Positioning method based on signal arrival time

Abstract

The invention discloses a positioning method based on signal arrival time. The method includes the steps that first, a nonlinear positioning problem is converted to a multiple integration problem; second, in the process of converting the nonlinear positioning problem to the multiple integration problem, a Gaussian distribution function is constructed according to the position of each base station, the measurement noise variance of signals of each base station and the distance between a terminal to be positioned and each base station in a cellular mobile network environment; third, several samples are randomly drawn from the Gaussian distribution function; fourth, the position of the terminal to be positioned is acquired according to the drawn samples. The method has the advantages that the constructed Gaussian distribution function can improve multiple integral computation efficiency and integral value precision, besides, the accurate position of the terminal to be positioned can be acquired by drawing only a few samples in the process of solving the multiple integration problem, and computation complexity is low.

Description

technical field [0001] The invention relates to a positioning method, in particular to a positioning method based on signal arrival time. Background technique [0002] In the research of radar and sonar, terminal location is a classic research topic. In the past 30 years, especially after the 911 incident, people have higher and higher requirements for terminal positioning, so terminal positioning has received more and more attention. Terminal positioning technology has broad application prospects in military reconnaissance, traffic monitoring, industrial and agricultural control, biomedicine, environmental monitoring, emergency rescue and remote control of dangerous areas, etc., so it is of great significance to study positioning methods. Figure 1 shows a schematic diagram of a typical positioning problem. By measuring the downlink pilot signals of different base stations, the terminal to be positioned can obtain the TOA (Time of Arrival, Time of Arrival) or TDOA (Time Dif...

AI Technical Summary

Problems solved by technology

Aiming at the problems existing in the linearization method based on Taylor expansion, people proposed the spherical interpolation (Spherical Interpolation, SI) method, which linearizes the nonlinear equation system by introducing an intermediate variable. The intermediate variable set is not desired. However, the relationship between it and the position of the terminal to be located is known. This method solves the linear equation system based on the Linear Least Squares (LLS) criterion, but completely ignores the known relationship between the intermediate variable and the terminal position mentioned above. relationship, resulting in inaccurate location of the terminal to be located

In order to improve the performance of the SI method, a Two-Stage Weighted Least Squares (Two-Stage WLS) method is proposed, which explicitly considers the relationship between the intermediate variable and the location of the terminal to be located , so it can achieve better performance than the SI method, but this method has a threshold effect, that is, when the noise in the measurement reaches a certain level, the positioning accuracy will drop sharply

In recent years, people have tried to use some nonlinear programming theories to solve the positioning problem. Due to the non-convex nature of the positioning problem, people have tried to use relaxation methods to relax the non-convex problem into a convex problem (such as semi-positive definite programming). After solving the convex problem, Then use some follow-up processing methods to obtain the approximate solution of the original positioning problem. This method is characterized by the high accuracy of the position of the terminal to be located, but the complexity of the algorithm is much higher than that of the linearization method.

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