Positioning method based on time difference of arrival and dispensing with noise power information

Abstract

The invention provides a positioning method based on time difference of arrival and dispensing with noise power information. The positioning method comprises the following steps: converting a positioning equation of the time difference of arrival and the positioning equation of the frequency difference of arrival into a matrix equation of the time difference of arrival and the matrix equation of the frequency difference of arrival by importing a redundancy variable way, and extracting, separating and measuring the noise power component according to the covariance matrix of the time differenceof arrival measurement noise and the covariance matrix of the frequency difference of arrival measurement noise, and precisely solving location and speed of a to-be-positioned target by applying a positive semidefinite planning method, thereby precisely estimating the location and speed of the to-be-positioned target under the condition that the measurement noise power is unknown.

Description

technical field [0001] The invention relates to the technical field of wireless mobile communication, in particular to a positioning method based on time difference of arrival without noise power information. Background technique [0002] Passive positioning refers to the technology that the positioning party does not transmit signals itself, but locates the target by receiving the signal emitted or reflected by the target. Because the passive positioning system has the advantages of long detection distance, strong anti-interference ability and good concealment, it has been widely used in the fields of radar, sonar, electronic countermeasures, wireless communication and wireless sensor networks, and it is also a signal processing field. one of the important research contents. [0003] The main principle of passive positioning is to extract the positioning parameters from the signal sent by the target first, and then complete the target positioning by these positioning param...

AI Technical Summary

Problems solved by technology

Among them, the two-step weighted least squares algorithm is simple to calculate and has a closed-form solution, but when the intensity of the background noise is high, its positioning accuracy is very unsatisfactory; the Taylor series expansion algorithm and the restricted weighted least squares algorithm need Iteration, so it has certain requirements for the selection of the initial value and cannot guarantee to converge to the global optimal solution

The positive semi-definite programming algorithm has the best positioning accuracy, but its computational burden is heavy

In addition, the implementation of these algorithms relies on accurate noise power estimation. When the noise power cannot be accurately estimated or the estimation error is large, the positioning performance of these methods will be seriously deteriorated.

Since the noise power cannot be accurately estimated in practice, this defect severely restricts the practical application of these time-frequency-difference-of-arrival algorithms

[0005] At present, in the positioning research based on the time-of-arrival difference, there are few positioning researches that do not rely on the prior information of the noise power. Among the known algorithms, only the total least square method and the deviation correction method do not need to know the prior information of the noise power. information, but the positioning accuracy of these two methods is relatively low, and both methods have a serious "threshold effect": when the noise intensity reaches a certain level, the positioning error of the algorithm will increase sharply

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