Modified Kirchhoff Migration for UWB MIMO Array-Based Radar Imaging

Zhuge, Xiaodong; Yarovoy, Alexander; Savelyev, T.G.; Ligthart, L.P.

doi:10.1109/tgrs.2010.2040747

Cited by 115 publications

(15 citation statements)

References 16 publications

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“…In air, the short-range imaging algorithms, including the back-propagation method [1], the Kirchhoff migration method [16] and the range migration methods (RMA) [1][2][3][4][5], are useful in different areas such as weapon detection [17].…”

Section: Radar Imaging In Airmentioning

confidence: 99%

Geometric approach for determining stationary phase points in radar imaging

Luomei,

Yin,

Tan

et al. 2024

Inverse Problems

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This paper proposes a geometric approach to find out the stationary phase points in radar imaging, namely the coordinates of the transmitting and the receiving antennas that have the greatest contribution to a specified point in the wavenumber spectrum of the scattered field. The foundation of the proposed approach is that, the Green’s function can be approximated by a locally plane wave when the distance between the individual antennas and the object is much larger than the wavelength. In this way, the stationary phase points can be easily found through geometric calculations, much more convenient than the prevailing algebraic approach of letting the first derivative of the phase term to be zero. Six examples for different propagation backgrounds and antenna setups are provided in this paper. It is demonstrated that, the proposed method is beneficial in eliminating extraneous roots of the stationary phase points, which could be generated by letting the first derivative of the phase term to be zero in the stationary phase method.

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Section: Radar Imaging In Airmentioning

confidence: 99%

Geometric approach for determining stationary phase points in radar imaging

Luomei,

Yin,

Tan

et al. 2024

Inverse Problems

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“…In this research, we applied the Kirchhoff migration, which is based on the generalised wave-equation [57,58]. Mathematically, the Kirchhoff migration method can be formulated in the time domain as follows:…”

Section: Kirchhoff Migrationmentioning

confidence: 99%

Mapping and Assessment of Tree Roots Using Ground Penetrating Radar with Low-Cost GPS

et al. 2020

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In this paper, we have presented a methodology combining ground penetrating radar (GPR) and a low-cost GPS receiver for three-dimensional detection of tree roots. This research aims to provide an effective and affordable testing tool to assess the root system of a number of trees. For this purpose, a low-cost GPS receiver was used, which recorded the approximate position of each GPR track, collected with a 500 MHz RAMAC shielded antenna. A dedicated post-processing methodology based on the precise position of the satellite data, satellite clock offsets data, and a local reference Global Navigation Satellite System (GNSS) Earth Observation Network System (GEONET) Station close to the survey site was developed. Firstly, the positioning information of local GEONET stations was used to filter out the errors caused by satellite position error, satellite clock offset, and ionosphere. In addition, the advanced Kalman filter was designed to minimise receiver offset and the multipath error, in order to obtain a high precision position of each GPR track. Kirchhoff migration considering near-field effect was used to identify the three-dimensional distribution of the root. In a later stage, a novel processing scheme was used to detect and clearly map the coarse roots of the investigated tree. A successful case study is proposed, which supports the following premise: the current scheme is an affordable and accurate mapping method of the root system architecture.

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“…Indeed, a MIMO GPR gathers a larger amount of useful data compared to a bistatic system and the increased amount of collected information yields an improvement in terms of target detection and reconstruction accuracy. Of course, specific data processing strategies are required [1]; accordingly, several approaches have been proposed to process data collected by down-looking and forward-looking MIMO GPR, and their performance has been assessed by performing numerical simulations or experimental tests, mainly in controlled conditions [2][3][4][5][6][7][8][9][10].…”

Section: Introduction He Ongoing Advances In Multiple Input Multiple ...mentioning

confidence: 99%

Contactless Microwave Tomography via MIMO GPR

Catapano

Gennarelli

Esposito

et al. 2023

IEEE Geosci. Remote Sensing Lett.

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This paper presents an imaging approach for Multiple Input Multiple Output Ground Penetrating Radar (MIMO GPR) systems working in down-looking contactless mode. The approach exploits a linear approximation of the scattering phenomenon and is based on a ray-based propagation model, which takes into account the presence of the air-soil interface. Accordingly, the Interface Reflection Point concept is extended to the case of MIMO GPR. The proposed approach performs the imaging in the 2D scalar case and applies the Truncated Singular Value Decomposition regularization scheme to perform the inversion. The effectiveness of the approach is assessed by processing synthetic and real data. The real data are referred to the lunar soil and have been collected by means of the Lunar Regolith Penetrating Radar, installed on the Chang'E-5 lander.

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Modified Kirchhoff Migration for UWB MIMO Array-Based Radar Imaging

Cited by 115 publications

References 16 publications

Geometric approach for determining stationary phase points in radar imaging

Geometric approach for determining stationary phase points in radar imaging

Mapping and Assessment of Tree Roots Using Ground Penetrating Radar with Low-Cost GPS

Contactless Microwave Tomography via MIMO GPR

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