Abstract. Reverberation chambers show transient behaviour when excited with a pulsed signal. The field intensities can in this case be significantly higher than in steady state, which implies that a transient field can exceed predefined limits and render test results uncertain. Effects of excessive field intensities of short duration may get covered and not be observable in a statistical analysis of the field characteristics. In order to ensure that the signal reaches steady state, the duration of the pulse used to excite the chamber needs to be longer than the time constant of the chamber. Initial computations have shown that the pulse width should be about twice as long as the time constant of the chamber to ensure that steady state is reached. The signal is sampled in the time domain with a sampling frequency according to the Nyquist theorem. The bandwidth of the input signal is determined using spectral analysis. For a fixed stirrer position, the reverberation chamber, wires, connectors, and antennas can jointly be considered as a linear time-invariant system. In this article, a procedure will be presented to extract characteristic signal properties such as rise-time, transient overshoot and the mean value in steady state from the system response. The signal properties are determined by first computing the envelope of the sampled data using a Hilbert transform. Subsequent noise reduction is achieved applying a Savitzky–Golay filter. The point where steady state is reached is then computed from the slope of the envelope by utilising a cumulative histogram. The spectral analysis is not suitable to examine the transient behaviour and determine the time constants of the system. These constants are computed applying the method of Prony, which is based on the estimation of a number of parameters in a sum of exponential functions. An alternative to the Prony Method is the Time-Domain Vector-Fit method. In contrast to the first mentioned variant, it is now also possible to determine the transfer function of the overall RC system. Differences and advantages of the methods will be discussed.
Near-linear time constant-factor approximation algorithm for branch-decomposition of planar graphs
