parameters and has greater practical significance. In addition, the previous RSSD-based FG model is not accurate enough to express the relationship between the RSSD and corresponding location coordinates since the RSSD variances of reference points are different in practice. This paper proposes a more accurate 3-D FG model to reduce the influence of difference of RSSD measurement variances on positioning accuracy effectively by utilizing weighted least square (WLS). With the proposed RSSD-based 3-D WLSFG model and sum-product rule, positioning process of the proposed 3-D RSSD-WLSFG algorithm is derived. To verify the feasibility of the proposed method, we also explores the effects of different signal receiver numbers and grid distances on positioning accuracy. The simulation experiment results show that the proposed algorithm can obtain the best positioning performance compared with the conventional K nearest neighbor (KNN) algorithm and RSSD-FG algorithm under different grid distances and signal receiver numbers.

Highlights

A variety of radio signals have been widely used and existed in our daily life
The basic principle of K nearest neighbor (KNN) approach is to calculate the location of positioning target by averaging locations of K reference points with the minimum received signal strength (RSS) Euclidean distance found in the fingerprint database
The following are the contributions of this paper: 1) A more accurate received signal strength difference (RSSD)-based 3-D WLSFG model was first constructed by combining the factor graph (FG) technique with weighted least square (WLS) for an unknown radio transmitter (URT), which can effectively reduce the impact of differences in variance of RSSD at different reference points on positioning accuracy

Summary

Introduction

A variety of radio signals have been widely used and existed in our daily life. A robust fingerprint database based on received signal strength difference (RSSD) was first proposed to eliminate the influence caused by the difference between the testing devices and training devices in [24]. We combine the RSSD-based FG fingerprint positioning technique and WLS method to propose a new 3-D RSSD-WLSFG algorithm, and it is considered to be an effective method for detecting an URT in 3-D space. The following are the contributions of this paper: 1) A more accurate RSSD-based 3-D WLSFG model was first constructed by combining the FG technique with WLS for an URT, which can effectively reduce the impact of differences in variance of RSSD at different reference points on positioning accuracy.

The principle and system model

Proposed 3-D RSSD-WLSFG algorithm

Soft-information calculation and iteration process

Results and discussion

Performance comparison of different grid distances and AP numbers

Conclusions