Two experiments were conducted to investigate Adaptive Noise Cancelling and Cepstrum echo removal post-processing techniques on acoustic data from a linear microphone array in an anechoic chamber. A point source speaker driven with white noise was used as the primary signal. The first experiment included a background speaker to provide interference noise at three different Signal-to-Noise Ratios to simulate noise propagating down a wind tunnel circuit. The second experiment contained only the primary source and the wedges were removed from the floor to simulate reflections found in a wind tunnel environment. The techniques were applicable to both signal microphone and array analysis. The Adaptive Noise Cancellation proved successful in its task of removing the background noise from the microphone signals at SNRs as low as -20 dB. The recovered signals were then used for array processing. A simulation reflection case was analyzed with the Cepstral technique. Accurate removal of the reflection effects was achieved in recovering both magnitude and phase of the direct signal. Experimental data resulted in Cepstral features that caused errors in phase accuracy. A simple phase correction procedure was proposed for this data, but in general it appears that the Cepstral technique is and would be not well suited for all experimental data. / Master of Science

<p>Two methods for evaluating and improving plane wave beamforming have beendeveloped. The methods estimate the shape of the wavefront and use theinformation in the beamforming. One of the methods uses estimates of the timedelays between the sensors to approximate the shape of the wavefront, and theother estimates the wavefront by matching the received wavefront to sphericalwavefronts of different radii. The methods are compared to a third more commonmethod of beamforming, which assumes that the impinging wave is planar. Themethods’ passive ranging abilities are also evaluated, and compared to a referencemethod based on triangulation.Both methods were evaluated with both real and simulated data. The simulateddata was obtained using Raylab, which is a simulation program based on ray-tracing. The real data was obtained through a field-test performed in the Balticsea using a towed array sonar and a stationary source emitted tones.The performance of the matched beamformers depends on the distance to the tar-get. At a distance of 600 m near broadside the power received by the beamformerincreases by 0.5-1 dB compared to the plane wave beamformer. At a distance of300 m near broadside the improvement is approximately 2 dB. In general, obtain-ing an accurate distance estimation proved to be difficult, and highly dependenton the noise present in the environment. A moving target at a distance of 600 mat broadside can be estimated with a maximum error of 150 m, when recursiveupdating of the covariance matrix with a updating constant of 0.25 is used. Whenrecursive updating is not used the margin of error increases to 400 m.</p>

Two methods for evaluating and improving plane wave beamforming have beendeveloped. The methods estimate the shape of the wavefront and use theinformation in the beamforming. One of the methods uses estimates of the timedelays between the sensors to approximate the shape of the wavefront, and theother estimates the wavefront by matching the received wavefront to sphericalwavefronts of different radii. The methods are compared to a third more commonmethod of beamforming, which assumes that the impinging wave is planar. Themethods’ passive ranging abilities are also evaluated, and compared to a referencemethod based on triangulation.Both methods were evaluated with both real and simulated data. The simulateddata was obtained using Raylab, which is a simulation program based on ray-tracing. The real data was obtained through a field-test performed in the Balticsea using a towed array sonar and a stationary source emitted tones.The performance of the matched beamformers depends on the distance to the tar-get. At a distance of 600 m near broadside the power received by the beamformerincreases by 0.5-1 dB compared to the plane wave beamformer. At a distance of300 m near broadside the improvement is approximately 2 dB. In general, obtain-ing an accurate distance estimation proved to be difficult, and highly dependenton the noise present in the environment. A moving target at a distance of 600 mat broadside can be estimated with a maximum error of 150 m, when recursiveupdating of the covariance matrix with a updating constant of 0.25 is used. Whenrecursive updating is not used the margin of error increases to 400 m.

An aeroacoustic study was conducted on a 26%-scale Boeing 777 main landing gear in the Virginia Tech (VT) Anechoic Stability Wind Tunnel. The VT Anechoic Stability Wind Tunnel allowed noise measurements to be carried out using both a 63-elements microphone phased array and a linear array of 15 microphones. The noise sources were identified from the flyover view under various flow speeds and the phased array positioned in both the near and far-field. The directivity pattern of the landing gear was determined using the linear array of microphones. The effectiveness of 4 passive noise control devices was evaluated. The 26%-scale model tested was a faithful reproduction of the full-scale landing gear and included most of the full-scale details with accuracy down to 3 mm. The same landing gear model was previously tested in the original hard-walled configuration of the VT tunnel with the same phased array mounted on the wall of the test section, i.e. near-field position. Thus, the new anechoic configuration of the VT wind tunnel offered a unique opportunity to directly compare, using the same gear model and phased array instrumentation, data collected in hard-walled and semi-anechoic test sections. The main objectives of the present work were (i) to evaluate the validity of conducting aeroacoustic studies in non-acoustically treated, hard-walled wind tunnels, (ii) to test the effectiveness of various streamlining devices (passive noise control) at different flyover locations, and (iii) to assess if phased array measurements can be used to estimate noise reduction. As expected, the results from this work show that a reduction of the background noise (e.g. anechoic configuration) leads to significantly cleaner beamforming maps and allows one to locate noise sources that would not be identified otherwise. By using the integrated spectra for the baseline landing gear, it was found that in the hard-walled test section the levels of the landing gear noise were overestimated. Phased array measurements in the near and far-field positions were also compared in the anechoic configuration. The results showed that straight under the gear, near-field measurements located only the lower-truck noise sources, i.e. noise components located behind the truck were shielded. It was thus demonstrated that near-field, phased-array measurements of the landing gear noise straight under the gear are not suitable. The array was also placed in the far-field, on the rear-arc of the landing gear. From this position, other noise sources such as the strut could be identified. This result demonstrated that noise from the landing gear on the flyover path cannot be characterized by only taking phased array measurement right under the gear. The noise reduction potential of various streamlining devices was estimated from phased array measurements (by integrating the beamforming maps) and using the linear array of individually calibrated microphones. Comparison of the two approaches showed that the reductions estimated from the phased array and a single microphone were in good agreement in the far-field. However, it was found that in the near-field, straight under the gear, phased array measurements greatly overestimate the attenuation. / Master of Science