Abstract
This paper sets out a method for improving the resolution of resonant microwave sensors. Usually, the frequency response of these devices is associated with a low quality factor, and consequently with a low resolution in terms of tracking capacity of the resonance frequency shift. Furthermore, since only a finite number of samples can be acquired during the measurement process, the “true” resonance frequency may not be included in the set of acquired data. In order to have an accurate estimate of the resonance frequency, high performance systems with very fine frequency sampling are thus required. To limit these drawbacks, an iterative algorithm is presented which aims to refine the response of resonant microwave sensors by means of a suitable post-processing. The algorithm evaluation is first carried out on synthetic data, and then applied on experimental data referring to a practical scenario, which is inherent to return loss measurements performed by a microwave patch antenna immersed in a water-glucose solution with different concentrations.
Highlights
Nowadays, microwave sensors are found in a variety of contexts, as their field of application is extremely broad
Referring to biomedical applications, in [2], the design of a resonant microwave sensor for applications related to blood glucose monitoring is proposed, showing that, in order to obtain a sensor suitable to provide an accurate estimation of the glucose concentration level, it is necessary to take into account the variations of both the real and the imaginary part of the complex permittivity of the medium under investigation as a function of frequency, yet discussed in [3]
In order to limit the above drawbacks, an iterative algorithm is proposed in this work which leads to post-process the acquired samples of the frequency response, in order to significantly increase the quality factor and achieve a more accurate estimate of the resonance frequency
Summary
Microwave sensors are found in a variety of contexts, as their field of application is extremely broad. This problem can be addressed from the circuit point of view, by means of some active microwave device which allows an increase in the quality factor of sensors [11,12] Another important aspect to be considered is related to the fact that the frequency response samples, acquired by the measurement instrumentation, represent a discrete set with finite extension, so there is a very high probability that the sample associated with the resonance frequency will not be captured correctly. In order to limit the above drawbacks, an iterative algorithm is proposed in this work which leads to post-process the acquired samples of the frequency response, in order to significantly increase the quality factor and achieve a more accurate estimate of the resonance frequency This algorithm has high performance even starting from a relatively very low number of acquired samples of the sensor response within a frequency band with a high extension. An appropriate performance analysis of this algorithm is first carried out using synthetic data; the proposed method is tested on measured data collected by a microstrip patch antenna immersed in a water-glucose solution, which represents a simplified case in the context of a blood glucose monitoring problem
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