Open airscrew VTOL concepts

The following concepts, based on using open airscrew(s) for VTOL maneuvers, are re-examined in light of current technology: (1) tip-driven helicopters, (2) compound helicopters; and (3) high-speed VTOL aircraft, represented by tiltrotors, tiltwings, retractoplanes and stoppable rotors. Criteria, permitting one to compare performance of aircraft using diverse lifting and propelling methods are established. Determination of currently possible performance, indication of near-future potentials, and comparison of those items with the baseline levels (as represented by contemporary shaft-driven helicopters, first generation tiltrotors, and commercial turboprop fixed-wind aircraft) constitutes bulk of this report

Filtering Nonuniformly Sampled Grid-Based Signals

This paper presents an example application of digital alias-free signal processing, where a sequence of irregularly spaced, yet uniformly gridded, samples of a bandlimited discrete-time signal is filtered by using an oversampled finite impulse response filter. The mathematical model of the proposed filter is introduced, and a new interpolation formula for calculating the convolution operation of the filter, based on nonuniform sampling, is derived. In addition, uniform grid versions of Total Random, Stratified and Antithetical Stratified random sampling techniques are demonstrated. We carry out numerical comparison between these techniques and the proposed one in terms of Fourier transform estimates of the filtered output signal. The proposed interpolation technique shows enhancements over other sampling techniques after certain number of sampling points. Furthermore, it has a faster uniform convergence rate of the normalized root mean squared error than other techniques

FIR filters for systems with input clock jitter

A method of designing fixed-coefficient FIR filters whose input signals are sampled irregularly due to clock jitter is presented. The approach does not require direct measuring of the jitter. Instead it is assumed that the jitter is a strictly stationary stochastic process for which some statistical information is available. Preliminary analysis of degradation of filter performance due to presence of jitter is also presented. Some numerical analyses illustrate the main assertions of the paper

Spectral analysis of randomly sampled signals: suppression of aliasing and sampler jitter

Nonuniform sampling can facilitate digital alias-free signal processing (DASP), i.e., digital signal processing that is not affected by aliasing. This paper presents two DASP approaches for spectrum estimation of continuous-time signals. The proposed algorithms, named the weighted sample (WS) and weighted probability (WP) density functions, respectively, utilize random sampling to suppress aliasing. Both methods produce unbiased estimators of the signal spectrum. To achieve this effect, the computational procedure for each method has been suitably matched with the probability density function characterising the pseudorandom generators of the sampling instants. Both proposed methods are analyzed, and the qualities of the estimators they produce have been compared with each other. Although none of the proposed spectrum estimators is universally better than the other one, it has been shown that in practical cases, the WP estimator produces generally smaller errors than those obtained from WS estimation. A practical limitation of the approaches caused by the sampling-instant jitter is also studied. It has been proven that in the presence of jitter, the theoretically infinite bandwidths of WS and WP signal analyses are limited. The maximum frequency up to which these analyses can be performed is inversely proportional to the size of the jitter

Estimation of Fourier Transform Using Alias-free Hybrid-Stratified Sampling

This paper proposes a novel method of estimating the Fourier Transform (FT) of deterministic, continuous-time signals, from a finite number \u1d441 of their samples taken from a fixed-length observation window. It uses alias-free hybrid-stratified sampling to probe the processed signal at a mixture of deterministic and random time instants. The FT estimator, specifically designed to work with this sampling scheme, is unbiased, consistent and fast converging. It is shown that if the processed signal has continuous third derivative, then the estimator's rate of uniform convergence in mean square is \u1d441^−5. Therefore, in terms of frequency-independent upper bounds on the FT estimation error, the proposed approach significantly outperforms existing estimators that utilize alias-free sampling, such as total random, stratified sampling, and antithetical stratified whose rate of uniform convergence is \u1d441^−1. It is proven here that \u1d441^−1 is a guaranteed minimum rate for all stratified-sampling-based estimators satisfying four weak conditions formulated in this paper. Owing to the alias-free nature of the sampling scheme, no constraints are imposed on the spectral support of the processed signal or the frequency ranges for which the Fourier Transform is estimated

Digital filtering of band-limited signals using Periodic Nonuniform Sampling

We examine the problem of digital filtering of band-limited signals by means of a linear digital filter with one or more stopbands. The main target of the study is to filter the signals using lower than Landau sampling rates, where the Landau rate is defined as the total bandwidth of the input signal. In order to reach such low rates Periodic Nonuniform Sampling is employed. We derive necessary and sufficient conditions for perfect filtering, and propose a practical algorithm for constructing PNS grids that allow for sub-Landau sampling and filtering. Finally, we present a reconstruction system and provide a numerical result illustrating the proposed method

A novel spectral estimation method by using periodic nonuniform sampling

In this paper we present a method of estimating power spectrum density of random ergodic signals. The method allows use of arbitrarily low sampling rates to achieve the goal. We compare our method with similar schemes reported in research literature and argue superiority of our approach in terms of its suitability for practical implementations. The most visible difference between our approach and the previously reported ones consists in replacing Poisson additive random sampling with deterministic sampling. Comparing with the approaches based on the Poisson additive random sampling, where theoreticall infinitely large resources are needed to implement them accurately, our approach clearly relies on limited and well defined resources

Optimal periodic sampling sequences for nearly-alias-free digital signal processing

Alias-free DSP (DASP) is a methodology of processing signals digitally inside bandwidths that are wider than the famous Nyquist limit of half of the sampling requency. DASP is facilitated by suitable combination of nonuniform sampling and appropriate processing algorithms. In this paper we propose a new method of constructing sampling schemes for the needs of DASP. Unlike traditional approaches that rely on randomly selected sampling instants we use deterministic schemes. A method of optimizing such sequences aimed at minimization of aliasing is proposed. The approach is tested numerically in an experiment where an undersampled signal is processed using DASP; first to estimate the signal's spectrum support function and then the spectrum itself. We demonstrate advantages of the proposed approach over those that use random sampling

Design of Monopole Antennas for UWB Applications

Presented are the design method, equations, and results of a broadband monopole antenna for UWB applications. The antenna is a fat monopole; made of rectangular and circular patches. Measured results show a passband of 2.8–11.97 GHz. Parametric studies of the effects of the ground plane and the gap between the radiating element and the ground plane were done and their results given. The gain and efficiency are also provided; with average values of 4.34 dBi and 96% respectively. The obtained radiation patterns show bi-directional patterns in the E-plane and omni-directional patterns in the H-plane

Evaluation of several reconstruction methods of bandlimited signals

In this paper we evaluate several methods of reconstructing signals from finite sets of their samples. A class of band-limited signals is considered. Both, noise-free and noisy cases are studied. The evaluation is performed by extensive simulations where different shapes and bandwidths of the reconstructing filters are examined. We demonstrate that if a fixed number of signal samples are used in the reconstruction, then the signal to noise ratio becomes the main factor limiting the quality of the reconstruction