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Distributed Target Detection in Unknown Interference.

Kaiming Xu1,2, Yunkai Deng1,2, Zhongjun Yu1,2

  • 1The Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.

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|April 12, 2022
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Summary

This study introduces novel radar detectors to improve target detection amidst unknown interference. The generalized likelihood ratio test (GLRT) and Wald test detectors show enhanced performance compared to existing methods.

Keywords:
Rao testWald testdistributed targetgeneralized likelihood ratio testmultichannel signalunknown interference

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Area of Science:

  • Radar Systems Engineering
  • Signal Processing
  • Detection Theory

Background:

  • Radar system performance is significantly degraded by interference.
  • Detecting targets in unknown interference environments presents a major challenge.

Purpose of the Study:

  • To develop effective radar target detection methods for unknown interference scenarios.
  • To model interference within a subspace orthogonal to the signal subspace.

Main Methods:

  • Design of three detectors based on generalized likelihood ratio test (GLRT), Rao test, and Wald test criteria.
  • Performance evaluation in the presence of completely unknown interference.
  • Modeling interference as belonging to a subspace orthogonal to the signal subspace.

Main Results:

  • The proposed GLRT and Wald test detectors demonstrate superior performance over existing methods.
  • Detection performance is illustrated even when interference is not constrained to the orthogonal subspace.
  • The developed detectors are effective for distributed target detection.

Conclusions:

  • The proposed GLRT and Wald test detectors offer improved solutions for radar target detection in unknown interference.
  • The subspace modeling approach effectively addresses the challenge of unknown interference.
  • These detectors enhance the robustness and reliability of radar systems.