## 4 Discussion and Conclusions  
In this paper, we reviewed our recent work in References [12; 13] on exploiting MWP techniques for interrogating simultaneously multiple FBG-based sensors. We described the use of MWP filtering, whereby the RF power at specific frequencies within an MWP filter response is tracked and correlated to changes applied to the FBG-based sensors that are used in implementing the MWP filter. The approach allows the possibility to monitor changes in power at multiple frequencies, or even to use a ratiometric approach. We also demonstrated the use of FBGs to generate chirped microwave waveforms and correlated shifts in the temporal peak of the compressed pulses to changes applied to the FBGs. The examples detailed in this paper focus on temperature sensing, while the techniques are equally applicable to strain sensing. This is based on the fact that the spectral response of FBGs or linearly chirped FBGs has a well-defined shift toward longer wavelengths as a function of increasing temperature or strain. It should be noted that the approaches support high sensitivity and support high-speed operation. An important consideration of multiple sensor systems is scaling. For the technique based on MWP filtering with in-fiber FP cavities, the number of sensors that can be interrogated may be increased by tailoring the FBG separation of the sensing structures to obtain MWP filter passbands centered about different frequencies. To avoid crosstalk, it is necessary to ensure that the MWP filter responses corresponding to the sensors do not overlap. The sensitivity can be further improved by using packages of higher thermal expansion so that there are greater changes in FSR as a function of applied temperature. Increasing the optical bandwidth of the sensor results in a narrower MWP filter passband (see Figures 4 and 5), which in turn results in steeper rising and falling edges and thus, greater sensitivities. It can also reduce cross-talk between the MWP filter passbands. The system will require an optimization between the optical bandwidth corresponding to one sensor, the bandwidth of the MWP filter passband, the operating RF frequency range, and the range over which sensing is required. With reference to Figures 4 and 5, using an optical bandwidth (3 dB) of \(\sim\)0.8 nm for one in-fiber FP cavity sensor (i.e., similar to Sensor 2) will allow for \(\sim\)10 different minimally overlapping MWP filter passbands operating in the RF frequency range up to 20 GHz; thus, \(\sim\)10 sensors can be interrogated. For the Sagnac loop, increasing the number of sensors that can be interrogated will depend on the number of LCFBGs that can be superimposed (at least 10 superimposed FBGs were demonstrated in Reference [20]), the bandwidth of the BBS, as well as the number of gratings that a given LCFBG can support, which depends on the bandwidth of the sensing FBG and the wavelength range over which the sensing FBG will operate. For example, if the sensing FBGs have a 3 dB bandwidth of \(\sim\)0.3 nm and need to be tuned over \(\sim\)1 nm (e.g., for temperature sensing over 100 \({}^{\circ}\)C), an LCFBG with a bandwidth of 4.5 nm can support \(\sim\)3 sensing FBGs. Superimposing 8 such LCFBGs will result in \(\sim\)24 sensors, occupying an optical bandwidth of \(\sim\)36 nm, well within the bandwidth of available BBSs. Figure 15: Variations in correlation peak (peak of compressed pulses) for Sensor 1 and Sensor 2 as a function of temperature applied to (**a**) Sensor 1 only and (**b**) Sensor 2 only (after Reference [13]). For the technique based on generating chirped microwave waveforms, the method can be scaled to a larger number of sensors by increasing the number of channels in the AWGSI. However, scalability will be constrained by the bandwidth of the BBS. Combining multiple bands, such as S, and C, and L, can increase scalability further, but this will require an appropriate pulsed BBS, and dispersive media for WTM.