A Subspace based Algorithm to Enhance the SNR of Active Sonar Audio Time Series

In a sonar system, the audio time series is an important tool for the sonar operator to validate and classify the target identified from the sonar display. The audio time series is also useful to confirm the target in the presence of reverberation. The beam time series is given as the input to the audio streamer. Comparing with the sensor level signal, the audio time series has an SNR (signal to noise ratio) improvement due to the directivity index (DI) of the beamforming. The beam time series is further processed using the matched filter and the normalized detector output is shown in the sonar display. Hence, the detector output in the sonar display has the gain of beamformer as well as matched filtering. However, the SNR of the audio time series is not enhanced by the detector gain. Hence in a scenario with weak SNR target, the target can be identified in the sonar display and the operator fails to confirm the target in the sonar audio. We introduce a subspace based algorithm to enhance the SNR of the sonar audio signal. The simulation as well as experimental results establish the superior performance of the proposed algorithm to improve the SNR of the audio time series significantly.