A New Fast Algorithm for Radar-Based Shape Reconstruction of Smoothly Varying Objects

González-Valdés, Borja; Martínez-Lorenzo, José Ángel; Rappaport, Carey M.

doi:10.1109/lawp.2013.2250895

Cited by 3 publications

(12 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a second step, the amplitude and phase of the SAR image are combined to extract constant phase lines or phasefronts. In a third step, a model-based inversion, which uses a phase formulation relating the actual measured field and the field scattered by the controlled displacement of a first guess contour, is used [16], [17]. Different first guess contours are selected from the phasefronts extracted in the previous step.…”

Section: Methodology Descriptionmentioning

confidence: 99%

“…The obtained phasefronts are sequentially used as a first guess for a Physical Optics model-based inversion [16], [17]. The method is based on an approximation of the nonlinear relationship between the actual scattered field and the one generated by controlled displacements from a first guess contour, as presented in Fig.…”

Section: Model Based Inversion Methodsmentioning

confidence: 99%

“…In previous works, the first guess was estimated from a priori knowledge of the object under test. For the application presented in this paper the following error function is minimized at each frequency [17]:…”

Section: Model Based Inversion Methodsmentioning

confidence: 99%

“…The objective of the minimization is to find the values of the vector of distances between the first guess and actual positions of the facets, τ i , that minimizes the euclidean norm of the error function in (8). In order to solve this non-linear minimization problem, with cost function e p , the Levenberg-Marquardt [17], [21] algorithm is used.…”

Section: Model Based Inversion Methodsmentioning

confidence: 99%

“…The first contour estimation, obtained from the SAR inversion, is used as first guess for the model-based inversion. The use of a fast implementation of the SAR algorithm [15] combined with an efficient model-based inversion [16], [17] allows for high resolution contour reconstruction of electrically large scatterers using very limited bandwidth. In addition, the algorithm can generate real time results.…”

mentioning

confidence: 99%

See 4 more Smart Citations

On the Combination of SAR and Model Based Techniques for High-Resolution Real-Time Two-Dimensional Reconstruction

González-Valdés

Álvarez

Martínez-Lorenzo

et al. 2014

IEEE Trans. Antennas Propagat.

Self Cite

View full text Add to dashboard Cite

Abstract-A novel, real-time, two-dimensional method to find the shape of a body from its scattered electric fields is presented. The method is based on a unique combination of the information obtained from the target using the SAR formulation with a novel fast model-based inversion. In the first step, a fast implementation of the SAR inversion is used to recover an initial estimate of the body shape. Secondly, the phase and amplitude of the SAR image are used to extract a set of first guess contours close to the actual position of the body under test. In a third step, these contours are used as a starting point for a model-based inversion in order to disregard the contours that do not match the body profile and to improve the final result. Resolution of less than half of a wavelength for the proposed method is achieved using representative simulation results and measured data

show abstract

Section: Methodology Descriptionmentioning

confidence: 99%

Section: Model Based Inversion Methodsmentioning

confidence: 99%

Section: Model Based Inversion Methodsmentioning

confidence: 99%

Section: Model Based Inversion Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

On the Combination of SAR and Model Based Techniques for High-Resolution Real-Time Two-Dimensional Reconstruction

González-Valdés

Álvarez

Martínez-Lorenzo

et al. 2014

IEEE Trans. Antennas Propagat.

Self Cite

View full text Add to dashboard Cite

show abstract

A feasibility study of radar-based shape and reflectivity reconstruction using variational methods

Bignardi¹,

Yezzi²,

Yıldırım³

et al. 2021

Inverse Problems

View full text Add to dashboard Cite

Remote sensing radar techniques provide highly detailed imaging. Nevertheless, radar images do not offer directly retrievable representations of shape within the scene. Therefore, shape reconstruction from radar typically relies on applying post-processing computer vision techniques, originally designed for optical images, to radar imaging products. Shape reconstruction directly from raw data would be desirable in many applications, e.g. in computer vision and robotics. In this perspective, inversion seems an attractive approach. Nevertheless, inversion has seldom been attempted in the radar context, as high frequency signals lead to energy functionals dominated by tightly packed narrow local minima. In this paper, we take the first step in developing a framework in which radar signals and images can be jointly used for shape reconstruction. In particular, we investigate the feasibility of shape reconstruction by inversion of pulse-compressed radar signals alone, collected at sparse locations. Motivated by geometric methods that have matured within the fields of image processing and computer vision, we pose the problem in a variational context obtaining a partial differential equation for the evolution of an initial shape towards the shape-reflectivity combination that best reproduces the data. While doing so, we highlight several non-obvious difficulties encountered and discuss how to surpass them. We illustrate the potential of this approach through three simulated examples and discuss several implementation choices, including boundary conditions, reflectivity estimation, and radiative models. The success of our simulations shows that this variational approach can naturally accommodate radar inversion and has the potential for further expansion towards active surfaces and level set applications, where we believe it will naturally complement current applications with optical images.

show abstract

A hybrid SAR - Model based method for high resolution imaging

González-Valdés

Martínez-Lorenzo

Rappaport

et al. 2014

2014 IEEE Antennas and Propagation Society International Symposium (APSURSI)

Self Cite

View full text Add to dashboard Cite

This paper describes a novel fast, two-dimensional method to find the shape of a body from its scattered electric field. The method combines the information extracted from the target using the SAR formulation with a fast model-based inversion in three steps: (1) The SAR image is formed, recovering an initial estimate of the body shape; (2) The phase and amplitude of the SAR image are used to extract a set of first guess contours close to the actual position of the body under test; and (3) these contours are used as a starting point for a model-based inversion, disregarding those that do not match the body profile, and refining the others. Measurement-based results prove that the method is able to achieve resolution of less than half of a wavelength.

show abstract

A New Fast Algorithm for Radar-Based Shape Reconstruction of Smoothly Varying Objects

Cited by 3 publications

References 12 publications

On the Combination of SAR and Model Based Techniques for High-Resolution Real-Time Two-Dimensional Reconstruction

On the Combination of SAR and Model Based Techniques for High-Resolution Real-Time Two-Dimensional Reconstruction

A feasibility study of radar-based shape and reflectivity reconstruction using variational methods

A hybrid SAR - Model based method for high resolution imaging

Contact Info

Product

Resources

About