Scanning Strategy Learning For Electronic Support Receivers by Robust Principal Component Analysis


Gul I., Erer I.

Conference on Artificial Intelligence and Machine Learning in Defense Applications III Held as Part of SPIE Security+Defence Conference, ELECTR NETWORK, 13 - 17 September 2021, vol.11870 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 11870
  • Doi Number: 10.1117/12.2601109
  • Country: ELECTR NETWORK
  • Keywords: Electronic Support Measures, Frequency Search Strategy, Robust Principal Component Analysis (RPCA), Scanning Regime Learning, Electronic Support Receiver, Electronic Warfare

Abstract

Narrow-band Electronic Support receivers cannot detect radar signals in broad frequency ranges of the electromagnetic spectrum simultaneously. Hence, a frequency spectrum scanning strategy has to be planned. Commonly, this strategy is determined based on prior knowledge about possible threats. However, in an environment where the parameters of the radars are unconfirmed, it could be planned via learning-based representations. In previous researches, this sensor scheduling problem was modeled as a dynamical system by Predictive State Representations. Moreover, Singular Value Thresholding (SVT) algorithm is used in the subspace identification part to cope with the complexity of the system. In this work, We propose a scanning strategy learning method based on Robust Principal Component Analysis (RPCA).