Frequency estimation for low earth orbit satellites

University of Technology Sydney. Faculty of Engineering.Low Earth Orbit (LEO) satellites have received increased attention in recent years. They have been proposed as a viable solution for remote sensing, telemedicine, weather monitoring, search and rescue and communications to name a few applications. LEO satellites move with respect to an earth station. Thus, the station must be capable of tracking the satellite both spatially and in frequency. In addition, as the spectrum becomes more congested, links are being designed at higher frequencies such as Ka band. These frequencies experience larger attenuations and therefore the system must be capable of operating at low signal to noise ratios. In this dissertation we report on the research conducted on the following problems. Firstly, we study the estimation of the frequency of a sinusoid for the purpose of acquiring and tracking the frequency of the received signal. Secondly, we propose the use of the frequency measurements to assist the spatial tracking of the satellite. The highly dynamic environment of a LEO system, combined with the high Ka band frequencies result in large Doppler rates. This limits the available processing time and, consequently, the fundamental resolution of a frequency estimator. The frequency estimation strategy that is adopted in the thesis consists of a coarse estimator followed by a fine estimation stage. The coarse estimator is implemented using the maximum of the periodogram. The threshold effect is studied and the derivation of an approximate expression of the signal to noise ratio at which the threshold occurs is examined. The maximum of the periodogram produces a frequency estimate with an accuracy that is Ο(N⁻¹), where N is the number of data samples used in the FFT. The lower bound for the estimation of the frequency of a sinusoid, given by the Cramer-Rao bound (CRB), is Ο(N⁻³⁄²) . This motivates the use of a second stage in order to improve the estimation resolution. A family of new frequency estimation algorithms that interpolate on the fractional Fourier coefficients is proposed. The new estimators can be implemented iteratively to give a performance that is uniform in frequency. The iterative algorithms are analysed and their asymptotic properties derived. The asymptotic variance of the iterative estimators is only 1.0147 times the asymptotic CRB. Another method of refining the frequency estimate is the Dichotomous search of the periodogram peak. This is essentially a binary search algorithm. However, the estimator must be padded with zeroes in order to achieve a performance that is comparable to the CRB. An insight into this is offered and a modified form that does not require the zero-padding is proposed. The new algorithm is referred to as the modified dichotomous search. A new hybrid technique that combines the dichotomous search with an interpolation technique in order to improve its performance is also suggested. The second research mm was to study the possibility of applying the frequency measurements to obtain spatial tracking information. This is called the frequency assisted spatial tracking (FAST) concept. A simple orbital model is presented and the resulting equations are used to show that the Doppler shift and rate uniquely specify the satellite’s position for the purpose of antenna pointing. Assuming the maximum elevation of the pass is known, the FAST concept is implemented using a scalar Extended Kalman Filter (EKF). The EKF performance was simulated at a signal to noise ratio of 0dB. The off-boresight error was found better than 0.1° for elevations higher than 30°

Predicting Bearing Fault in the Drone Freight Industry: Legal Liability in Australia

Many people are now aware of drones or remotely piloted aircraft (RPAs), and several others have predicted the significant impacts that drones will bring across society. Today, there is an expectation that drones will play a pivotal role in industries such as surveillance, security, surveying, construction, and freight transport. However, in all these cases, whenever a drone is flying over a populated area, it poses a danger to people or things on the ground. Perhaps the sector where the greatest risk of injury to the everyday person exists is the drone delivery industry. The drone freight industry is proliferating fast, with many companies like Skycart and Amazon investing in this sector. These companies plan to transport groceries, medical supplies, food, and par- cels, among many other things. If fleets of delivery drones are deployed around suburbs, the descent to lower altitudes and the general logistics of an airborne delivery presents a novel risk of harm. A drone failure resulting in a crash could lead to property damage, destruction of natural environments, and injury or death to persons, especially in areas of high population density. One promising way to prevent such harm is to use structural condition monitoring technology to preempt any deterioration of the airworthiness of a drone. In the absence of any existing precedent or authority on this, this Article investigates the legal implications of using such technology to guide future regulations and areas of research

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An efficient VLSI architecture for 4 × 4 16-QAM sorted QR-factorisation based V-BLAST decoder

This paper presents a practically realisable VLSI architecture for a 4 × 4 16-QAM MIMO wireless communication system using the Vertical Bell Labs Layered Space-Time (V-BLAST) detection scheme. The proposed implementation employs the QR-factorisation technique. The design and optimisation of the pre-decoder block are carried out using the COordinate Rotation DIgital Computer (CORDIC) processors. In order to avoid the numerical problems associated with Back Substitution (BS) based Symbol Interference Cancellation (SIC), a modified BS-SIC architecture that eliminates the need for division and multiplication is proposed. Not only does this substantially reduce the hardware cost, but also enjoys improved numerical stability. As the decoder hardware design can also be simplified by rendering it oblivious to the power normalisation in the transmitter side of the MIMO wireless system, we have designed a matching compensation unit at the receiver. The resulting VLSI architecture was implemented on an Altera Stratix Field Programmable Gate Array (FPGA) platform and on a 0.18 μm Application Specific Integrated Circuits (ASIC) platform. Detection throughput ratings of 149 Mbps and 212 Mbps were achieved. However, the lower hardware complexity of the BS-SIC based decoder architecture comes at the cost of a degradation in the Bit Error Rate (BER) performance with respect to the original higher complexity V-BLAST. Therefore, we also propose a novel parallel decoding scheme that is aimed at improving the system BER. This novel scheme allows for a compromise between the hardware overhead and the BER performance. As the hardware complexity is increased, the performance approaches the original V-BLAST limit. © 2010 Elsevier GmbH. All rights reserved

Predicting Bearing Fault in the Drone Freight Industry: Legal Liability in Australia

Many people are now aware of drones or remotely piloted aircraft (RPAs), and several others have predicted the significant impacts that drones will bring across society. Today, there is an expectation that drones will play a pivotal role in industries such as surveillance, security, surveying, construction, and freight transport. However, in all these cases, whenever a drone is flying over a populated area, it poses a danger to people or things on the ground. Perhaps the sector where the greatest risk of injury to the everyday person exists is the drone delivery industry. The drone freight industry is proliferating fast, with many companies like Skycart and Amazon investing in this sector. These companies plan to transport groceries, medical supplies, food, and par- cels, among many other things. If fleets of delivery drones are deployed around suburbs, the descent to lower altitudes and the general logistics of an airborne delivery presents a novel risk of harm. A drone failure resulting in a crash could lead to property damage, destruction of natural environments, and injury or death to persons, especially in areas of high population density. One promising way to prevent such harm is to use structural condition monitoring technology to preempt any deterioration of the airworthiness of a drone. In the absence of any existing precedent or authority on this, this Article investigates the legal implications of using such technology to guide future regulations and areas of research