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

On the choice of reference in sensor offset calibration

Sensor calibration is an indispensable feature in any networked cyberphysical system. In this paper we consider a sensor network plagued with offset errors measuring a rank-1 signal subspace where each sensor collects measurements under additive zero-mean Gaussian noise. Under varying assumptions on the underlying noise covariance, we investigate the effect of using an arbitrary reference for estimating the sensor offsets in contrast to the mean of all the unknown sensor offsets as a reference. We show that the mean reference yields an efficient estimator in the mean square error sense. If the underlying noise is homoscedastic in nature then the mean reference yields a factor 2 improvement on the variance as compared any arbitrarily chosen reference within the network. Furthermore when the underlying noise is independent, but not identical, we derive an expression for the improvement offered by the mean reference. We demonstrate our results using the problem of clock synchronization in sensor networks, and present directions for future work.Comment: In submissio

Multi-FEAT: Multi-Feature Edge AlignmenT for Targetless Camera-LiDAR Calibration

The accurate environment perception of automobiles and UAVs (Unmanned Ariel Vehicles) relies on the precision of onboard sensors, which require reliable in-field calibration. This paper introduces a novel approach for targetless camera-LiDAR extrinsic calibration called Multi-FEAT (Multi-Feature Edge AlignmenT). Multi-FEAT uses the cylindrical projection model to transform the 2D(Camera)-3D(LiDAR) calibration problem into a 2D-2D calibration problem, and exploits various LiDAR feature information to supplement the sparse LiDAR point cloud boundaries. In addition, a feature matching function with a precision factor is designed to improve the smoothness of the solution space. The performance of the proposed Multi-FEAT algorithm is evaluated using the KITTI dataset, and our approach shows more reliable results, as compared with several existing targetless calibration methods. We summarize our results and present potential directions for future work

Correlation between elevated serum ferritin and HbA1c in type 2 diabetes mellitus

Background: Serum Ferritin, an acute phase reactant is a marker of iron stores in the body. Recent studies indicate that increased body iron stores and subclinical hemochromatosis has been associated with the development of glucose intolerance, type 2 diabetes, metabolic syndrome and possibly the development of diabetic retinopathy, nephropathy and vascular dysfunction. This study was carried out to examine and establish a relationship between Serum Ferritin with Type 2 diabetes mellitus and metabolic syndrome and to examine whether a correlation between S. ferritin and FBS, HbA1c exists.Methods: 86 type 2 diabetes subjects (M:F - 57:29, mean age 54.3±9.2 years, mean BMI 24.28kg/m2) which included 24 patients with metabolic syndrome were studied and compared with controls. S. ferritin, Hb, ESR, FBS, PPBS, HbA1c and fasting lipid profile were measured.Results: Serum ferritin was significantly higher in diabetic patients when compared to controls and serum ferritin had a positive correlation with increasing duration of diabetes.Conclusions: There was a positive correlation between serum ferritin and FBS, HbA1c. There was no correlation between serum ferritin and age, sex, metabolic syndrome, coexistent hypertension, total cholesterol, LDL and serum triglycerides.

Familial esophageal achalasia in mother and son

Familial esophageal achalasia a rare presentation, is most often described in monozygotic twins or siblings. Parent/child association is very rare and exhaustive review of the literature found about 5 times as many instances of affected siblings than instances of affected parent/child. Only seven instances of parent/child association have been reported till date. We report a 75 -year-old lady with achalasia cardia and her son who developed the same illness one year later. Mother was treated by Heller's surgery and son is presently on medical management