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Results and Discussion on Audio Localization

Module by: Elizabeth Gregory, Joseph Cole. E-mail the authors

Summary: In this section, we will discuss the results of both the MATLAB simulation and the DSK and the areas that need improving.

Matlab Simulation Results

In running our simulation, we discovered that while our region output was not always correct, we maintained accuracy within 22.5°. Tha algorithm seemed to have the most difficultly on the edges of the field of view. Our exact results can be found in Table 1 and Table 2.

Table 1: Without Noise
True Region True Angle Estimated Region
0 π16 16 0
1 3⁢π16 3 16 0
2 5⁢π16 5 16 2
3 7⁢π16 7 16 3
4 9⁢π16 9 16 4
5 11⁢π16 11 16 5
6 13⁢π16 13 16 6
7 15⁢π16 15 16 7
Table 2: With Noise, SNR=2
True Region True Angle Estimated Region
0 π16 16 1
1 3⁢π16 3 16 2
2 5⁢π16 5 16 2
3 7⁢π16 7 16 2
4 9⁢π16 9 16 6
5 11⁢π16 11 16 7
6 13⁢π16 13 16 6
7 15⁢π16 15 16 6

Results with the DSK

In testing our DSK algorithm, we started with the ideal signal, generated using Matlab. The results had more error than in Matlab, but seemed reasonable at the time. However, in multiple trials of the same ideal signal, the DSK responded differently each time, indicating that our algorithm still needed a bit of work.

When we tried to implement the same algorithm using a real signal, generated from a computer across the room, we received very poor results. In the end, the DSK could tell whether the signal came from the left or the right, but only when the lab was quiet and empty. Also, the program was very sensitive to alternate signal paths and the general acoustics of the room. All in all, our program was not very reliable, as shown in Table 3.

Table 3: C Results
True Region True Angle Estimated Region
0 π16 16 4
1 3⁢π16 3 16 3
2 5⁢π16 5 16 6
3 7⁢π16 7 16 3
4 9⁢π16 9 16 5
5 11⁢π16 11 16 3
6 13⁢π16 13 16 4
7 15⁢π16 15 16 6

Areas of Improvement

All in all, we need to start the improvement by doing a better job designing and checking the array beampattern. Also, we need a better algorithm for integration. For this algorithm, we need to know how much of a cycle is needed, how integration length affects accuracy, and how to deal with non-periodic signals. Finally, we need a better understanding and control over the room acoustics, as well as more time to fully test the algorithm.

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