Nonlinearity assessment of MIMO electroacoustic systems on Direct Field Environmental Acoustic Testing

Direct Field Environmental Acoustic testing consists in reproducing the sound field inside a spacecraft vehicle's fairing using an array of loudspeakers. In order to ensure the accurate reproduction of the sound pressure field, the actuators need to be actively controlled. The performance of state-of-the-art Multiple-Input Multiple-Output (MIMO) random controllers is strongly dependent on the control strategy. The system identification, methodology applied at low power level excitation before the test, is one of the most sensitive aspects of such strategy. This is because it provides a linear nonparametric model of the electroacoustic system, which is used to design the signals to drive the loudspeakers. In this work novel system identification strategy is explored. The proposed method is a MIMO Best Linear Approximation (BLA). In this technique, instead of using classical excitation signals and the H1 estimate, a BLA model is estimated, and the coherence function is split into noise level and nonlinear contribution estimates.