Leveraging the computer chip and networking technologies that have benefited so much from Moore's law increases in capabilities and cost reductions, the National Science Foundation Engineering Research Center (ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) is transforming the way we do atmospheric sensing.  In contrast to today's national scale atmospheric sensing radar systems which are based on small numbers of very large, very high-power, long-range radars that operate essentially as isolated units, CASA is engineering a technology based on a tightly integrated, densely packed network of small size, low power, short-range, solid-state radars with overlapping coverage for coordinated scanning and data fusion.  Instead of radars with 10 m antenna, 100's of kW transmit power, and 100's of km spacing, CASA radars would be 1 m in size, solid state panels with transmit powers in the 10's of W and spacing of 10's of km.  The close spacing of a CASA network "defeats" the blockage due to the curvature of the earth, which limits today's widely spaced radar from viewing weather hazards, aircraft, smoke, and chemical contaminants at the earth's surface.  In addition, the diversity of multiple views of each location in the network greatly improves detection, resolution, and accuracy of the collected measurements in support of multiple end-users and applications.  Field tests being conducted by the CASA ERC are demonstrating dramatic improvements over the current state-of-the-art long-range paradigm.  One such improvement is the ability to support the atmospheric boundary layer sensing needs of a diverse population of end-users ranging from operational forecasters, to emergency managers, to researchers [McLaughlin 09].

Due to their very large size and very high radiated power, long-range radars require dedicated land, towers, and other support infrastructure.  Since the radars are relatively few in number, site selection is generally dictated by population density and proximity to other infrastructure such as airports [Leone 89].  As a result, coverage is highly non-uniform over the network, and only works well when situated close to the radars due to earth curvature, terrain blockage, and the loss of resolution and power density related to beam spreading.  The WSR-88D NEXRAD system in the U.S., which represents the state-of-the-art in the traditional long-range radar paradigm, provides a weather sensing capability that is the best in the world, with unquestioned socioeconomic value.  The deficiencies that the NEXRAD system does have, such as insufficient low-level coverage, poor coverage in rough terrain, and insufficient resolution far from the radar, are due precisely to the wide-spacing and non-uniform deployment of the radars [NRC 02].

The deficiencies of long-range radar systems, particularly their inability to see down low, can only be overcome through a more dense deployment of radars.  This is illustrated in Figure 1, which plots the relationship between the denseness of a radar network and its low-altitude coverage.  The vertical bars at 345 km and 230 km are the average spacing between the radars in the NEXRAD system in the western and eastern U.S., respectively.  This non-uniform density leaves the west with poorer coverage than the east, but even in the east, coverage in the lowest 100's of meters above ground level is very limited.  CASA's 30 km radar spacing is the vertical bar on the left of Figure 1.  This spacing represents a series of tradeoffs between low-altitude coverage, radar cost drivers (operating frequency, transmit power, antenna size, solid-state manufacturing technology), and system performance (sensitivity, resolution, update time) [McLaughlin 09].  The spacing also represents an increase in density over NEXRAD of about 50:1, i.e., every NEXRAD would be replaced by ~50 CASA-type radars; a replacement of ~150 radars by ~10,000.

Figure 1.  Percent coverage (solid lines) and number of radars needed for CONUS coverage (dashed line) vs. radar spacing.

The need for low cost radars and the need to site ~10,000 radars requires entirely different siting considerations than those for large radars.  The close spacing between CASA radars required for low-altitude coverage and high resolution would require that many be located directly in population centers.  The low radiated power and small flat panel form factor facilitates this by eliminating radiation hazard and allowing the radars to be mounted on existing infrastructure elements such as the sides of buildings and cell towers.  The need to keep the radars as low cost as possible requires that the radars work together to "amplify" their individual capabilities.  The topological arrangement, by influencing the ability of the radars to work together, will directly determine if and how their beams will interact to collaborate and adapt to changing user needs and atmospheric conditions.   The curve in Figure 1 was presented in [McLaughlin 09] but with only a cursory geometric and topological basis.  The first goal of this paper is to present that mathematical basis for two competing topologies; radars placed in a topology of equilateral triangles and radars placed in a rectangular grid topology.  The second goal is to compare the performance implications of these two topologies by comparing their "network advantages" in terms of low-altitude coverage, resolution, sensitivity, and velocity vector retrieval capabilities afforded by multiple simultaneous views of each point in the network.  The third goal is to compare the implications of the two topologies as they relate to the radar technology used.  In particular, full 360 degree azimuth coverage would require multiple phased array radar panels.  In addition, while single-polarization is generally sufficient for the point target applications that phased-array radars are currently most commonly used for, dual-polarization has proven invaluable for weather sensing applications.  Since the beam of a phased array radar degrades in both its width and dual-polarization purity with the amount by which the beam is steered off boresight, an analysis will address relationships between topology, the number of panels at a radar site, and the impact of this beam degradation on network level performance.