Sensor and Platform Technologies

Simulation study of first-order sea clutter Doppler spectra for shipborne high frequency radar via hybrid sky-surface wave propagation

[+] Author Affiliations
Yinsheng Wei, Yongpeng Zhu

Harbin Institute of Technology, School of Electronics and Information Engineering, 92 West Dazhi Street, Harbin 150001, China

J. Appl. Remote Sens. 11(1), 014001 (Jan 10, 2017). doi:10.1117/1.JRS.11.014001
History: Received June 30, 2016; Accepted December 20, 2016
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Abstract.  The Doppler spectra of first-order sea echo are studied in a high frequency radar system for hybrid sky-surface wave propagation when the receiving antenna array is mounted on a shipborne platform. Here, the platform motion and ionosphere perturbed phases are assumed to be the key factors resulting in the sea clutter spectral fluctuation. Based on the received first-order electric field equation, a closed form of cross sections is derived to account for the ship motion influence. It is shown numerically that the resultant clutter spectra exhibit significant discrepancies with different system operating parameters and platform motion states. In addition, the phase path variations along the inhomogeneous ionosphere are considered by dividing the ionosphere into the quiescent and distorted components. Such manipulation makes it feasible to simulate the phase fluctuations with a method associated with deterministic and stochastic models. Eventually, simulation results for a composite modulation taking account of both effects are provided. Compared with the spread Doppler spectra due to the platform motion, the attached ionosphere perturbed phases will further split and leak the spectral energy, which may bring in difficulties for the applications in remote sensing and target detection.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Yinsheng Wei and Yongpeng Zhu
"Simulation study of first-order sea clutter Doppler spectra for shipborne high frequency radar via hybrid sky-surface wave propagation", J. Appl. Remote Sens. 11(1), 014001 (Jan 10, 2017). ; http://dx.doi.org/10.1117/1.JRS.11.014001


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