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Passive positioning method based on regularization constraint weighted least square

A weighted least squares, passive positioning technology, applied in design optimization/simulation, radio wave measurement system, reflection/re-radiation of radio waves, etc., can solve problems such as ill-conditioned

Active Publication Date: 2021-08-31
HARBIN ENG UNIV
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Problems solved by technology

However, due to the interference of noise, the distribution of receiving stations and target positions, and the influence of the number of receiving stations on the coefficient matrix, the coefficient matrices in the above methods based on CWLS and CTLS models may have ill-conditioned problems in practical applications

Method used

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  • Passive positioning method based on regularization constraint weighted least square
  • Passive positioning method based on regularization constraint weighted least square
  • Passive positioning method based on regularization constraint weighted least square

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Embodiment Construction

[0054] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0055] A positioning method based on regularized constrained total least squares, specifically including:

[0056] (1) if figure 1 As shown, M receiving stations are used to locate the moving target radiation source in three-dimensional space, and the position and velocity of the target radiation source are respectively u o =[x,y,z] T , The position and velocity of the i-th receiving station are respectively s i =[x i ,y i ,z i ] T , Then the real distance between the receiving station and the target radiation source can be expressed as:

[0057]

[0058] Select any one of the receiving stations as the main station, numbered as 1, and the rest of the receiving stations are auxiliary stations, then the real distance difference between the main station and each auxiliary station is:

[0059]

[0060] in Calculated fr...

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Abstract

The invention provides a passive positioning method based on regularization constraint weighted least square. The method is divided into two steps, in the first step, a positioning model based on the RCTLS thought is established for the TDOA / FDOA positioning problem, regularization parameters are solved based on the criterion of the minimum mean square error, and then a closed analytical solution of the model is given through mathematical derivation; and in the second step, an equation about the estimation error of the first step is established by using constraint conditions, then solving is carried out, and finally the estimation result of the first step is corrected by using the obtained solution. According to the method, the positioning precision of the positioning method based on the CTLS model can be improved, and the performance is more stable under the condition that the coefficient matrix is ill-conditioned.

Description

technical field [0001] The invention relates to the field of passive radar positioning, which can estimate the position and speed of moving targets in real time in the military and civilian fields, and specifically relates to a TDOA / FDOA passive positioning method based on regularized constraint weighted least squares. Background technique [0002] At present, multi-station passive positioning technology has been widely used in various military and civilian fields, such as sensor network, radar, navigation and so on. The observations that can be used by multi-station passive positioning technology mainly include angle of arrival (Angel of Arrival, AOA), time difference of arrival (Time Difference of Arrival, TDOA), frequency difference of arrival (Frequency Difference of Arrival, FDOA), etc. [0003] The positioning system combining different measurement parameters can combine the advantages of different parameters and improve the positioning accuracy to a certain extent. Th...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S13/06G01S13/58G06F17/16G06F30/20
CPCG01S13/06G01S13/58G06F17/16G06F30/20
Inventor 国强李文韬王亚妮戚连刚乔勒纳果勒·列昂尼德尼古拉·卡留日内刘立超
Owner HARBIN ENG UNIV
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