Aided target recognition from 3D laser radar data

Abstract

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.