# Experimental Validation of GNSS Interferometric Radio Occultation
## 4 Data Processing, Analysis and Discussion
### Interferometric RO Processing
#### 4.3.4. Zenith iRO Processing  
In [8], an alternative approach to interferometric radio occultation is also proposed, in which the reference signal is acquired before any occultation actually happens, with the objective to increase the SNR of the occultation cross-correlation. We took the reference signal at SoD48000 when the antenna gain and the SNR were high enough and the received signal did not suffer serious interference from the sea surface reflection. The signal processing for the zenith iRO consists the following steps:  
1. **Reference signal acquisition:** A signal segment of 20 ms (\(s_{\rm r}^{\rm ref}(t)\)) was selected from the data file corresponding to SoD48000, the starting sample of \(s_{\rm r}^{\rm ref}(t)\) is aligned to the beginning of the navigation bit, which is estimated using the clean replica processing. It is worth to mention that the information on the navigation bit can be also predicted by the transmitter and receiver geometry when implemented in future space-borne interferometric receivers. 2. **Down-conversion and coherent averaging:** The selected signal segment was then down-converted to baseband by the local generated carrier with the predicted Doppler as \[s_{\rm r,BB}^{\rm ref}(t)=s_{\rm r}^{\rm ref}(t)e^{-j2\pi f_{\rm D,predict}}\] (23) Then, 20 1-ms segments (\(s_{\rm r,BB}^{\rm ref}(t_{0}+k/1000),k=0,1,\ldots 19\)) are _cropped_ from the down-converted signal and coherently averaged as \[s^{\rm ref}(t)=\sum_{k=0}^{19}s_{\rm r,BB}^{\rm ref}(t_{0}+k/1000)\] (24)
3. **Open-loop tracking with the zenith reference:** With the coherently averaged reference signal, a similar processing scheme from Section 4.2.2 is applied to the collected signal. It is noted that the initial code phase of the reference signal is also adjusted for each cross-correlation following the  
Figure 12: Relationship between the SNR and the precision of the iRO Doppler observation. predicted Doppler by shifting the reference signal accordingly. The number of samples adjusted can be computed by  
\[n_{\text{sample}}^{\text{incr}}(T)=\frac{f_{\text{D,predict}}(T)T_{i}F_{\text{s }}}{f_{\text{L1}}} \tag{25}\]  
Following the processing scheme above, the Doppler of the received signal is estimated with the zenith iRO method and presented in Figure 13 together with the one estimated through the clean replica open loop processing. In Figure 14, both Doppler observations are compared in detail for two different typical periods with high and low SNRs. It can be seen from both figures that the zenith iRO Doppler observations are almost identical compared to those estimated with the clean replica method at higher elevations, when the SNR is larger. At higher elevations the performance in terms of RMS deviation of the observables respect to the predicted Doppler is almost identical, as shown in Table 2. At lower elevations, towards the end of the experiment, appreciable minor differences between both retrievals can be appreciated (see Table 2). It is worth to note, that the RMS values have been computed taking the predicted Doppler as a reference, and that in RO geometry the purely geometric predicted Doppler does not correspond to the real Doppler, as the atmospheric effects have not been modelled. Thus, the resulting RMS values could be affected by this mismodelling. We think that both methods are comparable in performance, and that the slight differences between the noise in both methods could be attributed to the fact that the reference signal used in the cross-correlation computation is different in both approaches. In the clean-replica method the received signal is cross-correlated with an ideal model of the GNSS signal, i.e., a perfect PRN sequence. When using the Zenith iRO method the received signal is correlated with a segment of the same signal acquired at a different instant of time, and thus, it includes all nuisances introduced by the GPS transmitter and receiver, such as filtering and other non-idealities, which are also common to the occulting signal segment.