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TDOA direct positioning method based on matrix eigenvalue disturbance

A positioning method and eigenvalue technology, which is applied in the field of single-target passive positioning scenarios based on TDOA, can solve the problems of weak multi-target resolution and difficulty in achieving asymptotic optimization, and achieves reduced computational complexity, good timeliness, and fast convergence speed. Effect

Active Publication Date: 2019-12-31
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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Problems solved by technology

However, a large number of research experiments have shown that the traditional two-step positioning method has data association problems such as difficulty in achieving asymptotic optimality and weak multi-target resolution.

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  • TDOA direct positioning method based on matrix eigenvalue disturbance
  • TDOA direct positioning method based on matrix eigenvalue disturbance
  • TDOA direct positioning method based on matrix eigenvalue disturbance

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Embodiment Construction

[0038] The present invention will be further explained below in conjunction with accompanying drawing and specific embodiment:

[0039] like figure 1 As shown, a TDOA direct location method based on matrix eigenvalue perturbation includes:

[0040] Step S101: M observation stations synchronously receive the signal radiated by the target signal source, and aggregate the received signal to the central station;

[0041] Step S102: generating a Sinc interpolation function matrix, and establishing a signal model about TDOA parameters through the Sinc interpolation function matrix;

[0042] Step S103: using the signal model about TDOA parameters to establish a maximum likelihood optimization function about the target position;

[0043] Step S104: Obtain the gradient vector and Hessian matrix of the maximum likelihood optimization function based on the matrix eigenvalue perturbation method;

[0044] Step S105: Set iteration conditions, and use the Newton iteration method to optimi...

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Abstract

The invention discloses a TDOA direct positioning method based on matrix eigenvalue disturbance, comprising the following steps: M observation stations synchronously receive signals radiated by a target signal source, and gather the received signals to a central station; a Sinc interpolation function matrix is generated, and a signal model about TDOA parameters is established through the Sinc interpolation function matrix; an optimization function about the maximum likelihood of a target position is established by using the signal model about the TDOA parameters; a gradient vector and a Hessian matrix of the optimization function about the maximum likelihood are obtained based on a matrix eigenvalue disturbance method; and an iteration condition is set, and optimization is carried out by using a Newton iteration method based on the gradient vector and the Hessian matrix to obtain a final target position estimation result. The method can improve the positioning estimation precision under a low signal-to-noise ratio, and is of high reliability and practical application value.

Description

technical field [0001] The invention belongs to the technical field of wireless signal positioning, and relates to a TDOA direct positioning method based on matrix eigenvalue disturbance, in particular to a TDOA-based single target passive positioning scenario. Background technique [0002] Wireless signal positioning technology is of great significance in both civil and military fields. Because of its great role in electronic countermeasures, it is a research project that various countries attach great importance to. After decades of research and development, the passive positioning method is divided into two-step positioning from the positioning method (M.Wax, T.Kailath, "Decentralized processing in sensor arrays." IEEE Transactions on Acoustics Speech & Signal Processing.33.5(1985): 1123–1129.) and direct positioning (Wang Yunlong, Wu Ying. An improved direct positioning algorithm combined with time delay and Doppler frequency [J]. Journal of Xi'an Jiaotong University, 20...

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Application Information

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IPC IPC(8): G01S5/04
CPCG01S5/04
Inventor 杨泽宇王鼎唐涛杨红霞杨宾王成魏帅李建兵张光伟韩博臣
Owner PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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