Aided target recognition from 3D laser radar data

Klasen, Lena M.; Andersson, Pierre; Larsson, Håkan; Chevalier, Tomas; Steinvall, Ove

doi:10.1117/12.542434

Cited by 9 publications

(5 citation statements)

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“…Since it can obtain a high-resolution range or profile image, the laser radar owns potential applications in many fields such as architectural survey, space exploration, robot vision, precision guidance, vehicle anti-collision, etc. [1][2][3][4][5] In recent years, the laser radar technology has been developed rapidly, and many novel equipments have been designed and used in our life. However, there has little work on studying the quality of range images obtained by the laser radar.…”

Section: Introductionmentioning

confidence: 99%

Research on the effect of laser radar system parameters on the range image quality

et al. 2011

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The quality of the range image obtained by laser radar will directly influence the target profile reconstruction and the target identification, and the quality of the range image is mainly determined by the parameters of laser radar system. As a result, this paper concentrates on discussing the effect of laser radar's parameters on the quality of range image. To evaluate the quality of range image quantitatively, two parameters, the mean squared error of range (R-MSE) and peak signal noise ratio of range (R-PSNR), are introduced and a simulation program is developed to study the influence of system's parameters on the range imaging quality. The results show that for a given pulse width, there has an optimal bandwidth and threshold level, that make the range image has better image quality. Above results have important significance to optimize the parameter design of laser radar.

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Section: Introductionmentioning

confidence: 99%

Research on the effect of laser radar system parameters on the range image quality

et al. 2011

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“…The purpose of this paper is to present data for vegetation penetration from the aspects of target detection and classification and also to see how the additional information from the reflectance of targets and background may be used to predict the laser radar performance. There are several concepts under study for high resolution 3 D laser imaging for example the FM/CW approach using a modulated laser and a "self mixing FPA" architecture 2 developed by ARL, the modulated gain tube and modulated laser approach developed by Sandia 3 , and the streak-tube imaging lidar (STIL) 4,5 developed by Arete, and different 3 D imaging techniques based on more conventional range gated imaging 6,7 .…”

Section: Introductionmentioning

confidence: 99%

Characterizing targets and backgrounds for 3D laser radars

et al. 2004

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Exciting development is taking place in 3 D sensing laser radars. Scanning systems are well established for mapping from airborne and ground sensors. 3 D sensing focal plane arrays (FPAs) enable a full range and intensity image can be captured in one laser shot. Gated viewing systems also produce 3 D target information. Many applications for 3 D laser radars are found in robotics, rapid terrain visualization, augmented vision, reconnaissance and target recognition, weapon guidance including aim point selection and others. The net centric warfare will demand high resolution geo-data for a common description of the environment. At FOI we have a measurement program to collect data relevant for 3 D laser radars using airborne and tripod mounted equipment for data collection. Data collection spans from single pixel waveform collection (1 D) over 2 D using range gated imaging to full 3 D imaging using scanning systems. This paper will describe 3 D laser data from different campaigns with emphasis on range distribution and reflections properties for targets and background during different seasonal conditions. Example of the use of the data for system modeling, performance prediction and algorithm development will be given. Different metrics to characterize the data set will also be discussed.

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“…Laser radar, in contrast to passive imaging systems, provides both intensity and range information, see e.g. [41], [34], [27], [26] and [47]. The 3-D image can be derived from a few range gated images or from each pixel directly coded in range and intensity using a focal plane array or a scanning system with one or few detector elements.…”

Section: Laser Imagingmentioning

confidence: 99%

“…This work is described in [41], [7], [42], [26], [27], [20], [43] and [8]. To obtain point clouds at long ranges, data achieved by an experimental GV system [42], [25] out to 14 km was used, in combination with a method for reconstruction of the surface structure [7].…”

Section: Object Recognitionmentioning

confidence: 99%

Advanced Multifunctional Sensor Systems

Klasen

NATO Science for Peace and Security Series B: Physics and Biophysics

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This work addresses the role of multifunctional sensor systems in defence and security applications. The challenging topic of imaging sensors and their use in object detection is explored. We give a brief introduction to selected sensors operating at various wavelength bands in the electromagnetic spectra. Focus here is on sensors generating time or range resolved data and spectral information. The sensors presented here are imaging laser radar, multi-and hyper-spectral sensors and radar systems. For each of these imaging systems, we present and discuss analysis and processing of the multidimensional (n-dimensional) data obtained from these sensors. Moreover, we will discuss the benefits of using collaborative sensors, based on results from several ongoing Swedish research projects aiming to provide endusers of such advanced sensor systems with new and enhanced capabilities. Major applications of this kind of systems are found in the areas of surveillance and situation awareness, where the complementary information provided by the imaging systems proves useful for enhanced systems capacity. Typical capabilities that we are striving for are, e.g., robust identification of objects being possible threats on a sub-pixel basis from spectral data, or penetrating obscurant such as vegetation or certain building construction materials. Hereby we provide building blocks for solutions to, e.g., detecting unexploded ammunition or mines and identification of suspicious behavior of persons. Furthermore, examples of detection, recognition, identification or understanding of small, extended and complex objects, such as humans, will be included throughout the chapter. We conclude with some remarks on the use of imaging sensors and collaborative sensor systems in security and surveillance.

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Aided target recognition from 3D laser radar data

Cited by 9 publications

References 0 publications

Research on the effect of laser radar system parameters on the range image quality

Research on the effect of laser radar system parameters on the range image quality

Characterizing targets and backgrounds for 3D laser radars

Advanced Multifunctional Sensor Systems

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