- Fig. 1 – X-WALD radar prototype mounted in the nose of the aircraft
- Fig. 2 – Airplane trajectory toward the phenomenon as seen from the ground weather radar
- Fig. 3 – Range Doppler maps for the four polarimetric channel received by the radar. Note the strongest power in the co-polar channels
- Fig. 4 – Processing of the radar data to obtain polarimetric observables, compared with the output of the radar simulator, with mesoscale data initialization
Current commercial avionic radars mainly operate in single polarization even if there exist few experimental avionic polarimetric radars, mainly used for testing and measurement. It is obvious that the cost of avionic polarimetric radars is higher than that of single polarization ones, therefore the advantages in terms of weather classification and its use for trajectory optimization must be quantitatively demonstrated in order to show the significant gain. The development of new signal processing and trajectory optimization algorithms done within the framework of JU-SGO aimed at this purpose. In these programmes, an avionic polarimetric signal simulator, was developed so to have synthetic data on which the processing and trajectory optimization algorithms implemented on an Electronic Flight Bag (EFB) could be tested. The main limitation of this approach is related to the certainness of the reliability of such a simulator, whose performance clearly affects the algorithm behaviour. Moreover, for the algorithm testing point of view, the use of simulated data is always a limitation for the analysis goodness and for its behaviour when implemented on EFB.
The progress beyond the state of the art given by X-WALD project is:
1) Selection and/or update of an existing polarimetric radar to be installed on an airborne platform robust enough to be able to gather measurements during adverse weather events in compliance with the cases of the JU-SGO program.
2) Organization of a measurement campaign to obtain real data, which will be used for the algorithm performance analysis as well as to assess the reliability of the signal simulator.
3) Execution of an extensive validation campaign of the algorithms running in the customized EFB of the KLEAN project and of the reliability analysis of the signal simulator through the use of the observed real data.
4) Use of ancillary data coming from auxiliary sensors (polarimetric ground radar and meteorological sensor) to crosscheck the outcomes of the data analysis with in-situ measurements.