Target Detection in Coherent Frequency Diverse Array Radar Without Training Data

Articles in Press

Document Type : Research Paper

Authors

1 Department of electrical engineering

2 Electrical Engineering Departement, Shahid Bohonar University of Kerman

Abstract

Mathematical modeling offers a powerful framework for understanding complex problems and developing practical solutions. This paper investigates target detection in Coherent Frequency Diverse Array (C-FDA) radar systems without relying on training data. The target detection problem is formulated as a binary composite hypothesis testing-problem. Without applying any simplifications to the received signal model, we employ the full general model to derive new detectors based on the Generalized Likelihood Ratio Test (GLRT), Rao, and Wald test principles. The resulting detectors differ structurally and exhibit varying performance depending on the signaling scheme and detection scenarios. Extensive simulation results demonstrate that the proposed Wald and GLRT-based detectors consistently outperform the Rao detector in terms of detection probability. Furthermore, a comparison with an existing method for C-FDA systems shows that the proposed detectors achieve superior performance, offering approximately 3 dB improvement in signal-to-disturbance ratio. Furthermore, in multi-target scenarios, the proposed detectors exhibit significantly enhanced resolution and target separation in the range–angle domain.

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Journal of Modeling in Engineering

Articles in Press, Accepted Manuscript
Available Online from 05 October 2025

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History

  • Receive Date: 11 July 2024
  • Revise Date: 27 August 2025
  • Accept Date: 31 August 2025

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