Phillip M. S. Burt

Broken conductors protection system using carrier communication

This paper presents a detection and signaling system designed to identify and locate high impedance faults caused by broken conductors on distribution primary feeders. Unlike conventional protection systems, which perform current sensing, the working principle of the proposed system consists on monitoring the voltage unbalance along a feeder. This allows the system to detect a fault occurrence even in cases when the conductor touches a high impedance earth surface (for instance asphalt). This system has an additional advantage of giving an indication of the location of a fault since it involves measurements at multiple points on a feeder. In order to detect the voltage unbalance produced by a broken conductor, a new sensor was developed which is sensitive to the electric field generated by primary feeders. A carrier communication channel is associated to each sensor allowing the high impedance fault occurrence information to reach the protection equipment located closer to or at the substation.

Efficient Kernel Computation for Volterra Filter Structure Evaluation

Despite their generality, conventional Volterra filters are inadequate for some applications, due to the huge number of parameters that may be needed for accurate modelling. When a state-space model of the target system is known, this can be assessed by computing its kernels, which also provides valuable information for choosing an adequate alternate Volterra filter structure, if necessary, and is useful for validating parameter estimation procedures. In this letter, we derive expressions for the kernels by using the Carleman bilinearization method, for which an efficient algorithm is given. Simulation results are presented, which confirm the usefulness of the proposed approach.

A polyphase IIR adaptive filter: error surface analysis and application

An analysis of the local convergence speed of constant gain algorithms for direct form IIR adaptive filters is initially presented, showing the adverse effects that result from the proximity of the poles of the modelled system to the unit circle and, for complex poles, to the real axis. A global analysis of the reduced error surface in these cases is also presented, which shows that, away from the global minimum, there will be regions with an almost constant error, where the convergence of constant gain algorithms tends to be slow. A polyphase IIR adaptive filter is then proposed and its local and global convergence properties are investigated, showing it to be specially well suited for applications with underdamped low-frequency poles. The polyphase structure is tested with different constant gain algorithms in an echo-cancellation example, attaining a gain of 14 to 70 times in global convergence speed over the direct form, at the price of a relatively modest increase in computational complexity. A theorem concerning the existence of stationary points for the polyphase structure is also presented.

A stable and efficient DSP implementation of a LSL algorithm for acoustic echo cancelling

We present an optimized DSP implementation of a modified error-feedback lattice least-square (EF-LSL) adaptive filtering algorithm. Simple measures that provide numerical stability for poor persistent excitation are also proposed. As a result of the optimization and the stability measures, an efficient and stable implementation of a fast algorithm of the RLS family was attained. We present the results of an acoustic echo cancelling experiment performed with the implemented algorithm. With a 40 MIPS SHARC DSP, up to 290 adaptive filter coefficients can be used. This represents an effective alternative to algorithms of the LMS family, while still retaining the good convergence properties of the RLS family.

Improvement of MISO Single-User Time Reversal Ultra-Wideband Using a DFE Channel Equalizer

In this paper a baseband multiple-input single-output (MISO) time reversal ultra-wideband system (TR-UWB) incorporating a decision feedback equalizer (DFE) is evaluated over the scenarios CM1 and CM3 of the IEEE 802.15.3a channel model. A semi-analytical performance based on a Gaussian approximation is derived and compared with simulation results. The results show that such approach represents a good approximation for the bit error rate (BER) analysis, and that the DFE, as well as an increase in the number of transmit antennas, improve the system performance.

A new framework for convergence analysis and algorithm development of adaptive IIR filters

A parameterization of an adaptive infinite impulse response (IIR) filters poles is developed, based on balanced realization theory. From this, we develop a local approximation of the actual adapted pole parameters, in which convergence speed is related to a certain eigenvalue spread. This, in turn, is shown to relate to the Hankel singular values of the system to be identified, as well as certain coefficient sensitivity functions of the adapted filter. The local approximation is not restricted to stationary points. At these points, however, it is equivalent to a Hessian approximation, with the benefit of decomposing the Hessian matrix into terms related to the aforementioned singular values and sensitivity functions. The description of the adaptation process by means of the developed approximation leads to a greater understanding of the effects on convergence speed of factors, such as the Hankel singular values of the system, its order, the distribution of its poles, and the choice of adapted parameters. In particular, the use of direct form and lattice parameters are compared in detail. Based on these properties, a new adaptive IIR algorithm with faster convergence and relatively low computational complexity has recently been proposed, which is briefly mentioned. Results also indicate a potential for variable gain algorithms.

Evaluating the potential of Volterra-PARAFAC IIR models

The Volterra-PARAFAC (VP) nonlinear system model, which consists of a FIR filterbank followed by a memoryless nonlinearity, aims at offering a good compromise between accuracy and parametric complexity. Here, for an even better compromise, we propose a generalization with IIR filters (VPI model) and evaluate both models. For the evaluation, we consider the concrete case of two audio loudspeakers and initially compute reference Volterra kernels from their known physical state-space models, using an efficient procedure. Then, VP and VPI models are derived and their accuracy is tested. As shown, the VPI models have in this case only 15 to 26 % of the parametric complexity of VP models with the same accuracy, which points to a great potential for accurate and efficient nonlinear system modeling.

Performance of MISO Time Reversal Ultra-Wideband over an 802.15.3a Channel Model

This paper analyzes the performance of a baseband multiple-input single-output (MISO) time reversal ultra-wideband system (TR-UWB) over the IEEE 802.15.3a channel model. Two scenarios are considered, CM1 based on LOS (0-4 m) channel measurements and CM3 based on NLOS (4-10 m) channel measurements. A semi-analytical performance expression is derived and compared with simulation results in terms of the number of antenna elements, number of users, and transmission rate. The results show that the system performance is improved with an increase in the number of transmit antenna elements and that additional equalization and multiple access enhancement schemes are necessary for high transmission rates.

On the convergence speed of inverse identification adaptive IIR filters

The approach based on balanced realization theory, previously used to analyze the convergence speed of adaptive IIR filters in the identification configuration and to propose a faster algorithm (sucessive approximations algorithm), is now used in the inverse identification configuration. This case is of interest for applications such as channel equalization and system identification itself. The main result we obtain here is that, while in identification configuration the Hankel singular values of the system being identified have an important effect on convergence speed, in the inverse identification case it is the Hankel singular values of a certain system related to the system being identified that have this role. From this result, a condition for faster convergence speed is obtained, which suggests that an adaptive algorithm similar to the sucessive approximations algorithm can be obtained for inverse identification. Numerical examples are presented, which strongly corroborate the adopted analytical approach.

A polyphase IIR adaptive filter

A polyphase structure for infinite-impulse response (IIR) adaptive filtering is proposed and compared to the direct structure in terms of their reduced error surface. It is shown that the general shape of its surface can make the polyphase structure have higher convergence speed, alleviating the problem of convergence speed in IIR adaptive filters and allowing their computational complexity gain over finite-impulse response (FIR) adaptive filters to be exploited. Benefits regarding filter stability are also achieved with the polyphase structure. An example of a high-speed digital subscriber line (HDSL) application is presented, for which the polyphase structure attains a gain of up to 70 times in convergence speed over an IIR direct structure, leading to roughly the same convergence speed of a FIR structure but with only 12% of its computational complexity. The question of uniqueness of the stationary points of the proposed structure is also discussed. It is pointed out that for white input and sufficient modeling, all stationary points are global minima, a result which does not follow directly from an equivalent property of the direct structure.