Recovering Amplitudes and Phases From Saturated Multifrequency Sinusoid Signals

Abstract

In this paper, a novel method is proposed to recover and extract the original signal parameters from the saturated multifrequency sinusoid wave signals. It makes use of the zerocrossing characteristics of the multifrequency sinusoid signals, to collect valid samples in unsaturated parts of the signals. On these valid samples, the amplitudes and phases of the specific original ac sensing signals can be linearly computed by applying the least square method. The simulation results show that the proposed method has satisfactory accuracy even with very large saturation (∼10 times of the saturation limit) and large dc offset, which frees us from the restriction to avoid the signal saturation problem in the signal acquisition. The method is realized by the software algorithm, and no longer requires the common used hardware-the phase sensitive detection circuit. Hence when it is applied to the magnetic coupling system, we will obtain much simpler system composition, higher accuracy, and high execution speed.Index Terms-Multifrequency signal processing, amplitude and phase extraction, magnetic coupling, least square fitting method.

Undersampling and Saturation for Impedance Spectroscopy Performance

“…As there are no examples of saturated curve extraction for impedance spectroscopy to compare against, the performance of the algorithm is compared against a similar process used in the field of magnetic coupling. Hu et al [23] achieved measurements up to 10 times full scale, while maintaining an accuracy of 0.6% with a similar noise level (-20 dB) as in this paper. Above this level, however, the results degrade significantly and the error increases to 3.5%.…”

“…Saturated curve extraction using least-squares regression is therefore uniquely well-suited to be used in impedance spectroscopy for dynamic range improvement. Saturated sinusoid recovery with least-squares regression, even with multiple frequencies [23] is not a novel concept. Leveraging the unique experimental setup of impedance spectroscopy to optimise the least-squares algorithm, however, is novel combination of two complementary techniques.…”

An Improved Magnetic Tracking Method Using Rotating Uniaxial Coil With Sparse Points and Closed Form Analytic Solution

“…There are many methods to reconstruct the cosine signal and extract the amplitude, phase and DC information of the cosine signal, such as FFT and function fitting method (FFM) [32], [33]. Here we will use FFM, which is based on the Least Square Method.…”