Power efficient low latency architecture for decoder: Breaking the ACS bottleneck

Viterbi decoder (VD) is the majority used decoder for convolutional codes which play a role in WLAN and WSN applications. The trellis in VD needs proper analysis to calculate the metric at each stage to obtain a shortest path from every state to the next state. Existing techniques in VD design are namely (a) pipelined architecture, (b) modular ACS and buffers technique, and (c) quasi cyclic trellis technique. The key challenge of the VD trellis circuit is to attain high throughput and better latency performance with low power consumption without affecting hardware complexity of VD. This paper presents several of conventional methods used in VD. We also proposed a new method for VD with K the constraint length as multiple of M, the radix in trellis to calculate the shortest survival path to travel in trellis. The proposed VD is simulated using Xilinx. Use of a trace back approach in the proposed Viterbi decoder with capacitive and resistive feedback yields better throughput, latency, and power consumption with respect to other techniques. The static power outputs obtained in RE, shift update, and selective update methods using Libero IDE are also compared.     

Thin-film strain gauge sensors for ion thrust measurement

In order to measure the thrust produced by a stationary plasma thruster, a measurement system has been developed using a thrust balance with thin-film strain gauge sensors. For this purpose, strain gauges were designed and deposited on the columns of the thrust balance fabricated and necessary signal conditioning circuits have been used. The performance of the system developed was studied, in a vacuum chamber under space simulated conditions, by activating the thruster. In situ calibration was done using Lami's principle. For discharge powers varying from 210-275 W, the measured values of thrust were found to be in the range of 11-16 mN with an accuracy of /spl plusmn/1 mN and resolution of 0.12 mN. Specific impulse and efficiency were also estimated.     

Artifact cleaning of motor imagery EEG by statistical features extraction using wavelet families

Electroencephalogram (EEG) and its sub-bands represent electrical pattern of human brain. EEG signal contains transient components, spikes, and different types of artifacts due to eye blinking, movement of the person, anxiety, and so forth, during EEG capture. Wavelet transforms are powerful mathematical tool for sampling approximation to get clean EEG. It also helps in filtering, sampling, interpolation, noise reduction, signal approximation and signal enhancement, and feature extraction. In this paper, we have analyzed artifact cleaning via PSD graphs and statistical features extracted from motor imagery EEG-like standard deviation variance. For this, we considered 19 channels EEG signal and applied orthogonal Daubechies wavelet, bi-orthogonal rbio wavelet and Coifman wavelets to check the better performance of different wavelets. Coifman wavelet uses both scaling function and vanishing moments for sampling approximation and hence give smooth sampling compared to rbio and Daubechies wavelet transforms. Coif is a compactly supported wavelet system which also helps in smooth sampling approximations than other wavelets in the state of arts. The detailed coefficients and approximate coefficients can be further used for extracting features from EEG and classification purposes. Artifacts cleaning is thus observed better in coif wavelet analysis compared to other wavelets from the power distributions as power spectral density (PSD) graphs, standard deviation and variance obtained. Matlab R2013b is used for filtering and sampling EEG. Python 2.7 is used for statistical features extraction.     

The attitude control system of the satellite for earth observation ‘ Bhaskara ’

The satellite for earth observation (Bhaskara) launched on 7 June 1979 has two TV cameras and a passive microwave radiometer for earth resources survey and meteorological studies respectively. As it had to be a minimally modified version of the earlier spin-stabilised satelliteAryabhata, it is configured as a spin-stabilised satellite, with a spin rate of between 6 to 11 rev/min and a spin axis perpendicular to the orbital plane within 3°. The cold gas system ofAryabhata was modified to provide a low and controlled thrust for spin-up and spin-axis orientation operations. Two horizon-crossing sensors are used for automatic spin-axis control and attitude determination on ground. This paper presents a report on the system evolution, design, simulation and on-orbit performance ofBhaskara.