Accurate 3D models of natural environments are important for many modelling and simulation applications, for both civilian and military purposes. When building 3D models from high resolution data acquired by an airborne laser scanner it is de-sirable to separate and classify the data to be able to process it further. For example, to build a polygon model of a building the samples belonging to the building must be found. In this thesis we have developed, implemented (in IDL and ENVI), and evaluated algorithms for classification of buildings, vegetation, power lines, posts, and roads. The data is gridded and interpolated and a ground surface is estimated before the classification. For the building classification an object based approach was used unlike most classification algorithms which are pixel based. The building classifica-tion has been tested and compared with two existing classification algorithms. The developed algorithm classified 99.6 % of the building pixels correctly, while the two other algorithms classified 92.2 % respective 80.5 % of the pixels correctly. The algorithms developed for the other classes were tested with thefollowing result (correctly classified pixels): vegetation, 98.8 %; power lines, 98.2 %; posts, 42.3 %; roads, 96.2 %.

<p>Accurate 3D models of natural environments are important for many modelling and simulation applications, for both civilian and military purposes. When building 3D models from high resolution data acquired by an airborne laser scanner it is de-sirable to separate and classify the data to be able to process it further. For example, to build a polygon model of a building the samples belonging to the building must be found.</p><p>In this thesis we have developed, implemented (in IDL and ENVI), and evaluated algorithms for classification of buildings, vegetation, power lines, posts, and roads. The data is gridded and interpolated and a ground surface is estimated before the classification. For the building classification an object based approach was used unlike most classification algorithms which are pixel based. The building classifica-tion has been tested and compared with two existing classification algorithms. </p><p>The developed algorithm classified 99.6 % of the building pixels correctly, while the two other algorithms classified 92.2 % respective 80.5 % of the pixels correctly. The algorithms developed for the other classes were tested with thefollowing result (correctly classified pixels): vegetation, 98.8 %; power lines, 98.2 %; posts, 42.3 %; roads, 96.2 %.</p>

Thesis (doctoral)--Universität Bremen, 2007. / Includes bibliographical references (p. [153]-161).

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<p>Laser vibration sensing can be used to classify military targets by its unique vibration signature. A coherent laser radar receives the target´s rapidly oscillating surface vibrations and by using proper demodulation and Doppler technique, stationary, radially moving and even accelerating targets can be taken care of. </p><p>A frequency demodulation method developed at the former FOA, is for the first time validated against real data with turbulence, scattering, rain etc. The issue is to find a robust and reliable system for target recognition and its performance is therefore compared with some frequency distribution methods. The time frequency distributions have got a crucial drawback, they are affected by interference between the frequency and amplitude modulated multicomponent signals. The system requirements are believed to be fulfilled by combining the FOA method with the new statistical method proposed here, the combination being suggested as aimpoint for future investigations.</p>

LIDAR es un acrónimo de LIght Detection And Ranging. En la presente tesis, se usan técnicas basadas en lidar elástico para monitorizar la atmósfera remotamente y derivar información cuantitativa acerca de sus parámetros ópticos. Esta tesis doctoral comprende el diseño y operación de una estación lidar elástica basada en un láser pulsado de Nd:YAG operando a las longitudes de onda de 1064 y 532 nm, en lo que se refiere a los sistemas de recepción, control y diseño de algoritmos de inversión. Básicamente, puede dividirse en tres partes bien diferenciadas: La primera (Caps. 1, 2 y 3) comprende el estudio de la dispersión elástica (Rayleigh y Mie) en la atmósfera, orientada al cálculo del balance de enlace, e intenta vislumbrar la interrelación entre variables físicas tales como la temperatura, la presión y la humedad, y el fenómeno de dispersión, dejando de lado su posible extrapolación a modelos meteorologicos. Partiendo de esta base, se estiman valores de extinción y retrodispersión para diferentes condiciones atmosféricas y, como resultado, se presenta un balance de enlace para el sistema. El mismo incluye el estudio del alcance lidar, la estimación de la relación señal a ruido, y la evaluación de fotodiodos para diferentes librerías del usuario. Esta primera parte se cierra con las especificaciones globales del sistema. La segunda parte de este trabajo (Caps. 4, 5 y 6) atiende al diseño e implemen-tación del receptor, sistemas de sincronización y control. El receptor optoelectrónico se basa en amplificadores realimentados en corriente y cuenta con un excelente producto ganancia ancho de banda. Por lo que respecta al subsistema de sincronismo, se presentan dos unidades distintas con vistas a un futuro sistema lidar de escaneo, lo cuál ofrece la posibilidad de realizar scans entrelazados. Para terminar, el sistema de control diseñado se basa en el software de control LabView, que ofrece una filosofía de control distribuido. Con este propósito, se han especificado e implementado protocolos de bus lidar y su señalización para la presente estación lidar. Finalmente, la tercera parte comprende el diseño de algoritmos de inversión con y sin memoria (Caps. 7 y 8). Los algortimos sin memoria para atmósferas homogéneas se basan en procedimientos de ajuste por regresión como son el método de la pendiente y el de mínimos cuadrados y, en el caso de atmósferas inhomogéneas, se basan en el método de Klett y calibraciones adecuadas. Los algortimos con memoria se basan en diferentes modelos estocásticos para la atmósfera y filtrado de Kalman no lineal. Además de los algortimos de inversión, también se calculan y discuten las curvas del error de inversión. El Cap. 9 describe las medidas llevadas a cabo con el sistema que este trabajo ha permitido construir así como el resultado de aplicar los algoritmos de inversión presentados en los capítulos precedentes. La inversión de escenas reales comprende estudios de la estructura de polución, estudios de nubes (ceilometría, básicamente desplazamiento y estructura de las nubes) y señala posibles fuentes de error en el factor de solapamiento. / LIDAR is an acronym of LIght Detection And Ranging. In the present case, the elastic lidar techniques are used to remotely sense the atmosphere and to derive quantitative information about its optical parameters.This thesis comprises the design and operation of an elastic lidar station based on a pulsed Nd:YAG laser operating at the 1064- and 532-nm wavelengths, in the parts concerning receiver, control systems, and inversion algorithms.Basically, it can be divided in three different parts: The first one (Chaps. 1, 2, and 3) encompasses the study of the elastic scattering (Rayleigh and Mie) in the atmosphere for link-budget purposes and gives some insight into the interweaving between physical variables such as temperature, pressure and humidity, and the scattering phenomena, letting apart any possible extrapolation to meteorological models. From this basis, extinction and backscatter figures for different atmospheric conditions can readily be assessed and, as result, a system link budget is presented. This includes lidar range study, signal-to-noise ratio assessment, and photodiode evaluation from custom-made libraries. At the end of the first part, the system specification is made. The second part of this work (Chaps. 4, 5, and 6) is concerned with the design and implemen-tation of receiver, synchronization, and control systems. The optoelectronic receiver is based on current-feedback amplifiers and features a very large gain-bandwidth product. As for the synchronization subsystem, two different units are presented with a view to a future scanning lidar system, which makes room for interspersed scans. Eventually, the control system designed is LabView based and features a distributed control philosophy. For that purpose, lidar bus protocols and signals are specified and built for the actual lidar station. Finally, the third part encircles the design of inversion algorithms with and without memory (Chaps. 7 and 8). Non-memory algorithms for homogeneous atmospheres are based on regression curve-fitting procedures, such as the slope-method and the least squares while in instances of inhomogeneous atmospheres they are based on Klett's method and appropriate calibrations. Memory algorithms are based on different stochastic models for the atmosphere and on non-linear Kalman filtering. In addition to these inversion procedures, error assessment plots are also derived and discussed. Chap. 9 describes the measurements carried out with the system this work has contributed to build and the results of applying to them the inversion algorithms discussed in the preceding chapters.The inversion of live-scenes involves pollution structure studies, cloud studies (ceilometry, cloud motion and wave clouds, basically), and hints overlap factor error sources.

Laser vibration sensing can be used to classify military targets by its unique vibration signature. A coherent laser radar receives the target´s rapidly oscillating surface vibrations and by using proper demodulation and Doppler technique, stationary, radially moving and even accelerating targets can be taken care of. A frequency demodulation method developed at the former FOA, is for the first time validated against real data with turbulence, scattering, rain etc. The issue is to find a robust and reliable system for target recognition and its performance is therefore compared with some frequency distribution methods. The time frequency distributions have got a crucial drawback, they are affected by interference between the frequency and amplitude modulated multicomponent signals. The system requirements are believed to be fulfilled by combining the FOA method with the new statistical method proposed here, the combination being suggested as aimpoint for future investigations.

<p>Landminor är ett stort problem både under och efter krigstid. De metoder som används för att detektera minor har inte ändrats mycket sedan 1940-talet. Forskning med mål att utvärdera olika elektro-optiska sensorer och metoder som skulle kunna användas för att skapa mer effektiv min-detektion genomförs på FOI. Försök som har gjorts med data från bland annat laser-radar och IR-sensorer har gett intressanta resultat.</p><p>I det här examensarbetet utvärderades olika fenomen och egenskaper i laser-radar- och IR-data. De testade egenskaperna var intensitet, IR, ytlikhet och höjd.</p><p>En metod som segmenterar intressanta objekt och bakgrundsdata utformades och implementerades. Metoden använde sig av expectation-maximization-skattning och ett minimum message length-kriterium. Ett scatter separability-kriterium användes för att bestämma kvalitén på de olika egenskaperna och på den resulterande segmenteringen.</p><p>Data insamlad under en mätkampanj av FOI användes för att testa metoden. Resultatet visade bland annat att ytlikhetsmåttet gav en bra segmentering för stora objekt med släta ytor, men var sämre för små objekt med skrovliga ytor. Vid jämförelse med en manuellt skapad mål-mask visade det sig att metoden klarade av att välja ut egenskaper som i många fall gav en godkänd segmentering.</p> / <p>Land mines are a huge problem in conflict time and after. Methods used to detect mines have not changed much since the 1940's. Research aiming to evaluate output from different electro-optical sensors and develop methods for more efficient mine detection is performed at FOI. Early experiments with laser radar sensors show promising results, as do analysis of data from infrared sensors.</p><p>In this thesis, an evaluation is made of features found in laser radar- and in infrared -sensor data. The tested features are intensity, infrared, a surfaceness feature extracted from the laser radar data and height above an estimated ground plane.</p><p>A method for segmenting interesting objects from background data using theexpectation-maximization algorithm and a minimum message length criterion is designed and implemented. A scatter separability criterion is utilized to determine the quality of the features and the resulting segmentation.</p><p>The method is tested on real data from a field trial performed by FOI. The results show that the surfaceness feature supports the segmentation of larger object with smooth surfaces but gives no contribution to small object with irregular surfaces. The method produces a decent result of selecting contributing features for different neighbourhoods of a scene. A comparison with a manually created target mask of the neighbourhood and the segmented components show that in most cases a high percentage separation of mine data and background data is possible.</p>