Reflective tomography: images from rangeresolved laser radar measurements

Reflective Tomography Lidar Image Reconstruction for Long Distance Non-Cooperative Target

In the long-distance space target detection, the technique of laser reflection tomography (LRT) shows great power and attracts more attention for further study and real use. However, space targets are often non-cooperative, and normally a 360° complete view of reflection projections cannot be obtained. Therefore, this article firstly introduces an improved LRT system design with more advanced laser equipment for long-distance non-cooperative detection to ensure the high quality of the lidar beam and the lidar projection data. Then, the LRT image reconstruction is proposed and focused on the laser image reconstruction method utilizing the total variation (TV) minimization approach based on the sparse algebraic reconstruction technique (ART) model, in order to reconstruct the laser image in a sparse or incomplete view of projections. At last, comparative experiments with the system are performed to validate the advantages of this method with the LRT system. In both near and far field experiments, the effectiveness and superiority of the proposed method are verified for different types of projection data through comparison to typical methods.

Application of Image Fusion Algorithm Combined with Visual Saliency in Target Extraction of Reflective Tomography Lidar Image

Reflective tomography Lidar has been proved to be a new Lidar system with long distance and high resolution. The reflective tomography Lidar image is prone to clutter and artifacts; thus, it is important for space target recognition to extract the target from the image. In this study, we proposed image fusion algorithm combined with visual saliency could be applied to the target extraction of reflective tomography Lidar image, which can not only preserve the target information but also eliminate the clutter and artifacts in the image. The efficiency of this algorithm is shown by simulation and the experiment of the reflective tomography Lidar system. Also, we analyzed the main source of reflective tomography Lidar image artifacts and the reason why this algorithm could remove clutter and artifacts.

Bidirectional reflectance distribution function effects in ladar-based reflection tomography

Light reflection from a surface is described by the bidirectional reflectance distribution function (BRDF). In this paper, BRDF effects in reflection tomography are studied using modeled range-resolved reflection from well-characterized geometrical surfaces. It is demonstrated that BRDF effects can cause a darkening at the interior boundary of the reconstructed surface analogous to the well-known beam hardening artifact in x-ray transmission computed tomography (CT). This artifact arises from reduced reflection at glancing incidence angles to the surface. It is shown that a purely Lambertian surface without shadowed components is perfectly reconstructed from range-resolved measurements. This result is relevant to newly fabricated carbon nanotube materials. Shadowing is shown to cause crossed streak artifacts similar to limited-angle effects in CT reconstruction. In tomographic reconstruction, these effects can overwhelm highly diffuse components in proximity to specularly reflecting elements. Diffuse components can be recovered by specialized processing, such as reducing glints via thresholded measurements.

Reflective tomography reconstruction of satellite features-field results

We report on the first satellite feature reconstruction, to our knowledge, by use of range-resolved reflective tomography techniques from nonimaging laser radar data collected on an orbiting satellite. The reconstructed features were two retroreflectors mounted on a satellite. The data were collected with a coherent laser radar system located at the Maui Space Surveillance Site in Maui, Hawaii. We utilized a filtered backpropagation algorithm to reconstruct the images using intensity projections created from the raw data. Key components of the image reconstruction process included the calculation of tomographic angles, the alignment of the intensity projections to an appropriate center of rotation, and compensation for the lack of data for a full 360 degrees set of views.

Laboratory validation of range-resolved reflective tomography signal-to-noise expressions

The Air Force Phillips Laboratory is in the process of demonstrating an advanced space surveillance capability with a heterodyne laser radar (ladar) system. Notable features of this ladar system include its narrow micropulses (<1.5 ns) contained in a pulse-burst wave form that allows high-resolution range data to be obtained and its high power (30 J/pulse burst) that permits reasonable signal returns from satellites. Recently, time-resolved image-domain signal-to-noise ratios have been derived for both the intensity projections calculated from the range-resolved reflective data and image information obtained with linear combinations of the projections. In this paper the signal-to-noise expression for intensity projections is validated by laboratory data.

Laser radar reflective tomography utilizing a streak camera for precise range resolution

Tomography is used to reconstruct 2-D images from 1-D range-resolved laser radar data. A doubled mode-locked Nd:YAG pulsed laser illuminates a conical object, and a receiver utilizing a streak camera resolves the reflected light in time.