A refinement of the Radon transform and its inverse

The Radon transform of a function is defined as an integration over planes whose normals vary over the entire unit sphere. The space is actually covered twice because the distance of the plane from the origin is allowed to be positive or negative. The usual inverse transform requires knowledge of the transform evaluated over the entire sphere. However, we shall show that only the transform over a hemisphere, which can consist of disconnected parts, is required to reconstruct the original function . Thus the redundancy of the double-covering is removed and only one-half of the transform is needed to recover the original function. In essence we have introduced optical coordinates. We then consider function f(x) obtained by applying the inverse Radon transform to an arbitrary function which has the same arguments as the Radon transform but is not, in general, a Radon transform. On applying the Radon transform to f(x) we find that only part of the arbitrary function, to which the inverse was applied, is reproduced. Thus the Radon transform has a left inverse but not a right inverse. However, by restricting the range of variables in the transform space, a right and left inverse can be obtained which are the same. Finally, we give Parseval’s theorem in terms of the refined Radon transform. Though we modify the older proofs for obtaining the Radon transform and its inverse, for the sake of a self-contained paper we also use new elementary proofs based on relations which we have derived between one­-dimensional and three-dimensional delta functions. We expect that our result will have consequences in tomography and other applications. We ourselves will use the result to obtain the exact fields for the scalar three-dimensional wave equation and Maxwell’s equations from fields in the wave zone, and, conversely, fields in the wave zone from the exact causal fields. In fact, the principal reason for our writing the present paper is to cast the Radon transform and its inverse in a form suitable for these applications. Though we shall prove our result for the three-dimensional case only, the proof for the general case can be inferred from our proof.

A method based on the Radon transform is presented to determine the displacement field in a general anisotropic solid due to the application of a time-harmonic point force. The Radon transform reduces the system of coupled partial differential equations for the displacement components to a system of coupled ordinary differential equations. This system is reduced to an uncoupled form by the use of properties of eigenvectors and eigenvalues. The resulting simplified system can be solved easily. A back transformation to the original coordinate system and a subsequent application of the inverse Radon transform yields the displacements as a summation of a regular elastodynamic term and a singular static term. Both terms are integrals over a unit sphere. For the regular dynamic term, the surface integration can be evaluated numerically without difficulty. For the singular static term, the surface integral has been reduced to a line integral over half a unit circle. Reductions to the cases of isotropy and transverse isotropy have been worked out in detail. Examples illustrate applications of the method.


2019 ◽  
Vol 16 (6) ◽  
pp. 625-637
Author(s):  
I. R. Gabdrakhmanov ◽  
D. Müller ◽  
O. V. Teryaev

Author(s):  
Renyuan Zhang ◽  
Siyang Cao

In this paper, a new millimeter wave 3D imaging radar is proposed. The user just needs to move the radar along a circular track, a high resolution 3D imaging can be generated. The proposed radar uses the movement of itself to synthesize a large aperture in both the azimuth and elevation directions. It can utilize inverse Radon transform to resolve 3D imaging. To improve the sensing result, compressed sensing approach is further investigated. The simulation and experimental result further illustrated the design. Because a single transceiver circuit is needed, a light, affordable and high resolution 3D mmWave imaging radar is illustrated in the paper.


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