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Deep clustering based polar coordinate dynamic programming passive coherent location method

A dynamic programming algorithm and dynamic programming technology, applied in the directions of positioning, radio wave measurement systems, measurement devices, etc., can solve the problems of long algorithm time and high algorithm complexity, and achieve improved running time, low algorithm complexity, and improved target tracking. performance effect

Active Publication Date: 2017-08-18
北京莞安科技有限公司
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Problems solved by technology

[0004] The algorithm proposed in the above literature takes a long time and has high algorithm complexity

Method used

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  • Deep clustering based polar coordinate dynamic programming passive coherent location method
  • Deep clustering based polar coordinate dynamic programming passive coherent location method
  • Deep clustering based polar coordinate dynamic programming passive coherent location method

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Embodiment Construction

[0041] The present invention is further analyzed below in conjunction with specific examples.

[0042] The basic idea of ​​the PCL positioning algorithm based on DC-DP-SA is: for the measurement data in polar coordinates, the evaluation function is constructed through the DC-DP-TBD algorithm, and the amplitude accumulation and track backtracking are performed on the evaluation function. Theory (Error Propagation, EP) creates a new space transfer expansion and contraction amount, thereby optimizing the effective state transfer range of DP-TBD in the nonlinear measurement space, and at the same time determining the backtracking threshold of DP-TBD in the extreme value theory (Extreme Value Theory, EVT) Add an anti-interference factor to optimize the stability of the threshold. Then use the SA method to incorporate the state of the radiation source into the target state, and use the extended Kalman filter algorithm based on the correlation prediction to prevent errors to perform ...

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Abstract

The invention provides a deep clustering based polar coordinate dynamic programming passive coherent location method. The method comprises the steps of firstly, providing a process of environment variable learning so as to be used for determining the expansion amount of space transfer, and solving an effective transfer range in a nonlinear measurement space by combining an error propagation theory; secondly, adding an anti-interference factor into a backtracking threshold determined according to an extreme value theory for the first time, and finally determining a backtracking threshold of a deep clustering based dynamic programming algorithm; thirdly, providing a deep clustering based dynamic programming algorithm, and performing target detecting and tracking in the measurement space; and finally, performing dimension augmentation on a target state, thus comprising the state of a radiation source, providing an interaction prediction covariance based extended Kalman filtering algorithm, and performing joint estimation on the augmented state.

Description

technical field [0001] The invention belongs to the field of target detection and tracking, and relates to a deep clustering-based polar coordinate dynamic programming passive cooperative positioning algorithm (Deep Clustering-Dynamic Programming-State Augmentation, DC-DP-PCL). Background technique [0002] Passive Coherent Location (PCL) technology means that the radar as the receiving source does not emit high-power electromagnetic waves, and uses the electromagnetic wave signals emitted by a third-party non-cooperative external radiation source (airborne early warning aircraft, etc.) to detect and track targets. Compared with the traditional active radar, the PCL system has low cost, strong anti-stealth characteristics, quietness and strong survivability. At the same time, the PCL system can solve the problem that traditional passive positioning cannot locate when the target is silent, and has received extensive and continuous attention from scholars at home and abroad. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S5/00G06K9/62
CPCG01S5/00G06F18/2321
Inventor 郭云飞张沛男薛安克彭冬亮左燕
Owner 北京莞安科技有限公司
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