Multi-functional radar signal prediction mode based on predictive state representation model

A prediction method and radar signal technology, applied to radio wave measurement systems, instruments, etc., can solve problems such as complex MFR signals, achieve accurate prediction, reduce dependence, and have strong characterization capabilities

Inactive Publication Date: 2017-11-24
NAT UNIV OF DEFENSE TECH
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AI Technical Summary

Problems solved by technology

The prediction of MFR signal is very critical for realizing adaptive radar countermeasures, but in view of the complexity of MFR signal,

Method used

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  • Multi-functional radar signal prediction mode based on predictive state representation model
  • Multi-functional radar signal prediction mode based on predictive state representation model
  • Multi-functional radar signal prediction mode based on predictive state representation model

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Embodiment Construction

[0072] The present invention is applicable to MFR signal prediction. figure 1 It is a brief flow chart of the present invention, and the method proposed in the present invention will be further explained below in conjunction with the accompanying drawings. The specific steps and effects of this method are as follows:

[0073] Step 1: Establish the PSR model of MFR;

[0074] Since the reconnaissance system can only passively detect radar signals, the generation of radar word sequences is an uncontrolled process from the reconnaissance side's point of view. The PSR model of an uncontrolled system can be expressed as a quaternion :

[0075] O is the observation space, a finite discrete set containing all observations, an observation o∈O; it is experience, which refers to the observation sequence starting from the initial moment and ending at the current moment, h=o 1 o 2 ...o t ; e is the event, which refers to the observation sequence after the experience, e=o t+1 o t+2  ...

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Abstract

The invention relates to a multi-functional radar signal prediction mode based on a predictive state representation model. The method comprises the steps of (1) establishing a PSR model of MFR, (2) carrying out PSR model training, (3) carrying out MFR working mode posterior probability distribution estimation, and (4) carrying out MFR signal single-step and multi-step prediction. The method has the advantages that: (1) an MFR working identification and prediction problem is researched, the characterization ability of a dynamic system is stronger by using the PSR model, and the model is simple, (2) through extracting statistical amount information of training samples, landmarks and core events are used, and the dependence on MFR prior information is greatly reduced, and (3) the method has a strong application prospect, an MFR signal sequence can be accurately predicted, thus the dynamic analysis of the MFR working mode and scheduling strategy becomes possible, and a technical support is provided for the realization of adaptive radar countermeasure.

Description

【Technical field】 [0001] The invention belongs to the field of multifunctional radar, and specifically relates to multifunctional radar signal prediction technology. Furthermore, it proposes a multifunctional radar signal prediction method based on a prediction state representation model for intercepted multifunctional radar pulse sequences. 【Background technique】 [0002] As a multi-mode, multi-task and highly intelligent perception system, multifunctional radar (MFR) exhibits extremely strong flexibility and self-adaptive capabilities, but it also brings great challenges to battlefield electromagnetic environment reconnaissance and electronic warfare . Most of the current adaptive radar countermeasures respond to the radar's immediate signal, but this method has obvious lag. Since the countermeasures are only based on the historical state or behavior of the radar, the best countermeasure effect cannot be achieved when facing the MFR with extremely flexible and complex wav...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/02G01S7/38
CPCG01S7/021G01S7/38
Inventor 刘进欧健赵锋艾小锋杨建华吴其华李永祯肖顺平
Owner NAT UNIV OF DEFENSE TECH
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