Coherence-Factor-Based Rough Surface Clutter Suppression for Forward-Looking GPR Imaging

A robust method for ultra-wideband (UWB) imaging of buried shallow objects based on time gating, Wiener filtering, as well as constant false alarm rate (CFAR) is proposed. Moreover, it is demonstrated that Wiener filtering can be used as a clutter removal tool in UWB signal applications. Basically, the problem with time gating method is that the length of the timing window for unknown targets cannot be determined accurately in advance. In fact, it is a blind methodology and some targets can be missed due to a lack of preknowledge about their depth. Imprecise window length selection leads to missing some parts of the target signals along with the clutter, which in turn increases the missed detection rate. Herein, an algorithm to tackle this problem is proposed by using a Wiener filter along with CFAR as a primary detector of the target positions employing average similarity function imaging. The time gating method is then built on top of the information achieved for the window length selection from the primary detection. The combination of the two steps provides better detection of shallowly buried objects with less missed detection of targets, besides having fewer artefacts in comparison to other methods. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…where I(p) is the received signal from clutter or a target, and N c and N t represent number of clutter and signal pixels, respectively [31,32].…”

Section: Signal-to-clutter Ratiomentioning

confidence: 99%

Robust Wiener filter‐based time gating method for detection of shallowly buried objects

Gharamohammadi

Behnia

Shokouhmand

et al. 2021

IET Signal Processing

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“…However, there is a clear risk for the vehicle (and its operator/driver) if a buried explosive target is not detected. To improve the detection probability, several signal processing techniques have been proposed in the field of FLGPR systems [13].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Analysis and Validation of a Hybrid Forward-Looking Down-Looking Ground Penetrating Radar Architecture

et al. 2021

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Ground Penetrating Radar (GPR) has proved to be a successful technique for the detection of landmines and Improvised Explosive Devices (IEDs) buried in the ground. In the last years, novel architectures for safe and fast detection, such as those based on GPR systems onboard Unmanned Aerial Vehicles (UAVs), have been proposed. Furthermore, improvements in GPR hardware and signal processing techniques have resulted in a more efficient detection. This contribution presents an experimental validation of a hybrid Forward-Looking–Down-Looking GPR architecture. The main goal of this architecture is to combine advantages of both GPR architectures: reduction of clutter coming from the ground surface in the case of Forward-Looking GPR (FLGPR), and greater dynamic range in the case of Down-Looking GPR (DLGPR). Compact radar modules working in the lower SHF frequency band have been used for the validation of the hybrid architecture, which involved realistic targets.

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“…The contributions belonging to the second group [7][8][9][10] are focused on the description of novel data processing techniques aimed at achieving accurate radar imaging under complex acquisition geometries, such as in the case of airborne Synthetic Aperture Radar (SAR) [6][7][8], or in challenging scenarios, as in the case of Forward-Looking Ground-Penetrating Radar (FL-GPR) [9] or Lunar Penetrating Radar (LPR) [10].…”

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confidence: 99%

“…As for the papers belonging to the second group, they address the processing of three kinds of imaging radar data, namely, airborne SAR [7,8], FL-GPR [9] and LPR [10] data. For airborne SAR processing, exploitation of small and flexible aerial platforms to mount the radar systems makes the issues related to motion errors (that is, the attitude and position instabilities of the platform during the acquisition) coupled to the topographic variations of the observed scene even more critical; therefore, ad-hoc data processing strategies capable to properly account for these problems are needed.…”

mentioning

confidence: 99%

“…Furthermore, the rough ground surface generates clutter that may obscure the buried targets, rendering target detection very challenging. In this respect, the work in [9] presents an enhanced imaging procedure for the suppression of the rough surface clutter arising in FL-GPR applications. The procedure is based on a matched filtering formulation of microwave tomographic imaging enhanced by a coherence factor (CF) scheme for clutter suppression.…”

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confidence: 99%

See 1 more Smart Citation

Editorial for Special Issue “Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms”

2020

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Microwave radar imaging plays a key role in several civilian and defense applications, such as security, surveillance, diagnostics and monitoring in civil engineering and cultural heritage, environment observation, with particular emphasis on disasters and crisis management, where it is required to remotely sense the area of interest in a timely, safe and effective way. To address these constraints, a technological opportunity is offered by radar systems mounted onboard smart and flexible platforms, such as ground-based ones, airplanes, helicopters, drones, unmanned aerial and ground vehicles (UAV and UGV). For this reason, radar imaging based on data collected by such platforms is gaining interest in the remote sensing community. However, a full exploitation of smart and flexible radar systems requires the development and use of image formation techniques and reconstruction approaches able to exploit and properly deal with non-conventional data acquisition configurations. The other main issue is related to the need to operate in challenging environments, and still deliver high target detection, localization and tracking. These environments include through the wall imaging, rugged terrain and rough surface/subsurface. In these cases, one seeks mitigation of the adverse effects of clutter and multipath via the implementation of effective signal processing strategies and electromagnetic modeling.

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Coherence-Factor-Based Rough Surface Clutter Suppression for Forward-Looking GPR Imaging

Cited by 13 publications

References 39 publications

Robust Wiener filter‐based time gating method for detection of shallowly buried objects

Robust Wiener filter‐based time gating method for detection of shallowly buried objects

Analysis and Validation of a Hybrid Forward-Looking Down-Looking Ground Penetrating Radar Architecture

Editorial for Special Issue “Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms”

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