DARIS, a fleet of passive formation flying small satellites for low frequency radio astronomy

DARIS (Distributed Aperture Array for Radio Astronomy In Space) is a mission to conduct radio astronomy in the low frequency region from 1-10MHz. This region has not yet been explored, as the Earth's ionosphere is opaque to those frequencies, and so a space based observatory is the only solution. DARIS will undertake an extragalactic survey of the low frequency sky, and can also detect some transient radio events such as solar or planetary bursts. To achieve these scientific objectives, DARIS comprises a space-based array, forming a very large effective aperture, as required for such a long wavelength survey. Each station in the array (each required to be a small satellite to ensure several nodes can be flown) carries three orthogonal dipole antennas, each 5m in length. The more station nodes in the array, the more sensitive the antenna. The entire fleet remains within a 100km diameter cloud. \ud A very large data volume is generated by each node, as the antennas have to capture all radio signals, after which the data can be correlated to find the astronomical signal in the noise. As the astronomical signals also have a noise-like nature, no compression is possible on the data captured by the nodes. The data volume is too high to transfer directly to Earth, and will need to be correlated in space. Distributed correlation between the nodes is technically challenging, and therefore a mothership acts as the central correlator and then downlinks the correlated data (lower volume) to Earth. \u

DARIS : a low-frequency distributed aperture array for radio astronomy in space

The frequency band below 30 MHz is one of the last unexplored bands in radio astronomy. This band is well suited for studying the early cosmos at high hydrogen redshifts, the so-called dark ages, extragalactic surveys, (extra) solar planetary bursts, and high energy particle physics. In addition, space research such as space weather tomography, are also areas of scientific interest. \ud \ud Due to ionospheric scintillation (below 30MHz) and its opaqueness (below 15MHz), earth-bound radio astronomy observations in these bands are either severely limited in sensitivity and spatial resolution or entirely impossible. A radio telescope in space obviously would not be hampered by the Earth's ionosphere. In the past, several (limited) studies have been conducted to explore possibilities for such an array in space. These studies considered aperture synthesis arrays in space, at the back-side of the Moon, or a satellite constellation operating in a coherent mode. \u

Space-based Aperture Array For Ultra-Long Wavelength Radio Astronomy

The past decade has seen the rise of various radio astronomy arrays, particularly for low-frequency observations below 100MHz. These developments have been primarily driven by interesting and fundamental scientific questions, such as studying the dark ages and epoch of re-ionization, by detecting the highly red-shifted 21cm line emission. However, Earth-based radio astronomy below frequencies of 30MHz is severely restricted due to man-made interference, ionospheric distortion and almost complete non-transparency of the ionosphere below 10MHz. Therefore, this narrow spectral band remains possibly the last unexplored frequency range in radio astronomy. A straightforward solution to study the universe at these frequencies is to deploy a space-based antenna array far away from Earths' ionosphere. Various studies in the past were principally limited by technology and computing resources, however current processing and communication trends indicate otherwise. We briefly present the achievable science cases, and discuss the system design for selected scenarios, such as extra-galactic surveys. An extensive discussion is presented on various sub-systems of the potential satellite array, such as radio astronomical antenna design, the on-board signal processing, communication architectures and joint space-time estimation of the satellite network. In light of a scalable array and to avert single point of failure, we propose both centralized and distributed solutions for the ULW space-based array. We highlight the benefits of various deployment locations and summarize the technological challenges for future space-based radio arrays.Comment: Submitte

Unsupervised Heart-rate Estimation in Wearables With Liquid States and A Probabilistic Readout

Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine intelligent approach for heart-rate estimation from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach lies in (1) encoding spatio-temporal properties of ECG signals directly into spike train and using this to excite recurrently connected spiking neurons in a Liquid State Machine computation model; (2) a novel learning algorithm; and (3) an intelligently designed unsupervised readout based on Fuzzy c-Means clustering of spike responses from a subset of neurons (Liquid states), selected using particle swarm optimization. Our approach differs from existing works by learning directly from ECG signals (allowing personalization), without requiring costly data annotations. Additionally, our approach can be easily implemented on state-of-the-art spiking-based neuromorphic systems, offering high accuracy, yet significantly low energy footprint, leading to an extended battery life of wearable devices. We validated our approach with CARLsim, a GPU accelerated spiking neural network simulator modeling Izhikevich spiking neurons with Spike Timing Dependent Plasticity (STDP) and homeostatic scaling. A range of subjects are considered from in-house clinical trials and public ECG databases. Results show high accuracy and low energy footprint in heart-rate estimation across subjects with and without cardiac irregularities, signifying the strong potential of this approach to be integrated in future wearable devices.Comment: 51 pages, 12 figures, 6 tables, 95 references. Under submission at Elsevier Neural Network

A review of urban air pollution monitoring and exposure assessment methods

The impact of urban air pollution on the environments and human health has drawn increasing concerns from researchers, policymakers and citizens. To reduce the negative health impact, it is of great importance to measure the air pollution at high spatial resolution in a timely manner. Traditionally, air pollution is measured using dedicated instruments at fixed monitoring stations, which are placed sparsely in urban areas. With the development of low-cost micro-scale sensing technology in the last decade, portable sensing devices installed on mobile campaigns have been increasingly used for air pollution monitoring, especially for traffic-related pollution monitoring. In the past, some reviews have been done about air pollution exposure models using monitoring data obtained from fixed stations, but no review about mobile sensing for air pollution has been undertaken. This article is a comprehensive review of the recent development in air pollution monitoring, including both the pollution data acquisition and the pollution assessment methods. Unlike the existing reviews on air pollution assessment, this paper not only introduces the models that researchers applied on the data collected from stationary stations, but also presents the efforts of applying these models on the mobile sensing data and discusses the future research of fusing the stationary and mobile sensing data