## 6 Simulation and Measurement Comparisons  
To fully compare the simulation and measurement results, it is necessary to correct for the varying receiver antenna gain along the flight path. The required correction is computed from the antenna pattern, and its value is shown along the flight path in Figure 21. For our comparison, we apply this weighting to the simulated received-power values. Time-series comparisons between the simulated and measured received-power values are shown in Figure 22a for the MoM simulations and Figure 22b for the full SBR+ simulations. Since absolute received-power values are not available from the radar system, we apply an estimated correction to the measured values determined from the mean of the difference between the simulated and measured received-power values for all cases where measured received-power values are available. This means that the comparison is restricted to variations in the received power and not the absolute received-power values. The offsets are applied to the measured data and are given in the figure legends. Figure 20: Comparison between monostatic RCS measurements of a copper scale model of the PC-12 and SBR+ simulations. MoM simulations were performed at a smaller number of incidence angles using the MoM solver, and they show similar agreement (not shown). RCS is relative to the peak measured RCS. The confidence intervals are estimated from the fractional difference between the highest quality MoM estimation and the MoM/SBR+ estimations used, relative to the MoM/SBR+ estimation used. Since the errors are generally not symmetric around the MoM/SBR+ estimations used, we consider over- and under-estimation separately. We used the 90 th percentile of the error as our estimation for the error in each component. This is inherently quite impse, owing to the small number of data points available, but it provides an approximate guide to where the measured signal is plausibly expected to be. From the error analysis in Section 4, the dominant error sources are the azimuthal angle variation with integration time, the five-frequency approximation, the IMU attitude data and the simplifications in the model. The two-sided integration time-fractional RCS errors are +0.46, \(-0.10\) for an azimuth variation of \(0.12^{\circ}\). The two-sided frequency errors are +0.10, \(-0.061\). Estimates are from the SBR+ solver. It is likely that this is a slight over-estimation for the MoM solver, but since the equivalent MoM simulations would be too time-consuming to perform, we work with the SBR values. The two-sided IMU position errors are +1.97, \(-0.40\). Finally, the two-sided model errors for MoM are +0.28, \(-0.1\), and for the full SBR+ simulations, they are +2.44, \(-0.63\) (determined from the comparison between the basic MoM and the full SBR+ simulations, since the larger number of data points makes the estimate more robust). The combined fractional errors are therefore \(+2.04/-0.43\) for the MoM solutions, and \(+3.17/-0.76\) for the full SBR+ solutions. From these figures, it appears that there are some areas where the characteristics of the curves in the simulated and measured received values broadly agree in terms of the locations and relative amplitudes of peaks and troughs. However, there are other areas where this is clearly not the case. The simulations do, however, show some predictive power in being able to show where the aircraft cannot be detected in measurement: specifically when the aircraft is rolling, the simulated received-power values are particularly low, and the aircraft fails to be detected in measurement. This can be seen more clearly in Figure 23 where we show histograms of the received power for both the detection and no-detection cases. Figure 21: The variation of relative receiver antenna gain along the flight path, alongside the transmitter and receiver locations. Note that there is a significant reduction in receiver gain around where the aircraft turns.