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Joint frequency and two‐dimensional direction of arrival estimation for Electronic Support systems based on sub‐Nyquist sampling
Author(s) -
Ramezani Esmaeil,
Sabahi Mohamad Farzan,
Saberali Seyyed Mohammad
Publication year - 2018
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2017.0477
Subject(s) - nyquist frequency , nyquist–shannon sampling theorem , joint (building) , direction of arrival , sampling (signal processing) , computer science , acoustics , telecommunications , electronic engineering , physics , engineering , bandwidth (computing) , detector , architectural engineering , antenna (radio)
The electronic support (ES) receivers require wide instantaneous bandwidth as a result of a wide‐frequency range of modern radar signals. Thus, analogue‐to‐digital converters (ADCs) with high sampling rates are required for digital ES receivers. One of the bottlenecks in designing such systems is the high power consumption of the back‐end ADCs at high sampling rates. In this study, a system‐level approach with the goal of minimising the required digitisation rate is presented by exploiting compressive sampling. Using the proposed receiver structure, the location finding of pulsed radars in wideband scenarios is studied. To fulfil the need for frequency and position finding, the proposed receiver employs a three‐dimensional antenna array, followed by radio‐frequency back‐end and ADC blocks, inspired by the modulated wideband converter technique. Furthermore, an algorithm based on Bayesian compressed sensing, incorporating off‐grid techniques, is employed to jointly estimate the azimuth and the elevation angles of incoming signals, as well as their carrier frequencies. Simulation results are provided to support the theoretical results obtained in this study. The results show that the proposed off‐grid Bayesian method has a significantly lower mean square estimation error than the conventional deterministic approaches, while its average computation complexity can be reduced in multi‐snapshot scenarios.

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