Lena M. Klasen

Characterizing targets and backgrounds for 3D laser radars

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 produces 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.

An information system for target recognition

We present an approach to a general decision support system. The aim is to cover the complete process for automatic target recognition, from sensor data to the user interface. The approach is based on a query-based information system, and include tasks like feature extraction from sensor data, data association, data fusion and situation analysis. Currently, we are working with data from laser radar, infrared cameras, and visual cameras, studying target recognition from cooperating sensors on one or several platforms. The sensors are typically airborne and at low altitude. The processing of sensor data is performed in two steps. First, several attributes are estimated from the (unknown but detected) target. The attributes include orientation, size, speed, temperature etc. These estimates are used to select the models of interest in the matching step, where the target is matched with a number of target models, returning a likelihood value for each model. Several methods and sensor data types are used in both steps. The user communicates with the system via a visual user interface, where, for instance, the user can mark an area on a map and ask for hostile vehicles in the chosen area. The user input is converted to a query in ΣQL, a query language developed for this type of applications, and an ontological system decides which algorithms should be invoked and which sensor data should be used. The output from the sensors is fused by a fusion module and answers are given back to the user. The user does not need to have any detailed technical knowledge about the sensors (or which sensors that are available), and new sensors and algorithms can easily be plugged into the system.

Methods for recognition of natural and man-made objects using laser radar data

Over the years imaging laser radar systems have been developed for both military and civilian (topographic) applications. Among the applications, 3D data is used for environment modeling and object reconstruction and recognition. The data processing methods are mainly developed separately for military or topographic applications, seldom both application areas are in mind. In this paper, an overview of methods from both areas is presented. First, some of the work on ground surface estimation and classification of natural objects, for example trees, is described. Once natural objects have been detected and classified, we review some of the extensive work on reconstruction and recognition of man-made objects. Primarily we address the reconstruction of buildings and recognition of vehicles. Further, some methods for evaluation of measurement systems and algorithms are described. Models of some types of laser radar systems are reviewed, based on both physical and statistical approaches, for analysis and evaluation of measurement systems and algorithms. The combination of methods for reconstruction of natural and man-made objects is also discussed. By combining methods originating from civilian and military applications, we believe that the tools to analyze a whole scene become available. In this paper we show examples where methods from both application fields are used to analyze a scene.

Aided target recognition from 3D laser radar data

This paper presents our ongoing research activities on target recognition from data generated by 3-D imaging laser radar. In particular, we focus on future full flash imaging 3-D sensors. Several techniques for laser range imaging are applied for modelling and simulation of data from this kind of 3-D sensor systems. Firstly, data from an experimental gated viewing system is used. Processed data from this system is useful in assisting an operator in the target recognition task. Our recent work on target identification at long ranges, using range data from the gated viewing system, provides techniques to handle turbulence, platform motion and illumination variances from scintillation and speckle noise. Moreover, the range data is expanded into 3-D by using a gating technique that provides reconstruction of the target surface structure. This is shown at distances out to 7 km. Secondly, 3-D target data is achieved at short ranges by using different scanning laser radar systems. This provides high-resolution 3-D data from scanning a target from one single view. However, several scans from multiple viewing angles can also quite easily be merged for more detailed target representations. This is, for example, very useful for recognizing targets in vegetation. Hereby, we achieve simulated 3-D sensor data from both short and long ranges (100 meters out to 7 km) at various spatial resolutions. Thirdly, real data from the 3-D flash imaging system by US Air Force Research Lab (AFRL/SNJM), Wright Patterson Air Force Base, has recently been made available to FOI and also used as input in the development of aided target recognition methods. High-resolution 3-D target models are used in the identification process and compared to the 3-D target data (point cloud) from the various laser radar systems. Finally, we give some examples from our work that clearly show that future 3-D laser radar systems in cooperation with signal- and image analysis techniques have a great potential in the non-cooperative target recognition task and will provide several new and interesting capabilities, for example, to reveal targets hidden in vegetation.

Gated viewing in the atmosphere: a study of performance limits

The main purpose of the work presented here is to study the potential for an active imaging system for target recognition at long distances. This work is motivated by the fact that there are a number of outdoor imaging needs where conventional passive electro optical (EO) and infrared (IR) imaging systems are limited due to lack of photons, disturbing background, obscurants or bad weather. With a pulsed illuminating source, several of these problems are overcome. Using a laser for target illumination, target recognition at 10s of km can be achieved. Powerful diode pumped lasers and camera tubes with high spatial and time resolution will make this technique an interesting complement to passive EO imaging. Beside military applications, civilian applications of gated viewing for search and rescue, vehicle enhanced vision and other applications are in progress. To study the performance limitations of gated viewing systems due to camera, optics and the atmosphere an experimental system was developed. Measurements up to 10 km were made. The measurements were taken at the wavelength 532 nm. To extrapolate the results to future system performance at an eye safe wavelength, 1.5 micrometers nm, a theoretical performance model was developed. This model takes into account the camera and atmospheric influence on resolution and image quality, measured as a signal-to-noise-ratio, SNR. The result indicates turbulence influence, in agreement with the modeling. Different techniques were tested for image quality improvement and the best results were obtained by applying several processing techniques to the images. Moreover, the tests showed that turbulence seriously limits the resolution for horizontal paths close to the ground. A tactical system at 1.5 micrometers should have better performance than the used 532 nm in atmospheric-limited applications close to ground level. The potential to use existing laser range finders and the eye safety issue motivates the future use of 1.5 micrometers for gated viewing.

Waco investigation: analysis of FLIR videotapes

This paper presents some of the image processing techniques that were applied to seek an answer to the question whether agents of the Federal Bureau of Investigation (FBI) directed gunfired against the Branch Davidian complex in the tragic event that took place in Waco, Texas, U.S., 1993. The task for this investigation was to provide a scientific opinion that clarified the cause of the questioned events, or flashes, that can be seen on one of the surveillance videotapes. These flashes were by several experts, concluded to be evidence of gunfire. However, there were many reasons to question the correctness of that conclusion, such as the fact that some of the flashes appeared on a regular basis. The main hypothesis for this work was that the flashes instead were caused by specular solar reflections. The technical approach for this work was to analyze and compare the flashes appearance. By reconstructing the spatial and temporal position of the sensor, the complex and the sun, the geometrical properties was compared to the theoretical appearance of specular solar reflections. The result showed that the flashes seen on the FLIR videotape, were caused by solar or heat reflections from single or multiple objects. Consequently, they could not form evidence of gunfire. Further, the result highlights the importance of considering the characteristics of the imaging system within investigations that utilizes images as information source. This is due to the need of separating real data from other phenomena (such as solar reflections), distortions and artifacts in a correct manner.