Radar Signal Processing

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (20 September 2021) | Viewed by 5724

Special Issue Editor

Department of Information and Communication Engineering, Sejong University, Gwangjin-gu, Seoul, Korea
Interests: radar; nonlinear optimization; radar signal processing; digital signal processing; antennas and propagation

Special Issue Information

Dear Colleagues,

Various techniques have been employed to extract useful information from received radar signals. Moving target indication, signal integration for SNR improvement, pulse compression, angle estimation, and delay estimation can be examples of topics of radar signal processing. 

Traditionally, analog signal processing has been used for radar signal processing. However, due to the availability of digital processors with high speed and capability, digital signal processing has been extensively adopted in modern radar systems. 

The aim of this Special Issue is to invite recent advances and inherent challenges in radar signal processing and its implementation, with emphasis on modeling and simulation, analytic performance analysis, and the machine-learning-based approach.

Potential topics of the Special Issue include but are not limited to the following: 

  • Classifier design for radar target classification;
  • Performance analysis of feature extraction algorithm for radar target classification;
  • Machine-learning-based threshold detection of radar target;
  • Performance analysis of radar signal processing algorithm;
  • Hybrid angle-of-arrival and time-of-arrival based wireless localization;
  • Performance analysis of localization algorithms;
  • Recent advances in radar measurement algorithms and their performance analysis;
  • Recent advances in CFAR detectors, Doppler processing, pulse compression, and tracking algorithms;
  • Signal processing for jammer design;
  • Numerical analysis in radar signal processing algorithm;
  • Performance assessment of radar signal processing algorithm: Monte Carlo simulation versus analytical performance analysis.

Prof. Dr. Joon-Ho Lee
Guest Editor

Manuscript Submission Information

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Keywords

  • Digital signal processing for radar
  • Radar signal processor
  • Radar detection and tracking
  • Wireless localization
  • Analytic performance analysis
  • Radar target recognition and identification
  • Feature extraction for radar target classification
  • Machine-learning-based radar signal processing…

Published Papers (3 papers)

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Research

9 pages, 3011 KiB  
Article
Modulation Linearization Technique for FM/CW SAR Image Processing Using Range Migration
by Theodore Grosch and Cyril Okhio
Appl. Sci. 2021, 11(16), 7410; https://0-doi-org.brum.beds.ac.uk/10.3390/app11167410 - 12 Aug 2021
Viewed by 1377
Abstract
Linear FMCW radar suffers from impairments in range and range rate if there are errors in the modulation rate or phase discontinuities. Often, this is a result of a nonlinearity of the voltage-controlled oscillator that is in the source of the transmit and [...] Read more.
Linear FMCW radar suffers from impairments in range and range rate if there are errors in the modulation rate or phase discontinuities. Often, this is a result of a nonlinearity of the voltage-controlled oscillator that is in the source of the transmit and receive local oscillator. The nonlinearity can be corrected at the source by using a nonlinear control voltage or by processing the received beat frequency. Any signal processing using the later method leads to computation time and energy costs, which can be considerable in some applications. When the range migration algorithm using the Stolt Transform is used for Synthetic Aperture Radar (SAR) image processing, the autofocus linearization technique described here costs nothing in additional hardware or computation time. Full article
(This article belongs to the Special Issue Radar Signal Processing)
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15 pages, 9558 KiB  
Article
Selecting Target Range with Accurate Vital Sign Using Spatial Phase Coherency of FMCW Radar
by Ho-Ik Choi, Woo-Jin Song, Heemang Song and Hyun-Chool Shin
Appl. Sci. 2021, 11(10), 4514; https://0-doi-org.brum.beds.ac.uk/10.3390/app11104514 - 15 May 2021
Cited by 8 | Viewed by 2389
Abstract
Respiration and heartbeat are basic indicators of the physiological state of human beings. Frequency-modulated continuous wave (FMCW) radar can sense micro-displacement in the human body surface without contact, and is used for vital-sign (respiration and heartbeat) monitoring. For the extraction of vital-sign, it [...] Read more.
Respiration and heartbeat are basic indicators of the physiological state of human beings. Frequency-modulated continuous wave (FMCW) radar can sense micro-displacement in the human body surface without contact, and is used for vital-sign (respiration and heartbeat) monitoring. For the extraction of vital-sign, it is essential to select the target range containing vital-sign information. In this paper, we exploit the coherency of phase in different range-bins of FMCW radar to effectively select the range-bins that contain accurate signals for remote monitoring of human respiration and heartbeat. To quantify coherency, the spatial phase coherency (SPC) index is introduced. The experimental results show that the SPC can select a range-bin containing more accurate vital-sign signals than conventional methods. This result demonstrates that the proposed method is accurate for monitoring of vital signs by using FMCW radar. Full article
(This article belongs to the Special Issue Radar Signal Processing)
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20 pages, 435 KiB  
Article
Performance Analysis of Interferometer Algorithm under Phase Measurement Error
by Chan-Bin Ko and Joon-Ho Lee
Appl. Sci. 2021, 11(2), 467; https://0-doi-org.brum.beds.ac.uk/10.3390/app11020467 - 06 Jan 2021
Cited by 2 | Viewed by 1307
Abstract
Direction finding has been extensively studied over the past decades and a number of algorithms have been developed. In direction finding, theoretic performance prediction is a fundamental problem. This paper addresses the performance analysis issue of interferometer-based 2D angle of arrival estimation using [...] Read more.
Direction finding has been extensively studied over the past decades and a number of algorithms have been developed. In direction finding, theoretic performance prediction is a fundamental problem. This paper addresses the performance analysis issue of interferometer-based 2D angle of arrival estimation using uniform circular array (UCA). We propose an analytic method for performance analysis of interferometer in the presence of Gaussian or uniform error in phase measurement of incident signal on each sensor. The analytic mean square error (MSE), which is approximately equal to the MSE of actual interferometer-based DOA estimation, is derived via Taylor expansion and approximation. The derived analytic MSE is useful for predicting how the MSE of the interferometer-based DOA estimation algorithm is dependent on the phase measurement error. Full article
(This article belongs to the Special Issue Radar Signal Processing)
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