Margaret Cheney - Profile on Academia.edu (original) (raw)

Papers by Margaret Cheney

2006 International Waveform Diversity & Design Conference, 2006

In [28], we presented a synthetic aperture radar (SAR) inversion method in which the backscatter ... more In [28], we presented a synthetic aperture radar (SAR) inversion method in which the backscatter measurements are collected from known but arbitrary flight path and non-flat topography corrupted with clutter and noise. The objective of the current work is to design transmit waveforms and receive filters jointly to perform clutter suppression by adaptive transmit. Our approach starts with the development of a physics based forward model for SAR. Next, we formulate design of clutter rejecting waveforms as a variational problem using the minimum mean square error criteria. The resulting waveforms lead to an adaptive linear least squares transmit scheme in which waveforms vary at every point on the flight path based on the clutter and target spectral density functions.

This paper develops theory for an iterative experimental approach to use one or more antennas to ... more This paper develops theory for an iterative experimental approach to use one or more antennas to identify resonances of a scattering system, which could consist of the antennas and one or more scattering objects. We include realistic mathematical models for the antennas and for target(s), and we show that the resonances include effects from the antennas and wave propagation as well as the target scattering operator and its poles. We show how the effects of the antennas and wave propagation paths can be removed, to leave only the effect of the target scattering operator. We include simulations for the case of one and two cylindrical dipole antennas probing a dielectric sphere, and we show the effect of antenna resonances on the iterative experimental process. (Less)

Inverse Problems, 2019

Many state-of-the-art methods in source localization require large numbers of sensors and perform... more Many state-of-the-art methods in source localization require large numbers of sensors and perform poorly or require additional sensors when emitters of interest transmit highly correlated waveforms. We present a new source localization technique which employs a cross correlation measure of the Time Difference of Arrival (TDOA) for signals recorded at two separate platforms, at least one of which is in motion. This data is backprojected through a process of Synthetic Aperture Source Localization (SASL) to form an image of the locations of the emitters in a Region of Interest (ROI) This method has the advantage of not requiring any a priori knowledge of the number of emitters in the scene. Nor does it rest on an ability to identify regions of the data which come from individual emitters, though if this capability is present it may improve image quality. We demonstrate that this method is capable of localizing emitters which transmit highly correlated waveforms, though complications arise when several such emitters are present in the scene. We discuss these complications and strategies to mitigate them.

Public reporting burden for this collection of information is estimated to average 1 hour per res... more Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Washington Headquarters Services, Directorate for Information Operations and Reports,

This project dealt with radar remote sensing problems, including radar systems involving multiple... more This project dealt with radar remote sensing problems, including radar systems involving multiple transmitters and receivers, and the identification of targets in a complex environment. The project developed various imaging algorithms similar to synthetic-aperture radar. 14. SUBJECT TERMS radar imaging, synthetic-aperture radar (SAR) 15. NUMBER OF PAGES 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT unclassified

IEEE Transactions on Aerospace and Electronic Systems, 2017

Radar tracking of aircraft targets at low elevation angles can be complicated by clutter from win... more Radar tracking of aircraft targets at low elevation angles can be complicated by clutter from wind turbines, which we define to be clutter. In this paper, we study detection in a staring pulse-Doppler radar. By exploiting the second-order correlation structure of this wind-turbine clutter we derive a target detector that uses a sequence of adaptive coherence scores. The detector uses a multipulse coherence statistic consisting of an incoherent geometric average of coherently computed adaptive coherence scores. The detector compares favorably to a multipulse coherence detector that uses no modeling or estimation of the clutter.

Inverse Problems, 2017

This paper develops a mathematical method for determining the locations of multiple transmitters ... more This paper develops a mathematical method for determining the locations of multiple transmitters from passive measurements of the signals at two or more receivers. The method applies to the case of emitters transmitting either wideband or narrowband signals.

IEEE Transactions on Geoscience and Remote Sensing, 2017

Typical synthetic aperture radar imaging techniques neglect the dispersive nature of the so-calle... more Typical synthetic aperture radar imaging techniques neglect the dispersive nature of the so-called image "reflectivity" function over the bandwidth of the transmitted waveform. In this paper, we form an image of the complex scene reflectivity as it depends on (x, y, and frequency), or equivalently (x, y, and time delay), a technique we refer to as hyperspectral synthetic aperture radar (HSAR). Our approach is based on a signal model that allows arbitrary flight trajectories and arbitrary waveforms (including continuously transmitting signals such as noise waveforms), and incorporates the causal, dispersive nature of the scene reflectivity without resorting to resolution-degrading frequency-domain subbanding as others have previously proposed. We describe the resulting joint timespace resolution of HSAR in terms of the imaging point spread function for a selection of geometries and waveform bandwidths, and provide numerical examples to illustrate the approach.

IEEE Transactions on Antennas and Propagation, 2016

This paper considers a distributed wave-based sensing system that probes a scene consisting of mu... more This paper considers a distributed wave-based sensing system that probes a scene consisting of multiple interacting idealized targets. Each sensor is a collocated transmitreceive pair that is capable of transmitting arbitrary wideband waveforms. We address the problem of finding the space-time transmit waveform that provides the best target detection performance in the sense of maximizing the energy scattered back into the receivers. Our approach is based on earlier theoretical work that showed, for an idealized infinite half-space geometry, that the solution could be constructed by an iterative time-reversal (TR) process. In this paper, we give a more realistic example involving a two-sensor time-domain system. We show that for this system, the iterative TR process can be used to tune automatically to all the target resonances that are within the bandwidth of the interrogating radar system. We show that although obtaining eigenvalues (and hence resonances) of the scattering operator is in general unstable, using the iterative TR process to obtain the resonances is a stable process. Moreover, we show that these resonance frequencies are connected to the poles of the singularity expansion method.

Automatic Target Recognition XIX, 2009

We present a new image reconstruction method for distributed apertures operating in complex envir... more We present a new image reconstruction method for distributed apertures operating in complex environments with additive non-stationary noise. Our method is capable of exploiting information that we might have about: multipath scattering in the environment; statistics of the objects to be imaged; statistics of the additive nonstationary noise. The aperture elements are distributed spatially in an arbitrary fashion, and can be several hundred wavelengths apart. Furthermore, our method facilitates multiple transmit apertures which operate simultaneously, and is thus capable of handling a true multi-transmit-multi-receive scenario. We derive a set of basis functions which is adapted to the given operating environment and sensor distribution. By selecting an appropriate subset of these basis functions we obtain a sub-space reconstruction which is optimal in the sense of obtaining the minimum-mean-square-error for the reconstructed image. Furthermore, as this subspace determines which details will be visible in the reconstructed image, it provides a tool for evaluating the sensor locations against the objects that we would like to see in the image. The implementation of our reconstruction takes the form of a filter bank which is applied to the pulse-echo measurements. This processing can be performed independently on the measurements obtained from each receiving element. Our approach is therefore well suited for parallel implementation, and can be performed in a distributed manner in order to reduce the required communication bandwidth between each receiver and the location where the results are merged into the final image. We present numerical simulations which illustrate capabilities of our method.

2012 IEEE Radar Conference, 2012

This paper presents an analytic inversion scheme for polarimetric synthetic-aperture radar in the... more This paper presents an analytic inversion scheme for polarimetric synthetic-aperture radar in the case of an extended

In this paper we overview current efforts in the development of inverse methods which directly ex... more In this paper we overview current efforts in the development of inverse methods which directly extract target-relevant features from a limited data set. Such tomographic imaging problems arise in a wide range of fields making use of a number of different sensing modalities. Drawing these problem areas together is the similarity in the underlying physics governing the relationship between that which is sought and the data collected by the sensors. After presenting this physical model, we explore its use in two classes of feature-based inverse methods. Microlocal techniques are shown to provide a natural mathematical framework for processing synthetic aperture radar data in a manner that recovers the edges in the resulting image. For problems of diffusive imaging, we describe our recent efforts in parametric, shape-based techniques for directly estimating the geometric structure of an anomalous region located against a perhaps partially-known background.

Inverse Problems & Imaging, 2007

We derive an optimal transmit waveform for filtered backprojectionbased synthetic-aperture imagin... more We derive an optimal transmit waveform for filtered backprojectionbased synthetic-aperture imaging. The waveform is optimal in terms of minimising the mean square error (MSE) in the resulting image. Our optimization is performed in two steps: First, we consider the minimum-mean-square-error (MMSE) for an arbitrary but fixed waveform, and derive the corresponding filter for the filtered backprojection reconstruction. Second, the MMSE is further reduced by finding an optimal transmit waveform. The transmit waveform is derived for stochastic models of the scattering objects of interest (targets), other scattering objects (clutter), and additive noise. We express the waveform in terms of spatial spectra for the random fields associated with target and clutter, and the spectrum for the noise process. This approach results in a constraint that involves only the amplitude of the Fourier transform of the transmit waveform. Therefore, considerable flexibility is left for incorporating additional requirements, such as minimal variation of transmit amplitude and phase-coding.

SPIE Proceedings, 2007

The idea of preconditioning transmit waveforms for optimal clutter rejection in radar imaging is ... more The idea of preconditioning transmit waveforms for optimal clutter rejection in radar imaging is presented. Waveform preconditioning involves determining a map on the space of transmit waveforms, and then applying this map to the waveforms before transmission. The work applies to systems with an arbitrary number of transmitand receive-antenna elements, and makes no assumptions about the elements being co-located. Waveform preconditioning for clutter rejection achieves efficient use of power and computational resources by distributing power properly over a frequency band and by eliminating clutter filtering in receive processing.

Algorithms for Synthetic Aperture Radar Imagery XV, 2008

Inverse Problems, 2008

We derive a new image reconstruction method for distributed apertures operating in complex enviro... more We derive a new image reconstruction method for distributed apertures operating in complex environments. The aperture elements can be distributed spatially in an arbitrary fashion, can be several hundred wavelengths apart, and can involve transmission from multiple elements simultaneously. Moreover, the object to be imaged can be either in the near-field or far-field of the array. Our method is capable of exploiting information about multi-path scattering in the environment, statistics of the objects to be imaged and statistics of the additive (possibly non-stationary) noise. We formulate the image reconstruction problem as an inversion of a bilinear mapping that maps object reflectivity to an operator which in turn acts on the transmitted waveforms. We use transmitted waveforms to reveal the action of this bilinear mapping. We develop a minimum-norm inversion which takes the form of a family of linear operators applied to the pulse-echo measurements. This processing is implemented by means of inner products between the measurements and precomputed quantities, separately for each receiving element. Our approach is therefore well suited for parallel implementation, and can be performed in a distributed manner.

Inverse Problems, 1998

This paper considers an inverse problem for wave propagation in a perturbed, dissipative half-spa... more This paper considers an inverse problem for wave propagation in a perturbed, dissipative half-space. The perturbation is assumed to be compactly supported. This paper shows that in dimension three, the perturbation is uniquely determined by knowledge of the Dirichlet-to-Neumann map on an open subset of the boundary.

International Journal of Imaging Systems and Technology, 2004

This paper considers Synthetic Aperture Radar and other synthetic aperture imaging systems in whi... more This paper considers Synthetic Aperture Radar and other synthetic aperture imaging systems in which a backscattered wave is measured from a variety of locations. We focus on the case in which the ground-reflectivity function depends on frequency as well as on position. The paper begins with a (linearized) mathematical model, based on a scalar approximation to Maxwell's equations, that includes the effects of the source waveform and the antenna beam pattern. The model can also accommodate other effects such as antenna steering and motion. For this mathematical model, we use the tools of microlocal analysis to develop and analyze a three-dimensional inversion algorithm that uses measurements made on a surface and determines the frequency-dependent ground reflectivity.

Geophysical Journal International, 2010

We consider the problem of using scattered waves to recover an image of the medium in which the w... more We consider the problem of using scattered waves to recover an image of the medium in which the waves propagate. We address the case of scalar waves when the sources and receivers are sparse and irregularly spaced. Our approach is based on the single-scattering (Born) approximation and the generalized Radon transform. The key to handling sparse sources and receivers is the development of a data-weighting scheme that compensates for non-uniform sampling. To determine the appropriate weights, we formulate a criterion for measuring the optimality of the point-spread function, and solve the resulting optimization problem using regularized least squares. Once the weights are determined, they can be used to compute the point-spread function and thus determine resolution, and they can also be applied to the measured data to form an image. Tests of our minimization scheme with different regularization parameters show that, with appropriate weighting, individual scatterers can be resolved at subwavelength scales even when data is noisy and the locations of both sources and receivers are uncertain. We show an example in which the source-receiver geometry and frequency bandwidths correspond to seismic imaging from multiple local earthquakes (passive seismic imaging). The example shows that the weights determined by our method improve the resolution relative to reconstructions with constant weights.

We develop a linearized imaging theory that combines the spatial, temporal, and spectral aspects ... more We develop a linearized imaging theory that combines the spatial, temporal, and spectral aspects of scattered waves. We consider the case of fixed sensors and a general distribution of objects, each undergoing linear motion; thus the theory deals with imaging distributions in phase space. We derive a model for the data that is appropriate for any waveform, and show how it specializes to familiar results when the targets are far from the antennas and narrowband waveforms are used. We use a phase-space imaging formula that can be interpreted in terms of filtered backprojection or matched filtering. For this imaging approach, we derive the corresponding point-spread function. Special cases of the theory reduce to: a) Range-Doppler imaging, b) Inverse Synthetic Aperture Radar (ISAR) and Spotlight Synthetic Aperture Radar (SAR), c) Diffraction Tomography or Ultra-narrowband imaging, and d) Tomography of Moving Targets.