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For this block of labs, you will be evaluating a proposed SONAR system consisting of a signal generator, power amplifier, and speaker to provide an audio signal and a microphone attached to a boom with encoders to track its location to measure the signal reflection off of objects. A custom LabVIEW VI will be used to analyze the input and recorded signals. Last week you focused on characterizing the system capabilities including measuring the speed of sound, distance precision, and directionality. This week you will use the system to analyze and process signals recorded from reflected waves off a target object, determine its position, and characterize the precision of the calculated position.
The raw signal collected during the SONAR experiments will have all the ambient noise within the operating range of the microphone making identifying the reflection off the target object difficult. Signal processing can help increase the signal to noise ratio so that key features such as when the acoustic wave passes by the microphone before and after reflection off the target can be identified (Figure 1). Averaging multiple signals (one of the settings in the VI) will cancel most of the ambient noise, however this will not eliminate all the extraneous data such as amplifier or speaker system dynamics or reflections from objects not of interest. Furthermore, since the sound pressure level decreases with distance, the magnitude of the reflected wave from the target object may be much smaller than that of the extraneous noise. An example of this is shown in Figure 2, where the wave initially passing the microphone is clearly visible but there are other features in the signal which could possibly be the target object reflection. Additional signal processing is required to positively identify the target object.