A compact lightweight multipurpose ground-penetrating radar for glaciological applications

We describe a compact lightweight impulse radar for radio-echo sounding of subsurface structures designed specifically for glaciological applications. The radar operates at frequencies between 10 and 75 MHz. Its main advantages are that it has a high signal-to-noise ratio and a corresponding wide dynamic range of 132 dB due mainly to its ability to perform real-time stacking (up to 4096 traces) as well as to the high transmitted power (peak voltage 2800 V). The maximum recording time window, 40 ?s at 100 MHz sampling frequency, results in possible radar returns from as deep as 3300 m. It is a versatile radar, suitable for different geophysical measurements (common-offset profiling, common midpoint, transillumination, etc.) and for different profiling set-ups, such as a snowmobile and sledge convoy or carried in a backpack and operated by a single person. Its low power consumption (6.6 W for the transmitter and 7.5 W for the receiver) allows the system to operate under battery power for mayor que7 hours with a total weight of menor que9 kg for all equipment, antennas and batteries

PASSIVE TIME SYNCHRONIZATION IN SENSOR NETWORKS USING OPPORTUNISTIC FM RADIO SIGNALS

ABSTRACT Time synchronization is a critical piece of infrastructure for any wireless sensor network. It is necessary for applications such as audio localization, beam-forming, velocity calculation, and duplicate event detection. All of which require the coordination of multiple nodes. Recent advances in low-cost, low-power wireless sensors have led to an increased interest in large-scale networks of small, wireless, low-power sensor nodes. Because of the more stringent power and cost requirements that this technology is driving, current time synchronization techniques must be updated to capitalize on these advances. One time synchronization method developed specifically for wireless sensor networks is Reference Broadcast Synchronization. In RBS, a reference broadcast is transmitted to sensor nodes that require synchronization. Be recording the time of arrival, nodes can then use those time stamps to synchronize with each other. This project aimed to make the RBS system even more robust, energy efficient, and cost effective by replacing the reference broadcast with an ambient RF signal (FM, TV, AM, or satellite signals) already prevalent in the environment. The purpose of this project was to demonstrate the viability of using Opportunistic RF synchronization by 1.) quantifying error, 2.) applying this synchronization method in a real world application, and 3.), implementing a wireless sensor network using Android smart phones as sensor nodes. Many of the objectives for the project were successfully completed. For convenience and economic reasons, an FM signal was chosen as the reference broadcast. FM Radio Synchronization error was then quantified using local FM Radio stations. The results of this experiment were very favorable. Using 5 second segments for correlation, total error was found to be 0.208±4.499μs. Using 3 second segments, average error was 2.33 ± 6.784μs. Using 400ms segments, synchronization error was calculated to be 4.76 ± 8.835μs. These results were comparable to sync errors of methods currently in widespread use. It was also shown that Opportunistic RF Synchronization could be used in real world applications as well. Again FM was the RF signal of choice. FM Radio Synchronization was tested in an Audio Localization experiment with favorable results. Implementation of an Android Wireless Sensor Network according to our specifications, however, could not be achieved. HTC EVO 4G’s were programmed to communicate through TCP / IP network connections, record audio with a microphone, and to record FM Radio streams from the EVO’s internal FM radio. Although recording these two sources separately as different data tracks was successful, simultaneous recording of these streams could not be accomplished (simultaneous recording is essential for Opportunistic RF Synchronization). Although the Android smart phone implementation was not a total success, this project still provided data that supported the practical use of Opportunistic RF Synchronization.AFRLNo embarg

A low-power opportunistic communication protocol for wearable applications

© 2015 IEEE.Recent trends in wearable applications demand flexible architectures being able to monitor people while they move in free-living environments. Current solutions use either store-download-offline processing or simple communication schemes with real-time streaming of sensor data. This limits the applicability of wearable applications to controlled environments (e.g, clinics, homes, or laboratories), because they need to maintain connectivity with the base station throughout the monitoring process. In this paper, we present the design and implementation of an opportunistic communication framework that simplifies the general use of wearable devices in free-living environments. It relies on a low-power data collection protocol that allows the end user to opportunistically, yet seamlessly manage the transmission of sensor data. We validate the feasibility of the framework by demonstrating its use for swimming, where the normal wireless communication is constantly interfered by the environment

Data Provenance and Management in Radio Astronomy: A Stream Computing Approach

New approaches for data provenance and data management (DPDM) are required for mega science projects like the Square Kilometer Array, characterized by extremely large data volume and intense data rates, therefore demanding innovative and highly efficient computational paradigms. In this context, we explore a stream-computing approach with the emphasis on the use of accelerators. In particular, we make use of a new generation of high performance stream-based parallelization middleware known as InfoSphere Streams. Its viability for managing and ensuring interoperability and integrity of signal processing data pipelines is demonstrated in radio astronomy. IBM InfoSphere Streams embraces the stream-computing paradigm. It is a shift from conventional data mining techniques (involving analysis of existing data from databases) towards real-time analytic processing. We discuss using InfoSphere Streams for effective DPDM in radio astronomy and propose a way in which InfoSphere Streams can be utilized for large antennae arrays. We present a case-study: the InfoSphere Streams implementation of an autocorrelating spectrometer, and using this example we discuss the advantages of the stream-computing approach and the utilization of hardware accelerators

Advanced observation and telemetry heart system utilizing wearable ECG device and a Cloud platform

Short lived chest pain episodes of post PCI patients represent the most common clinical scenario treated in the Accidents and Emergency Room. Continuous ECG monitoring could substantially diminish such hospital admissions and related ambulance calls. Delivering community based, easy-To-handle, easy to wear, real time electrocardiography systems is still a quest, despite the existence of electronic electrocardiography systems for several decades. The PATRIOT system serves this challenge via a 12-channel, easy to wear, easy to carry, mobile linked, miniaturized automatic ECG device and a Cloud platform. The system may deliver high quality electrocardiograms of a patient to medical personnel either on the spot or remotely both in a synchronous or asynchronous mode, enhancing autonomy, mobility, quality of life and safety of recently treated coronary artery disease patients

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin