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A Multi-Stage Smart Noise Jamming Method Based on Model-Free Reinforcement Learning

A smart noise jamming and reinforcement learning technology, applied in the field of radar, can solve the problems of jamming performance loss, inaccuracy, and high jamming power

Active Publication Date: 2021-01-12
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Application Information

AI Technical Summary

Problems solved by technology

However, expert experience is often inaccurate, and inaccurate jamming power allocation can lead to loss of jamming performance
1) Too small interference power cannot effectively reduce the performance of FCR
2) If the interference power is too large, the probability of finding interference increases

Method used

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  • A Multi-Stage Smart Noise Jamming Method Based on Model-Free Reinforcement Learning

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Embodiment Construction

[0031] In order to describe content of the present invention conveniently, at first the following terms are explained:

[0032] Term 1: Fire Control Radar

[0033] Fire control radar refers to the radar used to accurately track targets and provide target coordinate data for weapon command and control systems. Abbreviated as FCR.

[0034] Term 2: Radar warning receiver

[0035] Radar warning receiver refers to the electronic countermeasure equipment used to intercept, analyze and identify enemy radar signals, judge the threat level in real time and give timely warning, referred to as RWR.

[0036] Term 3: Track while scanning

[0037] Tracking while scanning refers to the working method in which the radar scans the search space while tracking single or multiple targets, referred to as TWS.

[0038] Term 4: Track plus search

[0039] Tracking and searching refers to the way that the radar can simultaneously complete the search and precise tracking of single or multiple targ...

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Abstract

The invention discloses a multi-stage smart noise jamming method based on model-free reinforcement learning, which is applied in the field of radar technology, in order to solve the jamming machine's environmental model for enemy fire control radar jamming identification methods, anti-jamming measures, and working mode conversion rules. For the optimal interference power allocation problem under unknown conditions, the present invention first models the multi-stage interference power allocation problem as a Markov decision process of an unknown environment model; in order to evaluate the performance of multi-stage noise interference, the average value of the fire control radar is selected Search-lock time is used as an evaluation index; secondly, the principle of noise interference power allocation is analyzed, and a reinforcement learning framework for multi-stage interference power allocation problems is established for the challenge of unknown environment models; finally, a Q-learning algorithm based A multi-stage interference power allocation method; the method of the invention effectively solves the problem of optimal allocation of interference power in practical applications, and improves the interference success rate.

Description

technical field [0001] The invention belongs to the technical field of radar, in particular to a radar smart noise jamming technology. Background technique [0002] Smart noise jamming means that the jammer emits a coherent noise-like signal to overlap and cover the target echo signal in the time domain, thereby confusing the radar target detection and tracking. Noise jamming technology plays a key role in electronic countermeasures. Whether effective jamming can be carried out is related to the safety of our combat resources and combat personnel. Therefore, smart noise jamming has become a key research topic for experts at home and abroad. [0003] Because modern fire control radar has strong anti-jamming capability and multiple working modes. In the face of this modern FCR, the traditional noise interference performance is getting worse and worse. In this case, it is necessary to study better smart noise interference measures. The generation of smart noise jamming wave...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/38G06N20/00
CPCG01S7/38G06N20/00
Inventor 张天贤王远航贾瑞韩毅孔令讲杨晓波
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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