Blind Deconvolution for Two-thermocouple Sensor Characterisation

Thermocouples are one of the most popular devices for temperature measurement due to their robustness, ease of manufacture and installation, and low cost. However, when used in the harsh environment found in combustion systems and automotive engine exhausts, large wire diameters are required and consequently the measurement bandwidth is reduced. This paper describes two new algorithmic compensation techniques based on blind deconvolution to address this loss of high-frequency signal components using the measurements from two thermocouples. In particular, a continuous-time approach is proposed, combined with a cross-relation blind deconvolution for parameter estimation. A feature of this approach is that no a priori assumption is made about the time constant ratio of the two thermocouples. The advantages, including small estimation variance and limitations of the method, are highlighted using results from simulation and test rig studies.

Time signatures of impulsively generated coronal fast wave trains

Impulsively generated short-period fast magneto-acoustic wave trains, guided by solar and stellar coronal loops, are numerically modelled. In the developed stage of the evolution, the wave trains have a characteristic quasi-periodic signature. The quasi-periodicity results from the geometrical dispersion of the guided fast modes, determined by the transverse profile of the loop. A typical feature of the signature is a tadpole wavelet Spectrum: a narrow-spectrum tail precedes a broad-band head. The instantaneous period of the oscillations in the wave train decreases gradually with time. The period and the spectral amplitude evolution are shown to be determined by the steepness of the transverse density profile and the density contrast ratio in the loop. The propagating wave trains recently discovered with the Solar Eclipse Coronal Imaging System (SECIS) instrument are noted to have similar wavelet spectral features, which strengthens the interpretation of SECIS results as guided fast wave trains.

HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels

In this paper we concentrate on the direct semi-blind spatial equalizer design for MIMO systems with Rayleigh fading channels. Our aim is to develop an algorithm which can outperform the classical training based method with the same training information used, and avoid the problems of low convergence speed and local minima due to pure blind methods. A general semi-blind cost function is first constructed which incorporates both the training information from the known data and some kind of higher order statistics (HOS) from the unknown sequence. Then, based on the developed cost function, we propose two semi-blind iterative and adaptive algorithms to find the desired spatial equalizer. To further improve the performance and convergence speed of the proposed adaptive method, we propose a technique to find the optimal choice of step size. Simulation results demonstrate the performance of the proposed algorithms and comparable schemes.