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Special Issue "Sensors In Target Detection"

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

Deadline for manuscript submissions: 15 May 2019

Special Issue Editors

Guest Editor
Prof. Thierry Bouwmans

Universitè la Rochelle 17000 La Rochelle, France
Website | E-Mail
Interests: Data and Sensor Fusion; Low rank plus sparse decomposition; Robust principal component analysis; Image processing; Radar Signal processing
Guest Editor
Dr. Filippo Biondi

Joint Satellite Remote Sensing Center, Italian MoD, Rome RM, Italy
Website | E-Mail
Interests: Synthetic Aperture Radar (SAR) Spotlight and Stripmap focusing; SAR Interferometry and Differential SAR interferometry; Coherent filtering of SAR images; Precise atmospheric phase error estimation; 3-D SAR and polarimetric SAR Tomography; Polarimetric SAR assisted by Multi Chromatic Analysis (MCA) for target future extraction; Advanced algorithms development for Oil-Spill detection; SAR video production using the single SAR image by MCA; SAR refocusing for maritime surveillance; Low rank plus sparse decomposition for automatic future extraction; Super Resolution by spectrum extrapolation; Polarimetric Permanent Scatterers (PS) for precise 3D reconstruction and precise geolocation (Polarimetric-3-D Targeting); Multidimensional subsidence estimation by multiple look-angles of satellite observations and precise velocity/acceleration estimation

Special Issue Information

Dear Colleagues,

We invite manuscripts for this forthcoming Special Issue on all aspects of research and development related to these scientific and technical areas and in all possible domains of applications. Original research articles that focus on sensors in target detection and experimental validation are welcome to highlight novel approaches, recent advancements, and new application areas or that solve an important problem. Potential topics include (but are not limited to):

  • Visible cameras, IR cameras, multi-spectral sensors
  • Radar and sonar sensors
  • Sensor fusion
  •  Sensor placement, Sensor coverage
  • Wireless sensor networks
  • Synthetic-aperture radar (SAR) imaging, polarimetric (PolSAR), Interferometric SAR (InSAR), Polarimetric interferometric SAR (PolInSAR), Differential interferometric SAR (DinSAR), Persistent scatterer interferometry (PSInSAR), Multi-chromatic analysis (MCA) for SAR (MCA-SAR), SAR tomography
  • Pixel tracking in synthetic aperture radar for glacier applications
  • Pixel tracking in synthetic aperture radars for maritime surveillance
  • Along-track interferometry (ATI) for sea, lake and river current velocity estimation (distributed targets) and for maritime surveillance (coherent targets)
  • High-resolution, wide-swath strategies for synthetic aperture radars
  • Geosynchronous synthetic aperture radars, high-resolution methods and strategies
  • Hyperspectral satellite imaging classification and super-resolution techniques
  • Ground/marine moving target indication (MTI)
  • Direction-of-arrival tracking
  •  Deep-learning applied to remote sensing

Authors are invited to contact the Guest Editors prior to submission if they are uncertain whether their work falls within the general scope of this Special Issue.

Prof. Dr. Thierry Bouwmans
Dr. Filippo Biondi

Guest Editors

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 papers will be 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 1800 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.

Published Papers (5 papers)

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Research

Open AccessArticle A Doppler Range Compensation for Step-Frequency Continuous-Wave Radar for Detecting Small UAV
Sensors 2019, 19(6), 1331; https://doi.org/10.3390/s19061331
Received: 10 February 2019 / Revised: 12 March 2019 / Accepted: 13 March 2019 / Published: 16 March 2019
PDF Full-text (1494 KB)
Abstract
Step-frequency continuous-wave (SFCW) modulation can have a role in the detection of small unmanned aerial vehicles (UAV) at short range (less than 1–2 km). In this paper, the theory of SFCW range detection is reviewed, and a specific method for correcting the possible [...] Read more.
Step-frequency continuous-wave (SFCW) modulation can have a role in the detection of small unmanned aerial vehicles (UAV) at short range (less than 1–2 km). In this paper, the theory of SFCW range detection is reviewed, and a specific method for correcting the possible range shift due to the Doppler effect is devised. The proposed method was tested in a controlled experimental set-up, where a free-falling target (i.e., a corner reflector) was correctly detected by an SFCW radar. This method was finally applied in field for short-range detection of a small UAV. Full article
(This article belongs to the Special Issue Sensors In Target Detection)
Open AccessArticle A High-Multi Target Resolution Focal Plane Array-Based Laser Detection and Ranging Sensor
Sensors 2019, 19(5), 1210; https://doi.org/10.3390/s19051210
Received: 11 February 2019 / Revised: 1 March 2019 / Accepted: 4 March 2019 / Published: 9 March 2019
PDF Full-text (3575 KB) | HTML Full-text | XML Full-text
Abstract
This paper introduces a digital-assisted multiple echo detection scheme, which utilizes the waste time of the full serial data readout period in a focal plane array (FPA)-based laser detection and ranging (LADAR) receiver. With the support of an external digital signal processor (DSP) [...] Read more.
This paper introduces a digital-assisted multiple echo detection scheme, which utilizes the waste time of the full serial data readout period in a focal plane array (FPA)-based laser detection and ranging (LADAR) receiver. With the support of an external digital signal processor (DSP) and additional analog memory inserted into the receiver, the proposed readout scheme can effectively enhance multi-target resolution (MTR) three times higher than the conventional FPA-based LADAR, while maintaining low power consumption and a small area. A prototype chip was fabricated in a 0.18-μm CMOS process with an 8 × 8 FPA configuration, where each single receiver pixel occupied an area of 100 μm × 100 μm. The single receiver achieved an MTR of 20 ns with 7.47 mW power dissipation, an input referred noise current of 4.48 pA/√Hz with a bandwidth 530 MHz, a minimum detectable signal (MDS) of 340 nA, a maximum walk error of 2.2 ns, and a maximum non-linearity of 0.05% among the captured multiple echo images. Full article
(This article belongs to the Special Issue Sensors In Target Detection)
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Open AccessArticle A Two-Dimensional Adaptive Target Detection Algorithm in the Compressive Domain
Sensors 2019, 19(3), 567; https://doi.org/10.3390/s19030567
Received: 5 December 2018 / Revised: 16 January 2019 / Accepted: 25 January 2019 / Published: 29 January 2019
PDF Full-text (3389 KB) | HTML Full-text | XML Full-text
Abstract
By applying compressive sensing to infrared imaging systems, the sampling and transmitting time can be remarkably reduced. Therefore, in order to meet the real-time requirements of infrared small target detection tasks in the remote sensing field, many approaches based on compressive sensing have [...] Read more.
By applying compressive sensing to infrared imaging systems, the sampling and transmitting time can be remarkably reduced. Therefore, in order to meet the real-time requirements of infrared small target detection tasks in the remote sensing field, many approaches based on compressive sensing have been proposed. However, these approaches need to reconstruct the image from the compressive domain before detecting targets, which is inefficient due to the complex recovery algorithms. To overcome this drawback, in this paper, we propose a two-dimensional adaptive threshold algorithm based on compressive sensing for infrared small target detection. Instead of processing the reconstructed image, our algorithm focuses on directly detecting the target in the compressive domain, which reduces both the time and memory requirements for image recovery. First, we directly subtract the spatial background image in the compressive domain of the original image sampled by the two-dimensional measurement model. Then, we use the properties of the Gram matrix to decode the subtracted image for further processing. Finally, we detect the targets by employing the advanced adaptive threshold method to the decoded image. Experiments show that our algorithm can achieve an average 100% detection rate, with a false alarm rate lower than 0.4%, and the computational time is within 0.3 s, on average. Full article
(This article belongs to the Special Issue Sensors In Target Detection)
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Open AccessArticle A Clutter-Analysis-Based STAP for Moving FOD Detection on Runways
Sensors 2019, 19(3), 549; https://doi.org/10.3390/s19030549
Received: 3 December 2018 / Revised: 22 January 2019 / Accepted: 22 January 2019 / Published: 29 January 2019
PDF Full-text (7424 KB) | HTML Full-text | XML Full-text
Abstract
Security risks and economic losses of civil aviation caused by Foreign Object Debris (FOD) have increased rapidly. Synthetic Aperture Radars (SARs) with high resolutions potentially have the capability to detect FODs on the runways, but the target echo is hard to be distinguished [...] Read more.
Security risks and economic losses of civil aviation caused by Foreign Object Debris (FOD) have increased rapidly. Synthetic Aperture Radars (SARs) with high resolutions potentially have the capability to detect FODs on the runways, but the target echo is hard to be distinguished from strong clutter. This paper proposes a clutter-analysis-based Space-time Adaptive Processing (STAP) method in order to obtain effective clutter suppression and moving FOD indication, under inhomogeneous clutter background. Specifically, we first divide the radar coverage into equal scattering cells in the rectangular coordinates system rather than the polar ones. We then measure normalized RCSs within the X-band and employ the acquired results to modify the parameters of traditional models. Finally, we describe the clutter expressions as responses of the scattering cells in space and time domain to obtain the theoretical clutter covariance. Experimental results at 10 GHz show that FODs with a reflection higher than −30 dBsm can be effectively detected by a Linear Constraint Minimum Variance (LCMV) filter in azimuth when the noise is −60 dBm. It is also validated to indicate a −40 dBsm target in Doppler. Our approach can obtain effective clutter suppression 60dB deeper than the training-sample-coupled STAP under the same conditions. Full article
(This article belongs to the Special Issue Sensors In Target Detection)
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Open AccessArticle An Improved Inverse Beamforming Method: Azimuth Resolution Analysis for Weak Target Detection
Sensors 2018, 18(12), 4160; https://doi.org/10.3390/s18124160
Received: 1 November 2018 / Revised: 22 November 2018 / Accepted: 24 November 2018 / Published: 27 November 2018
PDF Full-text (3075 KB) | HTML Full-text | XML Full-text
Abstract
The inverse beamforming (IBF) is a mature method to improve azimuth resolution. However, for weak targets it is not applicable as IBF enhances side lobes. In this paper, an improved IBF algorithm is proposed to raise the azimuth resolution under the premise of [...] Read more.
The inverse beamforming (IBF) is a mature method to improve azimuth resolution. However, for weak targets it is not applicable as IBF enhances side lobes. In this paper, an improved IBF algorithm is proposed to raise the azimuth resolution under the premise of ensuring the detection ability for weak targets. Firstly, from the point of phase compensation, we analyze the cause of side lobes when IBF is applied. Then the improved IBF algorithm recorded as GIBF (the improved inverse beamforming) is proposed by changing the Toeplitz average into the phase construction. The theoretical derivation and simulation data processing show the proposed method can improve the resolution of the N sensors to the standard of 2N − 1 sensors under different signal-to-noise ratios. Compared with IBF, GIBF has great advantages in detecting weak targets. Passive sonar data are used to further verify the advantages of GIBF; the trajectories on azimuth history diagrams become clear, the azimuth resolution is improved, and the detection ability for weak targets is still robust. In addition, GIBF is combined with the common DOA (direction of arrival) estimation algorithms, such as conventional beamforming and minimum variance distortionless signal response, which proves the applicability of the algorithm. Full article
(This article belongs to the Special Issue Sensors In Target Detection)
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