Leveraging Backscatter for Ultra-low Power Wireless Sensing Systems

The past few years have seen a dramatic growth in wireless sensing systems, with millions of wirelessly connected sensors becoming first-class citizens of the Internet. The number of wireless sensing devices is expected to surpass 6.75 billion by 2017, more than the world\u27s population as well as the combined market of smartphones, tablets, and PCs. However, its growth faces two pressing challenges: battery energy density and wireless radio power consumption. Battery energy density looms as a fundamental limiting factor due to slow improvements over the past several decades (3x over 22 years). Wireless radio power consumption is another key challenge because high-speed wireless communication is often far more expensive energy-wise than computation, storage and sensing. To make matters worse, wireless sensing devices are generating an increasing amount of data. These challenges raise a fundamental question --- how should we power and communicate with wireless sensing devices. More specifically, instead of using batteries, can we leverage other energy sources to reduce, if not eliminate, the dependence on batteries? Similarly, instead of optimizing existing wireless radios, can we fundamentally change how radios transmit wireless signals to achieve lower power consumption? A promising technique to address these questions is backscatter --- a primitive that enables RF energy harvesting and ultra-low-power wireless communication. Backscatter has the potential to reduce dependence on batteries because it can obtain energy by rectifying the wireless signals transmitted by a backscatter reader. Backscatter can also work by reflecting existing wireless signals (WiFi, BLE) when these are available nearby. Because signal reflection only consumes uWs of power, backscatter can enable ultra-low-power wireless communication. However, the use of backscatter for communicating with wireless sensing devices presents several challenges. First, decreasing RF power across distance limits the operational range of micro-powered backscatter devices. This raises the question of how to maintain a communication link with a backscatter device despite tiny amount of harvested power. Second, even though the backscatter RF front-end is extremely power-efficient, the computational and sensing overhead on backscatter sensors limit its ability to operate with a few micro-Watts of power. Such overhead is a negligible factor of overall power consumption for platforms where radio power consumption is high (e.g. WiFi or Bluetooth based devices). However, it becomes the bottleneck for backscatter based platforms. Third, backscatter readers are not currently deployed in existing indoor environments to provide a continuous carrier for carrying backscattered information. As a result, backscatter deployment is not yet widespread. This thesis addresses these challenges by making the following contributions. First, we design a network stack that enables continuous operation despite decreasing harvested power across distance by employing an OS abstraction --- task fragmentation. We show that such a network stack enables packet transfer even when the whole system is powered by a 3cmx3cm solar panel under natural indoor light condition. Second, we design a hardware architecture that minimizes the computational overhead of backscatter to enable over 1Mbps backscatter transmission while consuming less than 100uWs of power, a two order of magnitude improvement over the state-of-the-art. Finally, we design a system that can leverage both ambient WiFi and BLE signals for backscatter. Our empirical evaluation shows that we can backscatter 500bps data on top of a WiFi stream and 50kbps data on top of a Bluetooth stream when the backscatter device is 3m away from the commercial WiFi and Bluetooth receivers

Comparison of sea-ice freeboard distributions from aircraft data and cryosat-2

The only remote sensing technique capable of obtain- ing sea-ice thickness on basin-scale are satellite altime- ter missions, such as the 2010 launched CryoSat-2. It is equipped with a Ku-Band radar altimeter, which mea- sures the height of the ice surface above the sea level. This method requires highly accurate range measure- ments. During the CryoSat Validation Experiment (Cry- oVEx) 2011 in the Lincoln Sea, Cryosat-2 underpasses were accomplished with two aircraft, which carried an airborne laser-scanner, a radar altimeter and an electro- magnetic induction device for direct sea-ice thickness re- trieval. Both aircraft flew in close formation at the same time of a CryoSat-2 overpass. This is a study about the comparison of the sea-ice freeboard and thickness dis- tribution of airborne validation and CryoSat-2 measure- ments within the multi-year sea-ice region of the Lincoln Sea in spring, with respect to the penetration of the Ku- Band signal into the snow

Characterising Spatial and Temporal Ionospheric Variability with a Network of Oblique Angle-of-arrival and Doppler Ionosondes

Ionospheric variability exists on a broad range of scales, and routinely impacts skywave propagation modes of high frequency radio waves, to the detriment of radar and communication systems. In order to better understand the electron density structures associated with such variability at mid-latitudes, a network of oblique angle-of-arrival (AoA) and Doppler ionosondes were installed in central and northern Australia as part of the ELOISE campaign in 2015. This thesis analyses observations from the ELOISE AoA ionosondes, with a focus on characterising the influence of medium- to large- scale gradients and signatures of travelling ionospheric disturbances (TIDs). Following an overview of the experiment, the design and calibration of the new ionosonde system is described. With multi-channel receivers connected to each element of two twin-arm arrays, a total of eleven AoA paths of between 900 and 2700 km were collected, including nine with interleaved Doppler measurements using a special channel scattering function (CSF) capability. On-board signal processing was developed to perform real-time clear channel evaluation and CSF scheduling, and generate the AoA ionograms and delay-Doppler images with fitted electron density profiles. In further offline analysis, peak detection and mode classification was carried out, to support reflection point mapping and tilt estimation. Significant testing and validation of the new ionosonde before and after the experiment revealed AoA uncertainties on the scale of 0.2–0.5° in bearing and 0.4–0.9° in elevation. Having identified a low-elevation bias, models of tropospheric refraction and antenna mutual coupling effects were considered as possible correction strategies, but ultimately an empirical approach based on aggregated ionospheric returns was implemented. Small-scale (intra-dwell) ionospheric variability also has the potential to compromise results, through unresolved multi-mode mixing, and this has been investigated using a combination of spatial and temporal variability metrics derived from the CSF data. The analysis of large quantities of F2 peak data shows persistent diurnal patterns in the oblique AoA observables that are also well-captured by a conventional data-assimilative ionospheric model, even without the benefit of AoA and Doppler inputs. Furthermore, Doppler measurements are reproduced remarkably well using just the midpoint fitted profiles. A statistical study has quantified the level of consistency between observations and model, to provide greater confidence in the results. Many of the geophysical features can be interpreted as ionospheric gradients, as evident in the tilt estimates, and horizontally moving structures such as TIDs, using a form of Doppler-based drift analysis. While signatures of TIDs vary considerably, two simple wave-like perturbation models have been evaluated to help classify quasi-periodic behaviour in the AoA observations, as well as understand the directional filtering effect imposed by the path geometry. In some cases, a set of TID parameters can be determined by eye, but in others automatic parameter inversion techniques may be more viable. Two such techniques were implemented but results using both real and synthetic data demonstrated some significant limitations. Finally, attempts to relate TID signatures across multiple paths shows promise, but there still appears to be a strong dependence on path geometry that is difficult to eliminate.Thesis (Ph.D.) -- University of Adelaide, School of Physical Sciences, 202

Cooperative Navigation for Low-bandwidth Mobile Acoustic Networks.

This thesis reports on the design and validation of estimation and planning algorithms for underwater vehicle cooperative localization. While attitude and depth are easily instrumented with bounded-error, autonomous underwater vehicles (AUVs) have no internal sensor that directly observes XY position. The global positioning system (GPS) and other radio-based navigation techniques are not available because of the strong attenuation of electromagnetic signals in seawater. The navigation algorithms presented herein fuse local body-frame rate and attitude measurements with range observations between vehicles within a decentralized architecture. The acoustic communication channel is both unreliable and low bandwidth, precluding many state-of-the-art terrestrial cooperative navigation algorithms. We exploit the underlying structure of a post-process centralized estimator in order to derive two real-time decentralized estimation frameworks. First, the origin state method enables a client vehicle to exactly reproduce the corresponding centralized estimate within a server-to-client vehicle network. Second, a graph-based navigation framework produces an approximate reconstruction of the centralized estimate onboard each vehicle. Finally, we present a method to plan a locally optimal server path to localize a client vehicle along a desired nominal trajectory. The planning algorithm introduces a probabilistic channel model into prior Gaussian belief space planning frameworks. In summary, cooperative localization reduces XY position error growth within underwater vehicle networks. Moreover, these methods remove the reliance on static beacon networks, which do not scale to large vehicle networks and limit the range of operations. Each proposed localization algorithm was validated in full-scale AUV field trials. The planning framework was evaluated through numerical simulation.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113428/1/jmwalls_1.pd

Program Annual Technology Report: Physics of the Cosmos Program Office

From ancient times, humans have looked up at the night sky and wondered: Are we alone? How did the universe come to be? How does the universe work? PCOS focuses on that last question. Scientists investigating this broad theme use the universe as their laboratory, investigating its fundamental laws and properties. They test Einsteins General Theory of Relativity to see if our current understanding of space-time is borne out by observations. They examine the behavior of the most extreme environments supermassive black holes, active galactic nuclei, and others and the farthest reaches of the universe, to expand our understanding. With instruments sensitive across the spectrum, from radio, through infrared (IR), visible light, ultraviolet (UV), to X rays and gamma rays, as well as gravitational waves (GWs), they peer across billions of light-years, observing echoes of events that occurred instants after the Big Bang. Last year, the LISA Pathfinder (LPF) mission exceeded expectations in proving the maturity of technologies needed for the Laser Interferometer Space Antenna (LISA) mission, and the Laser Interferometer Gravitational-Wave Observatory (LIGO) recorded the first direct measurements of long-theorized GWs. Another surprising recent discovery is that the universe is expanding at an ever-accelerating rate, the first hint of so-called dark energy, estimated to account for 75% of mass-energy in the universe. Dark matter, so called because we can only observe its effects on regular matter, is thought to account for another20%, leaving only 5% for regular matter and energy. Scientists now also search for special polarization in the cosmic microwave background to support the notion that in the split-second after the Big Bang, the universe inflated faster than the speed of light! The most exciting aspect of this grand enterprise today is the extraordinary rate at which we can harness technologies to enable these key discoveries