Simon Ahlberg

An information fusion demonstrator for tactical intelligence processing in network-based defense

The Swedish Defence Research Agency (FOI) has developed a concept demonstrator called the Information Fusion Demonstrator 2003 (IFD03) for demonstrating information fusion methodology suitable for a future Network Based Defense (NBD) C4ISR system. The focus of the demonstrator is on real-time tactical intelligence processing at the division level in a ground warfare scenario. The demonstrator integrates novel force aggregation, particle filtering, and sensor allocation methods to create, dynamically update, and maintain components of a tactical situation picture. This is achieved by fusing physically modelled and numerically simulated sensor reports from several different sensor types with realistic a priori information sampled from both a high-resolution terrain model and an enemy organizational and behavioral model. This represents a key step toward the goal of creating in real time a dynamic, high fidelity representation of a moving battalion-sized organization, based on sensor data as well as a priori intelligence and terrain information, employing fusion, tracking, aggregation, and resource allocation methods all built on well-founded theories of uncertainty. The motives behind this project, the fusion methods developed for the system, as well as its scenario model and simulator architecture are described. The main services of the demonstrator are discussed and early experience from using the system is shared.

Three-dimensional environment models from airborne laser radar data

Detailed 3D environment models for visualization and computer based analyses are important in many defence and homeland security applications, e.g. crisis management, mission planning and rehearsal, damage assessment, etc. The high resolution data from airborne laser radar systems for 3D sensing provide an excellent source of data for obtaining the information needed for many of these models. To utilise the 3D data provided by the laser radar systems however, efficient methods for data processing and environment model construction needs to be developed. In this paper we will present some results on the development of laser data processing methods, including methods for data classification, bare earth extraction, 3D-reconstruction of buildings, and identification of single trees and estimation of their position, height, canopy size and species. We will also show how the results can be used for the construction of detailed 3D environment models for military modelling and simulation applications. The methods use data from discrete return airborne laser radar systems and digital cameras.

On analysis and visualization of full-waveform airborne laser scanner data

The ongoing technical developments on airborne laser scanner systems, with shorter pulses, increased operation altitudes, focal plane array detectors, full-waveform digitization and recoding, etc. provide new opportunities for the expansion and growth of military as well as civilian applications. However, for the continuing development of systems and applications one crucial issue is the research and development of new and efficient laser data processing methods for analysis and visualization. In this paper we will present some recent developments on visualization and analysis of full-waveform data. We will discuss visualization of waveform data by inserting the waveform samples in a 3D volume consisting of small 3D cells referred to as voxels. We will also present an approach for extracting additional 3D point data from the waveforms. The long term goal of this research is to develop methods for automated extraction of natural as well as man-made objects. The aim is to support the construction of high-fidelity 3D virtual environment models and detection and identification of man-made objects.

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.

Airborne laser radar: systems and methods for reconnaissance and terrain modeling

Recently a number of airborne nadir scanning laser radars have been developed for both military and civilian applications. These have range resolutions on the order of 10 cm but relatively moderate area coverage rates, in the range 1000 - 10,000 m2/s (3.6 - 36 km2/h) when operating in a high resolution mode with 0.25 m spot distance. Technology development in laser sources, scanning techniques and signal processing will probably improve the area coverage substantially and lead to compact systems suitable for new applications, including the use in UAV:s. Present nadir capability could be combined with a forward looking capability for guidance and obstacle avoidance in autonomous or semi-autonomous systems. The paper will investigate the potential performance of such combined systems using state-of-the-art lasers and receiver technology. Among the applications for both military and civilian users we note the collection of 3-D data for terrain modeling and object recognition. For these functions signal processing using multiple echo and intensity information is of great value as well as adding passive senor information. Full wave form processing will further improve the information for example to characterize trees. The use of high resolution 3-D data in synthetic environments is obvious and will be discussed. Experimental data collected with a commercial laser system, TopEye, developed by Saab Dynamics, will be shown and some image examples will be discussed in relation to different applications.

Generation of high-resolution terrain elevation models for synthetic environments using laser-radar data

In this paper, a technique for generation of terrain elevation data for synthetic environments from laser-radar images will be demonstrated. The method is characterized by maintaining the high resolution that is available in source data without too much loss of significant information in its data reduction process. Separation of forest information as well as other types of outstanding objects from the ground is another important step in the process of generating a reliable terrain elevation model. As a consequence, it is possible to generate terrain models with a resolution of less than 0.5 m and where data have been highly reduced.

3D Urban Models from Laser Radar Data

Updated geographic information and 3D models of environments are becoming increasingly important for applications such as city planning, crisis management, visualisation, architecture, and landscaping. The task of producing detailed geospecific terrain databases or 3D city models has traditionally been manual and thus time-consuming, and the availability of appropriate source data has been limited. The use of available sensors such as airborne laser scanners (ALS) and digital cameras provides new opportunities to acquire detailed remote sensing data of the natural environment. This type of data is very suitable as the basis for the construction of high-fidelity 3D virtual environment models. To make use of this new type of data and to develop applications as mentioned above requires new methods for processing 3D sensor data and extracting geographic feature information from the data. In this paper we present recent results from the development of methods for processing ALS data and for transforming the data into geographic information and environment models, with the emphasis on urban environments. The long term objective of our work is the development of new methods for rapid and highly automated extraction of geographic information to support the construction of high-fidelity 3D virtual environment models from remote sensing data. As remote sensing data we use data from current high resolution ALS systems and digital cameras.