Our whole projects relies around three core characteristics: our sampling frequency, the speed of sound in a given medium and the distance between our sensors. In our original proof of concept we provided an ideal testing scenario. Our sensors were almost a meter apart, sampled at 96Kps and tested in open air, quiet room. Based on the paper Implementing a Microphone Array on a Mobile Robotic Device by Brian Blosser and Matt Meshulam, a good benchmark for the number of potential angles (T) that the sensor array can receive is T=(d*Fs)/s where d is the distance between sensors, Fs is the sampling frequency and s is the speed of sound in a medium. Based on our original proof of concept where d=0.9m, Fs = 96KHz, and s = 343m/s the number of potential angles between 0 and 90 degrees is 252 distinct angles. For our benefit, that means we could project the angle down to a specificity as high as 0.358 degrees.
However, if we were to take the current testing array for the boat application, many of the characteristics of sensor arra change. For one, due to the limited width of the hull of 40cm, our d value becomes 0.1m. Subsequently, the speed of sound in water is substantially faster than that of the speed of sound in air. This changes based on a number of factors including senility and senility, but for the purposes of rough calculations, our s value increases from 343m/s to 1500m/s. Assuming the same sampling frequency, our number of potential distinct angles decreases to only 6.4. As a result, our maximum potential specificity decreases from 0.358 degrees to 14.0625 degrees increments. While this could be acceptable for determining one of three docking locations across a field of view as high as 120 degrees, we face another unforeseen issue.
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For our original testing set up, we used 3 standard sound cards sampling at 96Ksp. In addition, the "signal" we used was that of a clapping hand. Two glaring errors are present with this set up. The first, is that the sound of hands clapping includes a large number of frequencies that are audible by the human ear. Today, the vast majority of sound cards are designed for the processing of audio signals audible to humans. This range typically falls between 20Hz and 20KHz. However, our ultimate goal is to detect the ultrasonic pulse emitted by a black box. The range of this signal is between 20KHz and 45KHz. While the hydrophones we are using can detect up to 100KHz, the sound card remains an issue.
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Looking Ahead
Looking ahead to the next three weeks there are a few tasks at head. We are going to need to increase our sampling rate, and increase our ability to listen to higher frequencies. While we can get access to a sound card that can sample at 192Kps that would increase our specificity to 7.03 degrees per measurement, this does not allow us to detect higher frequencies. After a conversation with Professor Achilles,our steps moving forward are clearer. The first is the ability to utilize existing sound cards, it is the expectation of Professor Achilles that the sound cards are filtered within their hardware to listen to frequencies below 20KHz and as a result, cannot be retrofit for our purpose. However, there are several professors at Michigan that design systems to listen at these frequencies that may be able to help us. Alternatively, there may be a way to modulate the pinger frequencies to a lower frequencies audible to our sound card. Lastly, there exist several off the shelf solutions designed for listening to dolphins or bats that can process higher frequencies that could be retrofit for our purposes. However, more research is still needed on the viability of those options. In the meantime, our best course of action is to continue to test in open air in order to develop our system.
Moreover, another task we'll need to achieve is being able the measure the angle and range in the air. Despite the fact that for now our current course is to test in the open air, another necessary task is to obtain water data so we can determine the feasibility of designing our system.