Technological Perspectives of Countering UAV Swarms

Conventional AD systems have been found less effective for countering UAVs and loitering munitions. Thishas necessitated the development of counter-UAV systems with different functionalities. A cluster of armed UAVsas swarm formations has further rendered the conventional AD systems far from effective, emphasizing the need to consider countering swarms as the most crucial element in new-generation aerial threat mitigation strategies. In this paper, the capabilities of UAV swarms and vital military assets exposed to such attacks are identified. To protect the vital assets from aerial swarm threats, ideal system characteristics of a counter-UAV (C-UAV) swarm system to overcome the challenges are discussed. Currently available acquisition & engagement technology is analyzed and the application of these systems to counter swarm applications is brought out. New requirements are discussed and a conceptual design of a layered system is derived which can handle a large spectrum of aerial threats including a swarm of UAVs. This system is expected to have a higher rate of engagement and can be designed with low-cost network-integrated systems

Collaborative signal and information processing for target detection with heterogeneous sensor networks

In this paper, an approach for target detection and acquisition with heterogeneous sensor networks through strategic resource allocation and coordination is presented. Based on sensor management and collaborative signal and information processing, low-capacity low-cost sensors are strategically deployed to guide and cue scarce high performance sensors in the network to improve the data quality, with which the mission is eventually completed more efficiently with lower cost. We focus on the problem of designing such a network system in which issues of resource selection and allocation, system behaviour and capacity, target behaviour and patterns, the environment, and multiple constraints such as the cost must be addressed simultaneously. Simulation results offer significant insight into sensor selection and network operation, and demonstrate the great benefits introduced by guided search in an application of hunting down and capturing hostile vehicles on the battlefield

Chip-based photonic radar for high-resolution imaging

Radar is the only sensor that can realize target imaging at all time and all weather, which would be a key technical enabler for future intelligent society. Poor resolution and large size are two critical issues for radars to gain ground in civil applications. Conventional electronic radars are difficult to address both issues especially in the relatively low-frequency band. In this work, we propose and experimentally demonstrate, for the first time to the best of our knowledge, a chip-based photonic radar based on silicon photonic platform, which can implement high resolution imaging with very small footprint. Both the wideband signal generator and the de-chirp receiver are integrated on the chip. A broadband photonic imaging radar occupying the full Ku band is experimentally established. A high precision range measurement with a resolution of 2.7 cm and an error of less than 2.75 mm is obtained. Inverse synthetic aperture (ISAR) imaging of multiple targets with complex profiles are also implemented.Comment: 4 pages, 6figure

Laser Based Altimetry for Unmanned Aerial Vehicle Hovering Over a Snow Surface

A microwave radar for non-invasive snow stratigraphy measurements has been developed. Results were promising, but it failed to detect light powder snow in the air-snowpack interface. The aim of this thesis is to find and verify a system for estimating altitude on centimeter scale over a snow surface, independent of snow conditions. Also, relative pitch and roll angle estimation between the UAV and local surface should be resolved, to help directing the radar beam perpendicularly to the surface. After a variety of technical solutions were examined, we propose a system of three time-of-flight near-infrared altimeters pointing at different directions towards the surface. Experimental results showed RMS error of 1.39 cm for range estimation averaged over the most common snow types, and 2.81 cm for wet snow, which was the least reflective medium. An experiment conducted for an array of two altimeters scanning over a snow surface, showed that the local, relative surface tilt was found to be accurate within ±2° given that it was sufficiently planar. Further, the altitude RMS error was estimated to 1.57 cm. We conclude that the chosen altimeter was within the requirements, and that an array of three altimeters would give acceptable relative tilt estimation in to planes on the snow surface. The system should be subject to flight testing and implemented on UAV platform such that it can aid the microwave radar system during snow scanning

RADAR Based Collision Avoidance for Unmanned Aircraft Systems

Unmanned Aircraft Systems (UAS) have become increasingly prevalent and will represent an increasing percentage of all aviation. These unmanned aircraft are available in a wide range of sizes and capabilities and can be used for a multitude of civilian and military applications. However, as the number of UAS increases so does the risk of mid-air collisions involving unmanned aircraft. This dissertation aims present one possible solution for addressing the mid-air collision problem in addition to increasing the levels of autonomy of UAS beyond waypoint navigation to include preemptive sensor-based collision avoidance. The presented research goes beyond the current state of the art by demonstrating the feasibility and providing an example of a scalable, self-contained, RADAR-based, collision avoidance system. The technology described herein can be made suitable for use on a miniature (Maximum Takeoff Weight \u3c 10kg) UAS platform. This is of paramount importance as the miniature UAS field has the lowest barriers to entry (acquisition and operating costs) and consequently represents the most rapidly increasing class of UAS

Detecting Invasive Insects with Unmanned Aerial Vehicles

A key aspect to controlling and reducing the effects invasive insect species have on agriculture is to obtain knowledge about the migration patterns of these species. Current state-of-the-art methods of studying these migration patterns involve a mark-release-recapture technique, in which insects are released after being marked and researchers attempt to recapture them later. However, this approach involves a human researcher manually searching for these insects in large fields and results in very low recapture rates. In this paper, we propose an automated system for detecting released insects using an unmanned aerial vehicle. This system utilizes ultraviolet lighting technology, digital cameras, and lightweight computer vision algorithms to more quickly and accurately detect insects compared to the current state of the art. The efficiency and accuracy that this system provides will allow for a more comprehensive understanding of invasive insect species migration patterns. Our experimental results demonstrate that our system can detect real target insects in field conditions with high precision and recall rates.Comment: IEEE ICRA 2019. 7 page

ENABLING WARFARE AT THE SPEED OF LIGHT: A COMPARATIVE ANALYSIS OF MULTI-MISSION HIGH ENERGY LASER RADARS

This capstone report provides a cost effectiveness analysis of various radar systems capable of guiding the Multi-Mission High Energy Laser (MMHEL) from a Stryker platform. The Army's Rapid Capability and Critical Technologies Office (RCCTO) is developing the MMHEL to provide a Mobile Short-Range Air Defense (MSHORAD) capability to maneuver units. The MMHEL requires a radar to cue the fire control system for target engagement. Past efforts to employ high-energy lasers have relied on large, stationary radars for target acquisition. The reliance on such radars limits a unit's ability to maneuver and results in the laser being employed primarily from a defensive posture. To maximize maneuverability and enable the offensive employment of the MMHEL, the U.S. Army needs an on-platform radar that is compact and inexpensive enough to equip multiple Strykers within a Stryker Brigade Combat Team with the capability to engage targets from a mobile platform. The RCCTO is currently tasked with accelerating efforts to fill this need. The intent of this report is to assist the RCCTO in these efforts by generating a list of viable radar alternatives and conducting a cost effectiveness analysis to produce a recommendation of the most optimal solution. The results indicate that RADA's aCHR radar presents the best value in terms of cost and benefit to the warfighter.http://archive.org/details/enablingwarfarea1094564109Captain, United States ArmyCaptain, United States ArmyMajor, United States ArmyCaptain, United States ArmyCaptain, United States ArmyApproved for public release; distribution is unlimited

Vegetation Dynamics in Ecuador

Global forest cover has suffered a dramatic reduction during recent decades, especially in tropical regions, which is mainly due to human activities caused by enhanced population pressures. Nevertheless, forest ecosystems, especially tropical forests, play an important role in the carbon cycle functioning as carbon stocks and sinks, which is why conservation strategies are of utmost importance respective to ongoing global warming. In South America the highest deforestation rates are observed in Ecuador, but an operational surveillance system for continuous forest monitoring, along with the determination of deforestation rates and the estimation of actual carbon socks is still missing. Therefore, the present investigation provides a functional tool based on remote sensing data to monitor forest stands at local, regional and national scales. To evaluate forest cover and deforestation rates at country level satellite data was used, whereas LiDAR data was utilized to accurately estimate the Above Ground Biomass (AGB; carbon stocks) at catchment level. Furthermore, to provide a cost-effective tool for continuous forest monitoring of the most vulnerable parts, an Unmanned Aerial Vehicle (UAV) was deployed and equipped with various sensors (RBG and multispectral camera). The results showed that in Ecuador total forest cover was reduced by about 24% during the last three decades. Moreover, deforestation rates have increased with the beginning of the new century, especially in the Andean Highland and the Amazon Basin, due to enhanced population pressures and the government supported oil and mining industries, besides illegal timber extractions. The AGB stock estimations at catchment level indicated that most of the carbon is stored in natural ecosystems (forest and páramo; AGB ~98%), whereas areas affected by anthropogenic land use changes (mostly pastureland) lost nearly all their storage capacities (AGB ~2%). Furthermore, the LiDAR data permitted the detection of the forest structure, and therefore the identification of the most vulnerable parts. To monitor these areas, it could be shown that UAVs are useful, particularly when equipped with an RGB camera (AGB correlation: R² > 0.9), because multispectral images suffer saturation of the spectral bands over dense natural forest stands, which results in high overestimations. In summary, the developed operational surveillance systems respective to forest cover at different spatial scales can be implemented in Ecuador to promote conservation/ restoration strategies and to reduce the high deforestation rates. This may also mitigate future greenhouse gas emissions and guarantee functional ecosystem services for local and regional populations