We argue for the integration of the statistical models already widely used in radar technology into lidar technology. The aim is to assess the validity or degree of confidence of an alert to be issued in view of not overloading the pilot with nuisance alerts. We present the basics of the detection theory. We give three examples of simulations illustrating the use of these statistical models either for designing lidars or for preparing lidar missions. We describe the simulator having been developed and used. We also present the idea of developing mixtures of statistical models as an approach to thresholding and object classification at mission time. Some experimental data are presented to validate both the simulator output and the use of mixtures of models for object segmentation or classification.
Operation under degraded visual environment (DVE) presents important strategic advantages. 3D mapping has been performed under DVE and good quality images have been obtained through DVE with active imaging systems. In these applications, the presence of fog clouds degrades the quality of the remotely sensed signal or even renders the operation totally impossible. In view of making the active imaging method more robust against dense fog, the use of polarimetry is herein studied. Spherical particles typical of fog do not depolarize incident polarized light in the backscattering (180°) direction. So, in principle, there should be less dazzling caused by aerosols for active imaging systems operating using the secondary polarization. However, strong depolarization still occurs at angles close to 180°. The greater the ratio of size to wavelength, the closer to 180° will the depolarization occur. When the cloud optical depth is small, the major scattering events seen by an active camera are the single backscattering events. However, when the optical depth of the cloud is higher than 1, multiple scattering becomes more important and causes depolarization due to the backscattering around 180°. The physics of this process will be discussed. Experimental results supporting the analysis will be presented. Those experimental results were obtained under controlled environment using the DRDC-Valcartier aerosol chamber. The experimental method herein proposed is based upon the use of ICCD range gated cameras wherein gate width and gate location may be varied on the fly. The optimal conditions for the use of these devices in view of obtaining the best image contrast are experimentally studied and reported in this paper.
It is generally admitted that the relative location of an aerosol between an observation device and the observed scene will have an influence on the detected image quality. These effects are usually classified under the label “shower curtain effect” (SCE). The usual formulation describing it is as follows: an observer standing away from a shower curtain can detect the presence of a person standing just behind it whereas the opposite is not true. Starting from a discussion of experimental results which seemed to invalidate the SCE, we show that it is not the only mechanism at work and that thorough analysis of the measurement setup is required before reaching such conclusion. We base our discussion on four cases, two of them of the passive detection type, the two others being of the active type. We also show that the ratio of scattered to unscattered light at the detector is of utmost importance. We show this by further developing our model [10] of the point spread function (PSF) of the receiver. This model allows the discussion of the SCE in the frequency domain in terms of the cuton and cutoff frequencies of the receiver. In the end, we show that the apparent paradoxical results we had found cannot actually be placed under the “shower curtain effect” denomination because: 1-) the amount of unscattered light captured is higher than the amount of scattered light, and 2-) the receiver cuton frequency is much higher than the aerosol cutoff frequency rendering most mechanisms of the shower curtain effect ineffective.
Strong experimental data supporting the theoretical relationship between linear and circular depolarizations for randomly oriented particles are presented. The analysis of the data leads to the first experimental validation of the theoretical representation of the scattering Mueller matrix as having indeed only one free parameter for randomly oriented particles, which is the depolarization parameter, d. Consequently, there is no added information on the nature of the aerosols when the four Stokes parameters are measured for randomly oriented aerosols, as opposed to measuring only the linear polarization or only the circular polarization related parameters. This conclusion has a direct impact on the analysis of the level of complexity of the systems that are required to analyze aerosols based on their depolarization signatures.
Cao et al.1 published a paper where differentiating bioaerosols (pollens) appeared feasible when linear depolarization
ratio signature at multiple wavelengths could be obtained. The measurements were performed at 4 wavelengths. The
bioaerosols were disseminated in a controlled environment and the discrimination analysis was based on Mahalanobis
distances. Poor discrimination was obtained for single wavelength measurement while acceptable and good
discrimination was reported for two and three wavelengths. This innovative work has raised the following question: to
which extent does the addition of circular polarization signature to the existing linear polarization increase the overall
discrimination capability? In order to answer that question, the measurements of Cao et al. were repeated for linear
and circular depolarization ratios.
We demonstrate experimentally that the linear and circular depolarization ratios are related to each other via a known
simple theoretical mathematical expression in the case of randomly oriented particles. Hence, by measuring one, you
obtain the other and consequently there is no additional information that is gained by doing measurements with the
two polarization states. This suggests that there is no need for full Mueller matrix measurement systems for detection
and discrimination of bioaerosols.
Ladar technology has long since established its advantages as a reliable method for automated Terrain Mapping. One still
remaining important problem of this methodology though happens at data processing time. Ladars generate huge
amounts of data referred to as 'point clouds'. The very first task in data processing consists of segmenting the terrain
image between ground and non-ground data points. The standard processing methods all rely on some slope analysis
technique. At the present moment, all these techniques still require interactive evaluation and manual editing of the
results.
In this work, Ladar polarization is used to discriminate between solid targets by using their polarization signatures. The
addition of this feature, over and above range and intensity, could greatly help in the process wherein ground and nonground
points are to be separated.
Linear and circular polarizations measurements were performed on different specimens in various conditions and at
various wavelengths. The results presented herein are a validation of the fact that typical solid targets show a response to
the Ladar sensor which conforms to the behavior predicted by the most recent polarimetric BDRF theories. Hence, their
polarization signature is expected to be repeatable. The results presented herein also show that, to the extent that more
than one wavelength is used, solid targets can be discriminated against each other by the use of their polarization
signatures.
Standoff discrimination of bioaerosols based on lidar measurements of depolarized backscattered light is herein studied. Measurements were performed at four wavelengths (355, 532, 1064, and 1570 nm) over 25 pollens and 2 dusts under controlled environment at a distance of 100 m. Linear polarization measurements were performed. It is shown that discrimination between pollens can be achieved using the linear polarization of at most three of the four wavelengths, and statistical discrimination based on Mahalanobis distance is obtained for most of the 27 cases studied.
Lidar bioaerosols discrimination based on depolarization signature is studied. The measurements were performed over
25 pollens and 2 dusts under controlled environment at a distance of 100 m, at wavelengths of 355 nm, 532 nm, 1064
nm and 1570 nm, and both linear and circular polarizations were used. It is found that discrimination of bioaerosols
using single wavelength linear depolarization ratios is difficult because most of them are quite alike. However, two or
more wavelengths measurements make it possible to discriminate different bioaerosols against others, especially when
a depolarization ratio cumulative distribution is available.
Measurements of the depolarization ratio of water droplets were performed to study the relationship between layer
integrated depolarization and layer integrated backscattered light for linear and circular polarization illumination. Since
those particles are spherical, the depolarization of the signal is attributed to multiple scattering effects. The experimental
data reported in this article support Hu relationship between the single scattering fraction As and the linear accumulated
depolarization ratio. For circular polarization, a modified Hu relationship is established and it is shown that the use of
the accumulated depolarization parameter instead of the accumulated depolarization ratio allows harmonization of the
linear and circular polarization measurements into a simple mathematical expression.
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