Lidar receivers with exquisitely sensitive Geiger-mode detectors are able to detect surfaces even when the line of sight from the lidar sensor to the surface is highly occluded by intervening forest canopy. Additionally, repeated scanning of a region of interest from a diversity of perspectives increases the likelihood of imaging any given surface through at least one substantially unoccluded line of sight. Together, these techniques allow airborne lidar collections to be tailored to achieve comprehensive human activity layer (HAL) data collection, even in areas with dense foliage. We present a study of the performance of a 3DEO lidar for foliage poke-through applications, exploiting both its Geiger-mode sensitivity and agile geo-referenced scanning system. We present two methods for estimating the utility of the resulting 3D point clouds in the HAL, near the ground, based on the spatial statistics of the point clouds. We apply those methods to airborne Geiger-mode lidar data of deciduous forests in Massachusetts and conifers in the US Pacific Northwest. We quantify the completeness of the point clouds as a function of the collection parameters. We then use this analysis to estimate the ideal collection parameters for a Geiger-mode lidar with georeferenced scanning to yield a high-utility data product.
We have developed a Geiger-mode lidar system for detecting individual birds in large flocks and tracking them using a real-time processing system. We present initial results of field tests conducted in North Dakota observing large flocks of red-wing black birds and their predators. We analyze the signals and tracks arising from the birds and from a small UAS in the scene. We also present data from testing in Lawrence, Massachusetts observing American Crows in which we tested a real-time processing system. The exquisite sensitivity and rapid measurement rates achievable with Geiger-mode lidars enable rapid surveillance of airspaces for the detection of small targets (cross section of 100 cm2 at 20 percent reflectivity) at operationally relevant standoff (400 - 800 m) with high revisit rates (5 - 10 Hz). The objective of this demonstration was the tracking of over 1000 birds in a flock occupying a volume of interest of (100 m)3 at a standoff of 400 m. We will present initial results from field campaigns observing red-wing blackbirds, predators and American crows.
Photon-sensitive lidar receivers enable range measurements at high probability of detection and low false alarm rate using only 5 - 10 detected photons on average per range measurement. This much-reduced link requirement, compared to photodiodes operating in linear mode, holds the promise of much-reduced system volume, mass, and power consumption, while simultaneously enabling longer standoff and higher measurement rates. We present a commercially-available, Geiger-mode lidar system, called Zion, optimized for rapid collection of dense 3D point clouds using small, economical aircraft. The system mass is under 120 kg and it consumes under 1 kW. Zion has operated at ranges between 800 m and 8,000 m. The area collection rate for data products with density of 100 points per square meter exceeds 300 km2/hr at an aircraft altitude of 1,400 m. The maximum usable measurement rate exceeds 10 million points per second. A significant capability of Zion is the agile geo-referenced scanning system, which can point and scan anywhere within a 40 × 40 degree field of regard. Collection efficiency is optimized by scanning only the desired geographic region of interest (e.g. meandering roads and utility corridors) and even in spite of non-ideal aircraft flight path and attitude. The agile, georeferenced scanning allows the flexibility to maximize oblique imaging of structures or to penetrate dense foliage. The collected points are spread evenly across the imaged area, which reduces image artifacts and simplifies processing. This system has flown over 50 flights, and is currently operational.
Aerial lidar systems tend to have narrow instantaneous fields of view, with imagers ranging from a single pixel to many tens of thousands of pixels. To collect data over a large area, the narrow lidar field of view (FoV) must be scanned. We present a unique method of scanning a lidar FoV that provides significant flexibility and allows uniform ground coverage, concentrating the system capability only in areas of interest. This method uses a queue of convex polygons, specified in world coordinates. Pre-collection planning tools establish the polygon layout. In flight, the lidar system adaptively collects those polygons that are inside the sensor field of regard, rapidly switching among the polygons as the aircraft flies. This scanning method enables the lidar to accomplish repeated collections of a single target or collections that cover a long straight or meandering path. It also enables collection of corridors with irregular widths, such as power line corridors with bulges at municipal power sub-stations or rail or roadway intersections. In the case of mixed scene types, the system can concentrate more collection time on foliated regions relative to unfoliated regions. Angular diversity can be achieved by sequentially revisiting a single target polygon. Live target tasking is accomplished by adding new targets to the target queue without stopping an ongoing collection. We present scanning simulations and example lidar data collected in flight with this scanning strategy and show some examples of sampling uniformity under the finite bandwidth and acceleration of a real scanning system.
The image formation process for airborne lidar systems utilizes physical sensor models
in order to create three-dimensional imagery
from range, scanning, position and attitude sensor measurements.
To estimate surface locations from data collected with Geiger-mode lidar systems,
typically range measurements are combined from many laser pulses,
from many camera pixels, over multiple viewing geometries and multiple collection times.
Sharp image formation requires well-calibrated camera and pointing models.
The calibration method presented here utilizes aerial data collections
spanning the full sensor field of regard to iteratively refine the system model parameters
while minimizing relative imagery misplacement.
Step one of the calibration adjusts parameters that only affect image quality
and evaluates image sharpness using, for example, a Sobel sharpness filter.
Step two adjusts parameters affecting image placement.
This calibration method utilizes the vendor-supplied transform code
inside the parameter optimization algorithm
and is therefore independent from the lidar configuration and the physical sensor model.
Utilizing the vendor-supplied transform ensures that the resulting calibration parameters
are interpreted correctly.
To reduce computational burden in step two, the input data from thousands of laser pulses
is condensed into a single effective pulse that is passed through the transform step.
This method has been used to calibrate four different Geiger-mode lidar systems
and has enabled sharp imagery over the full field of regard
prior to incorporating ground control points or performing registration with adjacent imagery.
We present representative results for the Cuchillo lidar system
and discuss execution time requirements and performance limitations.
Three lidar receiver technologies using the total laser energy required to perform a set of imaging tasks are compared. The tasks are combinations of two collection types (3-D mapping from near and far), two scene types (foliated and unobscured), and three types of data products (geometry only, geometry plus 3-bit intensity, and geometry plus 6-bit intensity). The receiver technologies are based on Geiger mode avalanche photodiodes (GMAPD), linear mode avalanche photodiodes (LMAPD), and optical time-of-flight lidar, which combine rapid polarization rotation of the image and dual low-bandwidth cameras to generate a 3-D image. We choose scenarios to highlight the strengths and weaknesses of various lidars. We consider HgCdTe and InGaAs variations of LMAPD cameras. The InGaAs GMAPD and the HgCdTe LMAPD cameras required the least energy to 3-D map both scenarios for bare earth, with the GMAPD taking slightly less energy. We comment on the strengths and weaknesses of each receiver technology. Six bits of intensity gray levels requires substantial energy using all camera modalities.
In response to the 2010 Haiti earthquake, the ALIRT ladar system was tasked with collecting surveys to
support disaster relief efforts. Standard methodologies to classify the ladar data as ground, vegetation, or
man-made features failed to produce an accurate representation of the underlying terrain surface. The majority
of these methods rely primarily on gradient- based operations that often perform well for areas with low
topographic relief, but often fail in areas of high topographic relief or dense urban environments. An
alternative approach based on a adaptive lower envelope follower (ALEF) with an adaptive gradient operation
for accommodating local slope and roughness was investigated for recovering the ground surface from the
ladar data. This technique was successful for classifying terrain in the urban and rural areas of Haiti over
which the ALIRT data had been acquired.
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