Electromagnetic Differential Measuring Method: Application in Microstrip Sensors Developing

Abstract

Electromagnetic radiation is energy that interacts with matter. The interaction process is of great importance to the sensing applications that characterize material media. Parameters like constant dielectric represent matter characteristics and they are identified using emission, interaction and reception of electromagnetic radiation in adapted environmental conditions. How the electromagnetic wave responds when it interacts with the material media depends on the range of frequency used and the medium parameters. Different disciplines use this interaction and provides non-intrusive applications with clear benefits, remote sensing, earth sciences (geology, atmosphere, hydrosphere), biological or medical disciplines use this interaction and provides non-intrusive applications with clear benefits. Electromagnetic waves are transmitted and analyzed in the receiver to determine the interaction produced. In this work a method based in differential measurement technique is proposed as a novel way of detecting and characterizing electromagnetic matter characteristics using sensors based on a microstrip patch. The experimental results, based on simulations, show that it is possible to obtain benefits from the behavior of the wave-medium interaction using differential measurement on reception of electromagnetic waves at different frequencies or environmental conditions. Differential method introduce advantages in measure processes and promote new sensors development. A new microstrip sensor that uses differential time measures is proposed to show the possibilities of this method.

Keywords: differential measurement; dispersive media; microstrip sensor; multifrequency treatment; remote sensing.

Figure 1

EM waves treatment in remote sensing applications. Devices need to synchronize the reference systems. Reference systems have the same reference time.

Figure 2

Differential method with different frequencies. The differential measures in the receiver incorporate information. Time synchronization is not necessary. The differential method proposed can also use a single frequency inducing different medium conditions.

Figure 3

Multifrequency FDTD simulation in a dielectric medium. Transparent (${ϵ}_{eff}=1$) for the first frequency at the top. Different interaction (propagation speed and energy absorption) for other frequencies with different ${ϵ}_{eff}$. Time differences $\mathrm{\Delta }{t}_1$ and $\mathrm{\Delta }{t}_2$ can be measured to analyze dielectric medium.

Figure 4

Rectangular wave guide ($L=60$ mm, $a=7.894$ mm and $b=3.947$ mm) used in propagation simulation built with two differentiated transmission lines. One input signal is transmitted (1) to the waveguide and derived into the two transmission lines. Two output ports signals are obtained (2) and time difference of arrival between two waves are obtained (3). The difference measured (4) characterize medium ${ϵ}_r$.

Figure 5

Three pictures with wave propagation simulation (in time domain) using waveguide shown in Figure 4; $m1$ is the input pulse, $m2$ is output line pulse with $ϵ=1$, $m3$ is output line pulse with unknown ${ϵ}_r$. One input signal is transmitted ($m1$) to the waveguide and derived into the two transmission lines. Two output ports signals are obtained ($m2$ and $m3$) and time difference of arrival between two waves are obtained (${\mathrm{\Delta }}_t=m3-m2$). The measured difference (4) characterizes ${ϵ}_m$.

Figure 6

Permittivity obtained using differential measures in equation.

Figure 7

Frequency response in rectangular wave guide with different dielectric (${ϵ}_r$) materials. Simulation using HFSS software is performed. Differences in cutoff frequencies ($m_i-m_j=f{c}_i-f{c}_j={\mathrm{\Delta }}_f$) are obtained to calculate unknown ${ϵ}_r$.

Figure 8

Basic microstip sensor.

Figure 9

Microstip sensor proposed. Differential measures on electrodes are performed.

Figure 10

Sensitive analysis to determine how different values of dielectric medium (${ϵ}_m$) and microstrip dimensions (h and w) impact on effective permittivity (${ϵ}_{eff}$) shown in Equation (10).

Figure 11

General model of microstip sensor proposed ($L=25$ mm, $width=10$ mm, $height=2$ mm and patch $line=0.8$ mm). Numeric differential measures ($d_{mr}$) can be obtained to characterize dielectric medium unknown (${ϵ}_m$), knowing reference permittivity (${ϵ}_r$) and microstrip substrate (${ϵ}_s$).

Figure 12

Microstrip line simulation with reference and substrate permittivity ${ϵ}_r=4$. Different permittivity medium ${ϵ}_m$ are used to obtain phase shift on microstrip terminals.

Figure 13

Microstrip line simulation with reference and substrate permittivity ${ϵ}_r=4$. Different permittivity medium ${ϵ}_m$ are used to obtain differential electric field on microstrip terminals.

Figure 14

Microstrip line used as a sensor to detect permittivity levels of unknown material. Microstrip patch can have different dimensions and forms.

Figure 15

Configuration of a sensor microstrip that detect low, medium or high permittivity levels in applications where permittivity must be detected.