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Advanced Passive Radar Techniques and Applications
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Advanced Passive Radar Techniques and Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 18209

Special Issue Editor

Dr. Michail Antoniou

E-Mail Website
Guest Editor
Department of Electronic, Electrical and Systems Engineering, School of Engineering, University of Birmingham, Birmingham B15 2TT, UK
Interests: passive radar; bi-/multi-static radar; synthetic aperture radar; MIMO radar; cognitive radar

Special Issue Information

Dear Colleagues,

Passive radar has reached an unprecedented maturity. Its ability to operate covertly, re-use existing parts of the electromagnetic spectrum, as well as its cost-effectiveness, has driven research and innovation that has led to commercial systems, with even more at their development stages across the world. Alongside this maturity, new passive radar techniques are being developed, from multistatic signal processing to imaging and compressive sensing, for applications from air traffic control to Earth Observation, and with well-established transmitters of opportunity as well as upcoming ones.

This Special Issue is aimed at representing the latest advances in passive radar technology. We welcome contributions in all fields of passive radar, including new systems, signal processing algorithms, as well as new applications. Those include but are not limited to:

  • Passive radar systems;
  • Passive radar phenomenology;
  • Multistatic signal processing;
  • Passive radar imaging, including SAR and ISAR;
  • Moving target indications;
  • Compressive sensing;
  • Emerging transmitters of opportunity for passive radar;
  • Emerging passive radar applications

Dr. Michail Antoniou
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • passive radar
  • passive coherent location
  • radar signal processing
  • radar phenomenology
  • SAR/ISAR
  • compressive sensing

Published Papers (6 papers)

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Research

24 pages, 9661 KiB  
Article
Detection of Direction-Of-Arrival in Time Domain Using Compressive Time Delay Estimation with Single and Multiple Measurements
by Youngmin Choo, Yongsung Park and Woojae Seong
Sensors 2020, 20(18), 5431; https://doi.org/10.3390/s20185431 - 22 Sep 2020
Cited by 6 | Viewed by 2513
Abstract
The compressive time delay estimation (TDE) is combined with delay-and-sum beamforming to obtain direction-of-arrival (DOA) estimates in the time domain. Generally, the matched filter that detects the arrivals at the hydrophone is used with beamforming. However, when the ocean noise smears the arrivals, [...] Read more.
The compressive time delay estimation (TDE) is combined with delay-and-sum beamforming to obtain direction-of-arrival (DOA) estimates in the time domain. Generally, the matched filter that detects the arrivals at the hydrophone is used with beamforming. However, when the ocean noise smears the arrivals, ambiguities appear in the beamforming results, degrading the DOA estimation. In this work, compressive sensing (CS) is applied to accurately evaluate the arrivals by suppressing the noise, which enables the correct detection of arrivals. For this purpose, CS is used in two steps. First, the candidate time delays for the actual arrivals are calculated in the continuous time domain using a grid-free CS. Then, the dominant arrivals constituting the received signal are selected by a conventional CS using the time delays in the discrete time domain. Basically, the compressive TDE is used with a single measurement. To further reduce the noise, common arrivals over multiple measurements, which are obtained using the extended compressive TDE, are exploited. The delay-and-sum beamforming technique using refined arrival estimates provides more pronounced DOAs. The proposed scheme is applied to shallow-water acoustic variability experiment 15 (SAVEX15) measurement data to demonstrate its validity. Full article
(This article belongs to the Special Issue Advanced Passive Radar Techniques and Applications)
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22 pages, 4279 KiB  
Article
Robust Weighted l1,2 Norm Filtering in Passive Radar Systems
by Baris Satar, Gokhan Soysal, Xue Jiang, Murat Efe and Thiagalingam Kirubarajan
Sensors 2020, 20(11), 3270; https://doi.org/10.3390/s20113270 - 08 Jun 2020
Cited by 5 | Viewed by 3249
Abstract
Conventional methods such as matched filtering, fractional lower order statistics cross ambiguity function, and recent methods such as compressed sensing and track-before-detect are used for target detection by passive radars. Target detection using these algorithms usually assumes that the background noise is Gaussian. [...] Read more.
Conventional methods such as matched filtering, fractional lower order statistics cross ambiguity function, and recent methods such as compressed sensing and track-before-detect are used for target detection by passive radars. Target detection using these algorithms usually assumes that the background noise is Gaussian. However, non-Gaussian impulsive noise is inherent in real world radar problems. In this paper, a new optimization based algorithm that uses weighted l 1 and l 2 norms is proposed as an alternative to the existing algorithms whose performance degrades in the presence of impulsive noise. To determine the weights of these norms, the parameter that quantifies the impulsiveness level of the noise is estimated. In the proposed algorithm, the aim is to increase the target detection performance of a universal mobile telecommunication system (UMTS) based passive radars by facilitating higher resolution with better suppression of the sidelobes in both range and Doppler. The results obtained from both simulated data with α stable distribution, and real data recorded by a UMTS based passive radar platform are presented to demonstrate the superiority of the proposed algorithm. The results show that the proposed algorithm provides more robust and accurate detection performance for noise models with different impulsiveness levels compared to the conventional methods. Full article
(This article belongs to the Special Issue Advanced Passive Radar Techniques and Applications)
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15 pages, 6186 KiB  
Article
Effects of Clear-Sky Assimilation of GPM Microwave Imager on the Analysis and Forecast of Typhoon “Chan-Hom”
by Dongmei Xu, Aiqing Shu and Feifei Shen
Sensors 2020, 20(9), 2674; https://doi.org/10.3390/s20092674 - 08 May 2020
Cited by 7 | Viewed by 2123
Abstract
The module of assimilating a new GMI (GPM Microwave Imager) satellite detector was built in the framework of the Weather Research and Forecasting Model (WRF) and its three-dimensional variational (3DVar) data assimilation system (WRFDA). Typhoon “Chan-Hom” in the 2015 Pacific typhoon season was [...] Read more.
The module of assimilating a new GMI (GPM Microwave Imager) satellite detector was built in the framework of the Weather Research and Forecasting Model (WRF) and its three-dimensional variational (3DVar) data assimilation system (WRFDA). Typhoon “Chan-Hom” in the 2015 Pacific typhoon season was selected to verify the effectivity of the GMI clear-sky assimilation. The results show that, after assimilating the GMI radiance data, the background information in the model is modified positively when compared with the experiment without any assimilation and the one with assimilation of the conventional data. The obvious warm core structure of the typhoon, the modified geopotential height field, and the intensified circulation of the typhoon are favorable for the northwest twist of the typhoon, thus contributing to a better track forecast with a maximum error below 160 km in the 48-h deterministic forecast. Full article
(This article belongs to the Special Issue Advanced Passive Radar Techniques and Applications)
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16 pages, 8026 KiB  
Article
Modified Blind Equalization Algorithm Based on Cyclostationarity for Contaminated Reference Signal in Airborne PBR
by Shuai Guo, Jun Wang, Hui Ma and Jipeng Wang
Sensors 2020, 20(3), 788; https://doi.org/10.3390/s20030788 - 31 Jan 2020
Cited by 11 | Viewed by 2567
Abstract
In airborne passive bistatic radar (PBR), the reference channel toward the opportunity illuminator is applied to receive the direct-path signal as the reference signal. In the actual scenario, the reference signal is contaminated by the multipath signals easily. Unlike the multipath signal in [...] Read more.
In airborne passive bistatic radar (PBR), the reference channel toward the opportunity illuminator is applied to receive the direct-path signal as the reference signal. In the actual scenario, the reference signal is contaminated by the multipath signals easily. Unlike the multipath signal in traditional ground PBR system, the multipath signal in the airborne PBR owns not only the time delay but also the Doppler frequency. The contaminated reference signal can cause the spatial-temporal clutter spectrum to expand and the false targets to appear. The performance of target detection is impacted severely. However, the existing blind equalization algorithm is unavailable for the contaminated reference signal in airborne PBR. In this paper, the modified blind equalization algorithm is proposed to suppress the needless multipath signal and restore the pure reference signal. Aiming at the Doppler frequency of multipath signal, the high-order moment information and the cyclostationarity of source signal are exploited to construct the new cost function for the phase constraint, and the complex value back propagation (BP) neural network is exploited to solve the constraint optimization problem for the better convergence. In final, the simulation experiments are conducted to prove the feasibility and superiority of proposed algorithm. Full article
(This article belongs to the Special Issue Advanced Passive Radar Techniques and Applications)
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20 pages, 4405 KiB  
Article
Experimental Demonstration of Ship Target Detection in GNSS-Based Passive Radar Combining Target Motion Compensation and Track-before-Detect Strategies
by Fabrizio Santi, Debora Pastina and Marta Bucciarelli
Sensors 2020, 20(3), 599; https://doi.org/10.3390/s20030599 - 21 Jan 2020
Cited by 28 | Viewed by 3248
Abstract
This work discusses methods and experimental results on passive radar detection of moving ships using navigation satellites as transmitters of opportunity. The reported study highlights as the adoption of proper strategies combining target motion compensation and track-before-detect methods to achieve long time integration [...] Read more.
This work discusses methods and experimental results on passive radar detection of moving ships using navigation satellites as transmitters of opportunity. The reported study highlights as the adoption of proper strategies combining target motion compensation and track-before-detect methods to achieve long time integration can be fruitfully exploited in GNSS-based passive radar for the detection of maritime targets. The proposed detection strategy reduces the sensitivity of long-time integration methods to the adopted motion models and can save the computational complexity, making it appealing for real-time implementations. Experimental results obtained in three different scenarios (port operations, navigation in open area, and river shipping) comprising maritime targets belonging to different classes show as this combined approach can be employed with success in several operative scenarios of practical interest for this technology. Full article
(This article belongs to the Special Issue Advanced Passive Radar Techniques and Applications)
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19 pages, 6937 KiB  
Article
A Block Method Using the Chirp Rate Estimation for NLFM Radar Pulse Reconstruction
by Karol Abratkiewicz and Piotr Samczyński
Sensors 2019, 19(22), 5015; https://doi.org/10.3390/s19225015 - 17 Nov 2019
Cited by 12 | Viewed by 3000
Abstract
This paper presents a novel approach to fast and accurate non-linear pulse signal reconstruction dedicated for electromagnetic sensors and their applications such as ELectronic INTelligence (ELINT), electronic warfare (EW), electronic reconnaissance (ER) systems, as well as for passive bistatic radar purposes in which [...] Read more.
This paper presents a novel approach to fast and accurate non-linear pulse signal reconstruction dedicated for electromagnetic sensors and their applications such as ELectronic INTelligence (ELINT), electronic warfare (EW), electronic reconnaissance (ER) systems, as well as for passive bistatic radar purposes in which other pulse radars are used as a source of illumination. The method is based on the instantaneous chirp rate (CR) estimation in the time-frequency (TF) domain providing a calculation of the frequency rate between every two consecutive samples. Such a new method allows for the precise reconstruction of the non-linear frequency modulated (NLFM) signal to be carried out in significantly shorter time in comparison to methods known in the literature. The presented approach was tested and validated using both simulated and real-life radar signals proving the usability of the proposed solution in practical applications. The results were compared with the precise extended generalized chirp transform (EGCT) method as a reference technique, using optimal matched filtration as the main concept. Full article
(This article belongs to the Special Issue Advanced Passive Radar Techniques and Applications)
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