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Sensors 2017, 17(3), 632; doi:10.3390/s17030632

Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations

1
Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defence Technology, Changsha 410073, China
2
Beijing Institute of Tracking & Telecommunications Technology, Beijing 100094, China
*
Author to whom correspondence should be addressed.
Received: 28 November 2016 / Revised: 10 March 2017 / Accepted: 16 March 2017 / Published: 19 March 2017
(This article belongs to the Special Issue Non-Contact Sensing)
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Abstract

The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity. View Full-Text
Keywords: predictive state representation; multi-function radar; signal prediction; operating mode recognition predictive state representation; multi-function radar; signal prediction; operating mode recognition
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Ou, J.; Chen, Y.; Zhao, F.; Liu, J.; Xiao, S. Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations
. Sensors 2017, 17, 632.

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