INTERROGATION OF ACOUSTIC WAVE SENSORS

Abstract

An interrogation device for interrogating an acoustic wave sensor device comprises a transmission antenna; a reception antenna; and a processor configured for determining in-phase components I and quadrature components Q of a response signal received from the sensor in N consecutive frames of the response signal; determining moduli |Y| of the in-phase components I and quadrature components Q; determining a first norm M based on the moduli |Y|; determining a first weighting function W based on the first norm M and the moduli |Y|; determining in-phase components I and quadrature components Q of an N+1th frame of the response signal; determining moduli |Y| of in-phase components I and quadrature components Q of the N+1th frame; and applying the first weighting function W to the determined moduli |Y| of the response signal in the N+1th frame to obtain weighted moduli |Y|w of the response signal for the N+1th frame.

Claims

1. An interrogation device for interrogating an acoustic wave sensor, comprising: a transmission antenna configured for transmitting an interrogation radiofrequency signal to the acoustic wave sensor device; a reception antenna configured for receiving a response radiofrequency signal from the acoustic wave sensor device; and a processing means configured for: determining in-phase components I and quadrature components Q of the received response radiofrequency signal in each of N consecutive frames of the response radiofrequency signal, N being an integer larger than 1, wherein each of the N frames comprises X sampling points; determining the moduli |Y| of each of the pairs of the determined in-phase components I and the quadrature components Q; determining a first norm M based on the determined moduli |Y|; determining a first weighting function W based on the determined first norm M and the determined moduli |Y|; determining the in-phase components I and the quadrature components Q of an N+1th frame of the received response radiofrequency signal, the N+1th frame comprising X sampling points of the received response radiofrequency signal; determining the moduli |Y| of each of the pairs of the determined in-phase components I and the quadrature components Q of the N+1th frame; and applying the first weighting function W to the determined moduli |Y| of the received response radiofrequency signal in the N+1th frame to obtain weighted moduli |Y|w of the received response radiofrequency signal for the N+1th frame.

2. An interrogation device for interrogating an acoustic wave sensor, comprising: a transmission antenna configured for transmitting an interrogation radiofrequency signal to the acoustic wave sensor device; a reception antenna configured for receiving a response radiofrequency signal from the acoustic wave sensor device; and a processing means configured for: determining in-phase components I and quadrature components Q of the received response radiofrequency signal in each of N consecutive frames of the response radiofrequency signal, N being an integer larger than 1, wherein each of the N frames comprises X sampling points; determining a first I norm MI based on the determined in-phase components I; determining a first Q norm MQ based on the determined quadrature components Q; determining a first I weighting function WI based on the determined first I norm MI and the determined in-phase components I; determining a first Q weighting function WQ based on the determined first Q norm MQ and the determined quadrature components Q; determining the in-phase components I and the quadrature components Q of an N+1th frame of the received response radiofrequency signal, the N+1th frame comprising X sampling points of the received response radiofrequency signal; applying the first I weighting function WI to the determined in-phase components I of the received response radiofrequency signal in the N+1th frame to obtain weighted in-phase components Iw of the received response radiofrequency signal for the N+1th frame; and applying the first Q weighting function WQ to the determined quadrature components Q of the received response radiofrequency signal in the N+1th frame to obtain weighted quadrature components Qw of the received response radiofrequency signal for the N+1th frame.

3. The interrogation device of claim 1, wherein the processing means is further configured for: determining the in-phase components I and the quadrature components Q of the received response radiofrequency signal in an N+2th frame of the response radiofrequency signal, the N+2th frame comprising X sampling points of the received response radiofrequency signal; determining the moduli |Y| of each of the pairs of the determined in-phase components I and the quadrature components Q of the N+2th frame; determining a second norm M based on the determined moduli |Y| of the 2nd to N+1th frame without using the determined moduli |Y| of the 1st frame of the N frames; determining a second weighting function W based on the determined second norm M and the determined moduli |Y| of the 2nd to N+1th frame without using the determined moduli |Y| of the 1st frame of the N frames; and applying the second weighting function W to the determined moduli |Y| of the received response radiofrequency signal in the N+2th frame to obtain weighted moduli |Y|w of the received response radiofrequency signal for the N+2th frame.

4. The interrogation device of claim 2, wherein the processing means is further configured for: determining the in-phase components I and the quadrature components Q of the received response radiofrequency signal in an N+2th frame of the response radiofrequency signal, the N+2th frame comprising X sampling points of the received response radiofrequency signal; determining a second I norm MI based on the determined in-phase components I of the 2nd to N+2th frame without using the determined in-phase components I of the 1st frame of the N frames; determining a second Q norm MQ based on the determined quadrature components Q of the 2nd to N+2th frame without using the determined quadrature components Q of the 1st frame of the N frames; determining a second I weighting function WI based on the determined second I norm MI and the determined in-phase components I of the 2nd to N+2th frame without using the determined in-phase components I of the 1st frame of the N frames; determining a second Q weighting function WQ based on the determined second Q norm M and the determined quadrature components Q of the 2nd to N+2th frame without using the determined quadrature components Q of the 1st frame of the N frames; applying the second I weighting function WI to the determined in-phase components I of the received response radiofrequency signal in the N+2th frame to obtain weighted in-phase components Iw of the received response radiofrequency signal for the N+2th frame; and applying the second Q weighting function WQ to the determined quadrature components Q of the received response radiofrequency signal in the N+2th frame to obtain weighted quadrature components Qw of the received response radiofrequency signal for the N+2th frame.

5. The interrogation device of claim 1, wherein the processing means is configured to determine the first norm M according to the equation $=\underset{n=1}{\overset{N}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{.Math.Y_n\left({\omega }_x\right).Math.}{\mathrm{NX}}$ wherein |Yn(ωx)| denotes the modulus of the in-phase components I and quadrature components Q for the x-th sampling point and the n-th frame.

6. The interrogation device of claim 5, wherein the processing means is configured to determine the first weighting function according to the equation $W\left({\omega }_x\right)=\underset{n=1}{\overset{N}{.Math.}}{Y}_n\left({\omega }_n\right)$

7. The interrogation device of claim 1, wherein the processing means is further configured for applying a Gaussian density function to the obtained weighted moduli |Y|w.

8. The interrogation device of claim 4, wherein the processing means is configured to determine the first I norm MI according to the equation $M^I=\underset{n=1}{\overset{N}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{I_n\left({\omega }_x\right)}{\mathrm{NX}}$ wherein In(ωx) denotes the in-phase component for the x-th sampling point and the n-th frame and to determine the first Q norm MQ according to the equation $M^Q=\underset{n=1}{\overset{N}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{Q_n\left({\omega }_x\right)}{\mathrm{NX}}$ wherein Qn(ωx) denotes the quadrature component for the x-th sampling point and the n-th frame.

9. The interrogation device of claim 8, wherein the processing means is configured to determine the first I weighting function WI according to the equation $W^I\left({\omega }_x\right)=\underset{n=1}{\overset{N}{.Math.}}\frac{I_n\left({\omega }_n\right)}{{\mathrm{NM}}^I}$ and the first Q weighting function WQ according to the equation $W^Q\left({\omega }_x\right)=\underset{n=1}{\overset{N}{.Math.}}\frac{Q_n\left({\omega }_n\right)}{{\mathrm{NM}}^Q}$

10. The interrogation device of claim 4, wherein the processing means is further configured for: calculating weighted moduli |Y|w for the obtained weighted in-phase components Iw of the received response radiofrequency signal for the N+1th frame and the obtained weighted quadrature components Qw of the received response radiofrequency signal for the N+1th frame and applying a Gaussian density function to the calculated weighted moduli |Y|w.

11. The interrogation device of claim 1, further comprising a filter configured for filtering the received response radiofrequency signal before determining either the first norm M or the first I norm MI and first Q norm MQ to eliminate such frames of the N frames that show variances or standard deviations in the in-phase components I and the quadrature components Q over the respective entire frame that exceed a predetermined variance or standard deviation threshold.

12. The interrogation device of claim 11, wherein the filter is configured to dynamically determine the variance or standard deviations or the corresponding threshold by determining an initial threshold as the variance or standard deviation of the in-phase components I and the quadrature components Q in a particular one of the N frames and determine the threshold as the variance or standard deviations of the in-phase components I and the quadrature components Q in a frame directly following the particular frame if it is smaller than the variance or standard deviation in the particular frame.

13. A system for monitoring an ambient parameter, comprising: an interrogation device according to claim 1; and an acoustic wave sensor device communicatively coupled to the interrogation device.

14. The system of claim 13, wherein the acoustic wave sensor device comprises a passive surface acoustic wave sensor device.

15. The system of claim 13, wherein the ambient parameter comprises at least one parameter selected from among a temperature, a strain, a pressure, or a torque.

16. The interrogation device of claim 2, wherein the processing means is configured to determine the first I norm MI according to the equation $M^I=\underset{n=1}{\overset{N}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{I_n\left({\omega }_x\right)}{\mathrm{NX}}$ wherein In(ωx) denotes the in-phase component for the x-th sampling point and the n-th frame and to determine the first Q norm MQ according to the equation $M^Q=\underset{n=1}{\overset{N}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{Q_n\left({\omega }_x\right)}{\mathrm{NX}}$ wherein Qn(ωx) denotes the quadrature component for the x-th sampling point and the n-th frame.

17. The interrogation device of claim 16, wherein the processing means is configured to determine the first I weighting function WI according to the equation $W^I\left({\omega }_x\right)=\underset{n=1}{\overset{N}{.Math.}}\frac{I_n\left({\omega }_n\right)}{{\mathrm{NM}}^I}$ and the first Q weighting function WQ according to the equation $W^Q\left({\omega }_x\right)=\underset{n=1}{\overset{N}{.Math.}}\frac{Q_n\left({\omega }_n\right)}{{\mathrm{NM}}^Q}$

18. The interrogation device of claim 2, wherein the processing means is further configured for: calculating weighted moduli |Y|w for the obtained weighted in-phase components Iw of the received response radiofrequency signal for the N+1th frame and the obtained weighted quadrature components Qw of the received response radiofrequency signal for the N+1th frame and applying a Gaussian density function to the calculated weighted moduli |Y|w.

19. The interrogation device of claim 2, further comprising a filter configured for filtering the received response radiofrequency signal before determining either the first norm M or the first I norm MI and first Q norm MQ to eliminate such frames of the N frames that show variances or standard deviations in the in-phase components I and the quadrature components Q over the respective entire frame that exceed a predetermined variance or standard deviation threshold.

20. The interrogation device of claim 19, wherein the filter is configured to dynamically determine the variance or standard deviations or the corresponding threshold by determining an initial threshold as the variance or standard deviation of the in-phase components I and the quadrature components Q in a particular one of the N frames and determine the threshold as the variance or standard deviations of the in-phase components I and the quadrature components Q in a frame directly following the particular frame if it is smaller than the variance or standard deviation in the particular frame.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Additional features and advantages of the present disclosure will be described with reference to the drawings. In the description, reference is made to the accompanying figures that are meant to illustrate preferred embodiments of the present disclosure. It is understood that such embodiments do not represent the full scope of the present disclosure.

[0029] FIG. 1 represents a system comprising an acoustic wave sensor and an interrogation device wherein the present disclosure according to an embodiment can be implemented.

[0030] FIG. 2 represents a flow diagram illustrating the processing of a received response radiofrequency signal according to an embodiment of the present disclosure.

[0031] FIG. 3 represents the effect of the processing of a received response radiofrequency signal according to an embodiment of the present disclosure on the signal quality of the obtained signal.

DETAILED DESCRIPTION

[0032] The present disclosure provides techniques for the remote interrogation of passive acoustic wave sensors, in particular, SAW sensors, wherein the techniques are characterized by a high signal-to-noise ratio. The techniques can be applied to any interrogators that are configured to determine a response spectrum from an interrogated acoustic wave sensor. The interrogated acoustic wave sensor can, for example, be a resonator device, for example, a differential SAW sensor. FIG. 1 illustrates an exemplary relatively simple system (i.e., a resonator exhibiting several modes that satisfy the cavity resonance conditions), wherein an embodiment of the present disclosure can be implemented. It goes without saying that the present disclosure can be implemented in any devices employing acoustic wave sensors or dielectric resonators, RLC circuits, etc. Interrogation devices used can include any reader operating with an IQ-detector in a network analyzer signal acquisition/processing mode, for example.

[0033] The system shown in FIG. 1 comprises a resonator 1, an acoustic wave (SAW) sensor device 10 comprising an antenna 11 for receiving an interrogation radiofrequency signal and transmitting a response radiofrequency signal, a comb transducer 12 connected to the antenna 11 and comprising interdigitated electrodes and a SAW resonance cavity 13 comprising two series of reflectors. The acoustic wave sensor device 10 may comprise a SAW-based sensor built on single-crystal piezoelectric materials like quartz (SiO.sub.2), lithium niobate (LiNbO.sub.3), lithium tantalate (LiTaO.sub.3), langasite (LGS) or poly-crystal piezoelectric materials like aluminum nitride (AlN) or zinc oxide (ZnO), in particular, deposited on silicon, or even on a Piezo-On-Insulator (POI) composite material comprising a layer of piezoelectric material, in particular, a single-crystal material, such as, for example, lithium tantalate or lithium niobate, bonded to a support substrate as, for instance, silicon, if necessary by way of a bonding layer, as, for instance, a silicon oxide layer. The transducer 12 converts the interrogation radiofrequency signal received by the antenna 11 into an acoustic wave that is reflected back by the reflectors of the resonance cavity 13 and converted back into a radiofrequency signal that in course is transmitted by the antenna 11 as a response radiofrequency signal.

[0034] The system further comprises an interrogation device 20 comprising a transmission antenna 21 for transmitting an interrogation radiofrequency signal to the acoustic wave (SAW) sensor device 10 and a reception antenna 22 for receiving a response radiofrequency signal from the acoustic wave (SAW) sensor device 10. The interrogation radiofrequency signal transmitted by the transmission antenna 21 is generated by a signal generator 23 that may comprise a radiofrequency synthesizer or oscillator as well as optionally some signal shaping module providing a suitable frequency transposition and/or amplification of the signal to be transmitted by the transmission antenna 21. The interrogation radiofrequency signal generated by the signal generator 23 may be a pulsed or bursty signal with a frequency selected according to the resonance frequency of the acoustic wave sensor device 10.

[0035] Furthermore, the interrogation device 20 comprises a processing means 24 connected to the reception antenna 22. The processing means 24 may comprise filtering and/or amplification means and be configured for analyzing the response radiofrequency signal received by the reception antenna 22. For example, the acoustic wave sensor device 10 operates at a resonance frequency of 434 MHz or 2.45 GHz. The interrogation device 20 may transmit a long radiofrequency pulse and after the transmission has been stopped, the resonance cavity 13 discharges at its resonant eigenfrequency with a time constant τ equal to Qf/πF wherein F is the central frequency and Qf is the quality factor Qf corresponding to the ratio between the central frequency and the width at half maximum of the band pass used in the interrogation process. Spectral analysis performed by the processing means 24 of the interrogation device 20 allows for calculating the resonator frequency and, thereby, the sensing of an ambient parameter. The received response radiofrequency signal may be mixed by the processing means with interrogation radiofrequency signal according to the so-called I-Q protocol as known in the art to extract the real and imaginary parts (in-phase I and quadrature Q) from which the modulus and phase can then be derived.

[0036] According to the present disclosure, processing of the received response radiofrequency signal by means of a norm and a weighting function is performed in order to increase the signal-to-noise ratio. The processing can, in principle, be performed at least partly in the time domain or the frequency (spectral) domain. For exemplary purposes, in the following, processing in the spectral domain will be considered. FIG. 2 shows a flow diagram illustrating the processing according to an embodiment of the present disclosure, for example, a kind of processing that can be performed by the processing means 24 of the interrogation device 20 shown in FIG. 1.

[0037] At a first step in the procedure, an interrogation radiofrequency signal is transmitted 101 by an interrogation device, for example, the interrogation device 20 shown in FIG. 1, to an acoustic wave sensor device, for example, the acoustic wave sensor device 10 shown in FIG. 1. The interrogation device receives a response radiofrequency signal 102. The received response radiofrequency signal is processed/analyzed by the interrogation device, for example, the processing means 24 of the interrogation device 20 shown in FIG. 1.

[0038] In particular, the in-phase components I and the quadrature components Q of the received response radiofrequency signal in each of N consecutive frames (1, . . . , N) of the response radiofrequency signal, N being an integer larger than 1, wherein each of the N frames comprises X sampling (frequency) points, are determined 103, for example, by employing an I-Q protocol. For example, X may lie in a range of 100 to 1000 and N may lie in a range of 20 to 100.

[0039] Based on the determined in-phase components I and the quadrature components Q, a norm is determined 104. According to a particular embodiment, the moduli

[00009]$\begin{array}{cc}.Math.Y.Math.=\sqrt{I^2+Q^2}& \left[\mathrm{Equation}9\right]\end{array}$

for the pairs of the determined in-phase components I and the quadrature components Q of the N frames of the received response radiofrequency signal are calculated. A first norm is calculated 104 according to the equation

[00010]$\begin{array}{cc}M=\underset{n=1}{\overset{N}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{.Math.Y_n\left({\omega }_x\right).Math.}{\mathrm{NX}}& \left[\mathrm{Equation}10\right]\end{array}$

wherein |Yn(ωx)| denotes the modulus of the in-phase components I and quadrature components Q for the x-th sampling point and the n-th frame.

[0040] Based on the first norm a first weighting function,

[00011]$\begin{array}{cc}W\left({\omega }_x\right)=\underset{n=1}{\overset{N}{.Math.}}{Y}_n\left({\omega }_n\right)& \left[\mathrm{Equation}11\right]\end{array}$

is calculated 105. This weighting function is applied 106 to an N+1th frame (also comprising X sampling points) of the received response radiofrequency signal that may follow directly the Nth frame (for the matter of understanding function means that there is not a unique or single value that is applied to the data series of the N+1th frame but that the weighting depends on the recorded signals at each sampling point, the weighting operation thereby achieved by multiplication of the weighting at each sampling point with the value of that sampling point in the N+1th frame). The in-phase components I and the quadrature components Q of the N+1th frame of the received response radiofrequency signal are determined and the moduli |Y| of each of the pairs of the determined in-phase components I and the quadrature components Q of the N+1th frame are determined. The weighting function is applied to the moduli in order to obtain weighted moduli showing a superior signal-to-noise ratio. From the weighted moduli a resonance frequency may be determined by fitting the data to an appropriate fitting function, in particular a Gaussian fitting as described in more detail below, and based on the determined resonance frequency, an ambient parameter can be monitored.

[0041] The above-described procedure according to this embodiment is recursively carried out for the following frames N+2, N+3, etc., wherein in each of the recursive loops the norm (and, thus, the weighting function) is calculated neglecting the first frame used in the previous loop. So, in the next loop 107, the first (oldest) frame 1 is excised from consideration and a second (updated) norm is calculated by using the 2nd to N+1th frames:

[00012]$\begin{array}{cc}M=\underset{n=2}{\overset{N+1}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{.Math.y_n\left({\omega }_x\right).Math.}{\mathrm{NX}}& \left[\mathrm{Equation}12\right]\end{array}$

Accordingly, in the next loop 107 the (second) weighting function is given by

[00013]$\begin{array}{cc}W\left({\omega }_x\right)=\underset{n=2}{\overset{N+1}{.Math.}}{Y}_n\left({\omega }_n\right)& \left[\mathrm{Equation}13\right]\end{array}$

and it is to be applied to the N+2th frame, etc.

[0042] FIG. 3 illustrates the effect of such a kind of processing with respect to an enhanced signal-to-noise ratio. FIG. 3 shows raw data of the I and Q components and the modulus (graph a) obtained for the raw data. In comparison, graph b in FIG. 3 shows the obtained weighted modulus obtained by the above-described procedure. As illustrated in FIG. 3 the signal-to-noise ratio can be increased by one order of magnitude in this example.

[0043] Whereas, in the above-described embodiment, a norm and a weighting function are determined and applied on moduli of the I and Q components, alternatively, norms and weighting functions can be determined for the I and Q components, separately, and the thus obtained weighting functions can be applied to the I and Q components of the respective following frame. According to this alternative, a first I norm MI according to the equation

[00014]$\begin{array}{cc}{M}^I=\underset{n=1}{\overset{N}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{I_n\left({\omega }_x\right)}{\mathrm{NX}}& \left[\mathrm{Equation}14\right]\end{array}$

is calculated wherein In(ωx) denotes the in-phase component for the x-th sampling point and the n-th frame and a first Q norm MQ is calculated according to the equation

[00015]$\begin{array}{cc}{M}^Q=\underset{n=1}{\overset{N}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{Q_n\left({\omega }_x\right)}{\mathrm{NX}}& \left[\mathrm{Equation}15\right]\end{array}$

wherein Qn(ωx) denotes the quadrature component for the x-th sampling point and the n-th frame.

[0044] Accordingly, a first I weighting function WI is calculated according to the equation

[00016]$\begin{array}{cc}{W}^I\left({\omega }_x\right)=\underset{n=1}{\overset{N}{.Math.}}\frac{I_n\left({\omega }_n\right)}{{\mathrm{NM}}^I}& \left[\mathrm{Equation}16\right]\end{array}$

and a first Q weighting function WQ is calculated according to the equation

[00017]$\begin{array}{cc}{W}^Q\left({\omega }_x\right)=\underset{n=1}{\overset{N}{.Math.}}\frac{Q_n\left({\omega }_n\right)}{{\mathrm{NM}}^Q}& \left[\mathrm{Equation}17\right]\end{array}$

[0045] The first I weighting function WI is then applied to the I components of the N+1th frame and the first Q weighting function WQ is applied to the Q components of the N+1th frame. Correspondingly, a second I norm MI and a second Q norm MQ are calculated

[00018]$\begin{array}{cc}{M}^I=\underset{n=2}{\overset{N+1}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{I_n\left({\omega }_x\right)}{\mathrm{NX}};M^Q=\underset{n=2}{\overset{N+1}{.Math.}}\underset{x=1}{\overset{X}{.Math.}}\frac{Q_n\left({\omega }_x\right)}{\mathrm{NX}}& \left[\mathrm{Equation}18\right]\end{array}$

in order to determine a second I weighting function WI as well as a second Q weighting function WQ

[00019]$\begin{array}{cc}{W}^I\left({\omega }_x\right)=\underset{n=2}{\overset{N+1}{.Math.}}\frac{I_n\left({\omega }_n\right)}{{\mathrm{NM}}^I};W^Q\left({\omega }_x\right)=\underset{n=2}{\overset{N+1}{.Math.}}\frac{Q_n\left({\omega }_n\right)}{{\mathrm{NM}}^Q}& \left[\mathrm{Equation}19\right]\end{array}$

that are to be applied to the I and Q components, respectively, of the N+1th frame, in order to obtain weighted I and Q components. Weighted moduli can be readily calculated from the weighted I and Q components. Further recursive loops (for the N+2th frame, N+3th frame etc.) follow in a straightforward manner (each loop neglecting the respective first frame of the previous loop).

[0046] According to particular embodiments, step 104 of the flow diagram of FIG. 2 is preceded by a step of pre-filtering in order to eliminate defective frames. In fact, frames of the N frames that show a variance in the in-phase components I and the quadrature components Q over the respective entire frame that exceed a predetermined variance threshold can be eliminated. The thresholding can be adaptive. For example, the variance threshold may be dynamically determined by setting an initial threshold as the variance of the in-phase components I and the quadrature components Q in a particular one of the N frames and determining the threshold as the variance of the in-phase components I and the quadrature components Q in a frame directly following the particular frame if it is smaller than the variance in the particular frame or, else, maintaining the initial threshold. This process can be recursively performed for the following frames, i.e., for the following frames, again, the variances of the in-phase components I and the quadrature components Q over the respective entire frames are calculated and, if the variances for the following frames are decreasing, the threshold value will be updated by the variances of the following frames. When a variance of a following frame is larger than the one of the previous frame the variance of the previous frame is used as the threshold value.

[0047] Furthermore, a Gaussian density function ˜exp(−0.5 (|b−x|/c)2), with x denoting the time or frequency variable, c denoting the variance and b denoting the maximum of x, can be applied to the resulting weighted moduli in both alternative approaches described above. Thereby, the resonance frequency of a resonator device as the one illustrated in FIG. 1 can be reliably extracted, for example. Fitting the processed signal with such a density function yields direct access to the resonance frequency corresponding to the variable b.

[0048] Any smoothing of data in the context of some post-processing as needed in the art is no longer necessary due to the obtained high signal-to-noise ratio. Particularly, any signal components exhibiting amplitudes close to the noise level can reliably be minimized or even eliminated.

[0049] By means of the herein disclosed techniques an ambient parameter can be sensed using an acoustic wave sensor device and an interrogation device interrogating the acoustic wave sensor wherein by employing a norm and a weighting function an enhanced signal-to-noise ratio can be achieved. Particularly, the stability of the measurement of an ambient parameter as, for example, a temperature, strain, pressure or torque of a rotating axis, allows for a robust and reliable monitoring.

[0050] All previously discussed embodiments are not intended as limitations but serve as examples illustrating features and advantages of the present disclosure. It is to be understood that some or all of the above described features can also be combined in different ways.