This paper describes the development of a high resolution waveform recording laser scanner and presents results
obtained with the system. When collecting 3-D data on small objects, high range and transverse resolution is needed. In
particular, if the objects are partly occluded by sparse materials such as vegetation, multiple returns from a single laser
pulse may limit the image quality. The ability to resolve multiple echoes depends mainly on the laser pulse width and the
receiver bandwidth. With the purpose to achieve high range resolution for multiple returns, we have developed a high
performance 3-D LIDAR, called HiPer, with a short pulse fibre laser (500 ps), fast detectors (70 ps rise time) and a 20
GS/s oscilloscope for fast sampling. HiPer can acquire the full waveform, which can be used for off-line processing. This
paper will describe the LIDAR system and present some image examples. The signal processing will also be described,
with some examples from the off-line processing and the benefit of using the complete waveform.
Lidar has been identified as a promising sensor for remote detection of biological warfare agents (BWA). Elastic IR lidar
can be used for cloud detection at long ranges and UV laser induced fluorescence can be used for discrimination of BWA
against naturally occurring aerosols. This paper will describe a simulation tool which enables the simulation of lidar for
detection, tracking and classification of aerosol clouds. The cloud model was available from another project and has been
integrated into the model. It takes into account the type of aerosol, type of release (plume or puff), amounts of BWA,
winds, height above the ground and terrain roughness.
The model input includes laser and receiver parameters for both the IR and UV channels as well as the optical
parameters of the background, cloud and atmosphere. The wind and cloud conditions and terrain roughness are specified
for the cloud simulation. The search area including the angular sampling resolution together with the IR laser pulse
repetition frequency defines the search conditions. After cloud detection in the elastic mode, the cloud can be tracked
using appropriate algorithms. In the tracking mode the classification using fluorescence spectral emission is simulated
and tested using correlation against known spectra. Other methods for classification based on elastic backscatter are also
discussed as well as the determination of particle concentration. The simulation estimates and displays the lidar response,
cloud concentration as well as the goodness of fit for the classification using fluorescence.
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