Resolution Analysis of Passive Synthetic Aperture Imaging of Fast Moving Objects

Borcea, Liliana; Garnier, Josselin; Papanicolaou, George; Sølna, Knut; Tsogka, Chrysoula

doi:10.1137/16m109716x

Cited by 10 publications

(11 citation statements)

References 20 publications

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“…In this context, we study the well-established matched-filter imaging method [5,19] and compare its performance with a correlation-based imaging method. Correlation-based imaging for fast moving objects has been considered in [2] where it was shown that two well-separated airborne pairs of receivers are sufficient for determining the target's location and velocity. We adopt here a simpler configuration with the receivers located on the ground.…”

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confidence: 99%

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Matched-Filter and Correlation-Based Imaging for Fast Moving Objects Using a Sparse Network of Receivers

Fournier¹,

Garnier²,

Papanicolaou³

et al. 2017

SIAM J. Imaging Sci.

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In this paper we consider the problem of imaging a fast moving small object. The imaging system consists of a powerful emitter and several passive receivers located on the ground. Our aim is to compare the well-known matched-filter imaging method with correlation-based imaging. Imaging with correlations has the advantage of not requiring any knowledge about the probing pulse and the emitter position, both assumed known with high accuracy in the case of matched-filter imaging. But correlation-based imaging requires recording fully resolved signals without down-ramping while matched-filer imaging does not. To account for the fast moving target's velocity, Doppler compensation is necessary for both imaging methods. Our resolution analysis, from first principles, shows that with the two methods we have similar resolution in the cross-range direction, for both the location and the velocity of the moving target. In the range direction, matched-filter imaging has better resolution mainly because it benefits from the signal bandwidth, which is not true for correlation-based imaging that relies on travel time differences. We also analyze the role of the number of receivers and show that a small number of them sparsely distributed provides an image with resolution close to the one obtained with a dense array of comparable overall size.

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confidence: 99%

“…For correlation-based imaging we do not need to know the pulse profile or the emission times but we need to record the whole train of scattered pulses. In this paper we assume a sufficiently high sampling rate so that the real-valued scattered signal can be recorded as in [2,1].…”

mentioning

confidence: 99%

Matched-Filter and Correlation-Based Imaging for Fast Moving Objects Using a Sparse Network of Receivers

Fournier¹,

Garnier²,

Papanicolaou³

et al. 2017

SIAM J. Imaging Sci.

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“…An interesting application of this modality is the synthetic aperture imaging of fast-moving objects (satellites or energetic debris) orbiting the earth, where the sources are powerful antennas on the ground and the receivers are mounted on aircraft that fly over the turbulent atmosphere [3], as illustrated in Figure 6. We refer the reader to [12,Chapter 10] for the analysis of the virtual source imaging method using the paraxial theory of wave propagation in random media summarized in the section "Gaussian beam in the random medium" and to [3] for the analysis of the imaging modality illustrated in Figure 6.…”

Section: Imaging With Noisy Sourcesmentioning

confidence: 99%

Imaging with Waves in Random Media

Borcea¹

2019

Notices Amer. Math. Soc.

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Wave-based imaging is an inverse problem for the wave equation, with a broad spectrum of applications in nondestructive testing, ultrasound for medical diagnosis, radar, underwater sonar, space surveillance, geophysical exploration, etc. Any imaging system uses sensors that measure sound, electromagnetic, or elastic waves generated by impulsive sources or by ambient noise sources. These waves carry information about the medium through which they travel and their initial state, and the goal of imaging is to extract this information from the sensor measurements, a.k.a. the data. The sensor configurations are application specific. The illustrations in Figure 1 show sensors that are closely spaced in a bounded set, so for imaging purposes they can be treated as a collective entity called an array. The

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“…For these reasons it is necessary to use imaging methods that are robust with respect to the fluctuations of the medium when it is randomly heterogeneous. In several studies Borcea and her co-workers [9,10,11,12,13,15,16,14,17] have introduced a new imaging modality called Coherent INTerferometry (CINT) whose principle is to back-propagate the cross correlations of the recorded signals, and not the signals themselves. In [16] the authors analyze the KM and CINT methods for passive and active arrays of sensors, and quantify their resolution limits and their signal-to-noise ratio (SNR).…”

Section: Introductionmentioning

confidence: 99%

“…More recently, correlation-based imaging have been used to observe fast moving objects [17,24]. In these papers, the authors introduce a Doppler compensation parameter which is used in the imaging function to provide the necessary correction of the movement of the object to be observed.…”

Section: Introductionmentioning

confidence: 99%

Coherent interferometric imaging in a random flow

Gay

Bonnet

Peyret

et al. 2021

Journal of Sound and Vibration

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This paper is concerned with the development of imaging methods to localize sources or reflectors in inhomogeneous moving media with acoustic waves that have travelled through them. A typical example is the localization of broadband acoustic sources in a turbulent jet flow for aeroacoustic applications. The proposed algorithms are extensions of Kirchhoff migration (KM) and coherent interferometry (CINT) which have been considered for smooth and randomly inhomogeneous quiescent media so far. They are constructed starting from the linearized Euler equations for the acoustic perturbations about a stationary ambient flow. A model problem for the propagation of acoustic waves generated by a fixed point source in an ambient flow with constant velocity is addressed. Based on this result imaging functions are proposed to modify the existing KM and CINT functions to account for the ambient flow velocity. They are subsequently tested and compared by numerical simulations in various configurations, including a synthetic turbulent jet representative of the main features encountered in actual jet flows.

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Resolution Analysis of Passive Synthetic Aperture Imaging of Fast Moving Objects

Cited by 10 publications

References 20 publications

Matched-Filter and Correlation-Based Imaging for Fast Moving Objects Using a Sparse Network of Receivers

Matched-Filter and Correlation-Based Imaging for Fast Moving Objects Using a Sparse Network of Receivers

Imaging with Waves in Random Media

Coherent interferometric imaging in a random flow

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