Propagation of millimetric radio waves through the clear atmosphere

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Differential Interferometry Techniques on L-Band Data Employed for the Monitoring of Surface Subsidence Due to Mining

Mining activities in South Africa changes the natural environment in several ways. Challenges for mining companies lie in the detection and monitoring of surface subsidence and there exists a need for a long term monitoring system. Field-based techniques for deformation measurement are labour intensive and time consuming and, consequently, the implementation of these techniques for long-term monitoring is not ideal. On the other hand, satellite remote sensing data provides a synoptic view of an area and the repeat image acquisition strategy implies that the long-term monitoring of surface deformation is a possibility. This paper investigates the use of L-band ALOS PALSAR data for the detection and monitoring of surface subsidence due to underground mining activities in the Witbank Coalfields. Surface subsidence was detected for a period of over 3 years between 2007/08/16 and 2010/10/09. Centimetre scale surface deformation was detected in the study area and is associated with areas of active mining. The systematic evolution of the surface deformation basins over time was recognised and is consistent with the advance of the working face of the mine during the same period. The results confirm that L-band synthetic aperture radar data through dInSAR techniques can be used for the long-term monitoring of surface subsidence associated with mining activities

Mixed-architecture process scheduling on tightly coupled reconfigurable computers

The design and implementation of a multitasking runtime system for mixed-architecture applications on a tightly coupled FPGA-CPU platform is presented. The runtime environment and the user applications assume an underlying machine that encompasses multiple computing architectures within a unified machine model. Using this model, a unified process scheduling mechanism was developed that enables concurrent execution of multiple mixed-architecture processes. Scheduling and allocation strategies, including blocking and preemption, were implemented and evaluated with respect to performance and fairness on a Xilinx Zynq platform using a mix of synthetic workloads.postprin

Multistatic Radar: System Requirements and Experimental Validation

Multistatic radar provides many advantages over conventional monostatic radar, such as enhanced information on target signatures and improvements in detection which are due to the multiple perspectives and differences in the properties of clutter. Furthermore, the fact that receive-only multistatic nodes are passive may be an advantage in military applications. In order to quantify potential performance benefits of these advantages a comprehensive understanding of target and clutter behaviour in multistatic scenarios is necessary. However, such information is currently limited because bistatic and multistatic measurements are difficult to make, their results depend on many variables such as multistatic geometry, frequency, polarization, and many others, and results from previous measurements are likely to be classified for military targets. Multistatic measurements of targets and clutter have been performed over the past few years by the NetRAD system developed at the University College London and the University of Cape Town. A new system, NeXtRAD, is now being developed in order to investigate some of the many aspects of multistatic radar. This paper discusses the results obtained with the previous system and the lessons learnt from its use. These points are then discussed in the context of the new radar, defining key important factors that have to be considered when developing a new multistatic radar system

Measurements and discrimination of drones and birds with a multi‐frequency multistatic radar system

This article presents the results of a series of measurements of multistatic radar signatures of small UAVs at L‐ and X‐bands. The system employed was the multistatic multiband radar system, NeXtRAD, consisting of one monostatic transmitter‐receiver and two bistatic receivers. NeXtRAD is capable of recording simultaneous bistatic and monostatic data with baselines and two‐way bistatic range of the order of a few kilometres. The paper presents an empirical analysis with range‐time plots and micro‐Doppler signatures of UAVs and birds of opportunity recorded at several hundred metres of distance. A quantitative analysis of the overall signal‐to‐noise ratio is presented along with a comparison between the power of the signal scattered from the drone body and blades. A simple study with empirically obtained features and four supervised‐learning classifiers for binary drone versus non‐drone separation is also presented. The results are encouraging with classification accuracy consistently above 90% using very simple features and classification algorithms

Measurements of the Multistatic X&L Band Radar Signatures of UAVS

This paper illustrates the results of a series of measurements of multistatic radar signatures of small UAVs at L and X band. The system employed was the multistatic multiband radar system, NeXtRAD, consisting of one monostatic transmitter-receiver and two bistatic receivers. Results demonstrate the capability of the system of recording bistatic data with baselines and two-way bistatic range of the order of few kilometres

Measurements of multistatic X&L band radar signatures of UAVs

This paper illustrates the results of a series of measurements of multistatic radar signatures of small UAVs at L and X band. The system employed was the multistatic multiband radar system, NeXtRAD, consisting of one monostatic transmitter-receiver and two bistatic receivers. Results demonstrate the capability of the system of recording bistatic data with baselines and two-way bistatic range of the order of few kilometres

Inverse synthetic aperture imaging using 140 kHz ultrasonic laboratory sonar

A sonar system operating at 40 kHz in air has been developed to allow the capture of acoustic data in a laboratory environment. The system can serve as a teaching tool for students in seismology, sonar and radar, as well as a useful tool for the development and testing of signal and image processing algorithms. The system can be used for monostatic or bistatic modes of imaging. Range compression is achieved by deconvolution filtering which compensates for the linear system effects of the transducers and other components. A deconvolution filter is generated via a calibration technique in which the system response is measured by pointing the transmitting transducer directly at the receiving transducer. Results are presented which demonstrate the capability of the system for range profiling and 2-D imaging, using the inverse synthetic aperture technique whereby the scene to be imaged is moved across the beam of the sensor. The focused image is obtained by synthetic aperture azimuth focusing / migration techniques. The range and azimuth resolutions achieved with system are discussed

First Measurements with NeXtRAD, a Polarimetric X/L Band Radar Network

NeXtRAD is a fully polarimetric, X/L Band radar network. It is a development of the older NetRAD system and builds on the experience gained with extensive deployments of NetRAD for sea clutter and target measurements. In this paper we will report on the first measurements with NeXtRAD, looking primarily at sea clutter and some targets, as well as early attempts at calibration using corner reflectors, and an assessment of the polarimetric response of the system. We also highlight innovations allowing for efficient data manipulation post measurement campaigns, as well as the plans for the coming years with this system

Parallel symbolic state-space exploration is difficult, but what is the alternative?

State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1) parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2) symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal