# A Wide-Area Deep Ocean Floor Mapping System: Design and Sea Tests
## 3 Sparse-Aperture Sonar: Scaled Tank Test  
To demonstrate that a large sparse-aperture sonar could be made and the sidelobe issue could be mitigated by appropriate array design and signal processing, we built a proof-of-principle sonar in a test tank. The sonar consists of 43 transducers that operate at 200 kHz across a 1.5 m aperture. The array is effectively 200 wavelengths in each direction, and with only 43 transducers, it is very sparse. Figure 7 shows a picture of the sparse sonar array above the test tank and example imagery. In preparation for the oceangoing system, given that acoustic projectors are significantly more expensive than hydrophones (\(\sim\)20\(\times\) more), the system was biased toward many \"receive\" channels and few \"transmit\" channels. All beamforming and timing are performed on the receive side. The system has a custom data acquisition system that samples at 1.67 Msps, and all transmitters have loopbacks. Figure 6: Illustrations of ray tracing in range migration, and the effect of varying the diffuse parameter (\(\mu\)) in [PERSON] and Crowe bistatic scattering filter application. To generate the imagery from the acoustic data collected in the tank, we employed our custom signal-processing chain and imaging algorithms presented in Section 2. Figure 7 shows sample imagery of a 10 cm MIT LL logo positioned 10 cm above the tank bottom. The features of the logo are about 9 mm wide, and the acoustic wavelength is about 8 mm, so resolving the finer details of the logo is not expected. However, the overall extent is readily apparent. The imaging algorithms were compared to attain the sharpest image. Because of the vast volume of 3D, high-resolution data to be processed and limited computing power, we sought an algorithm that produced suitable images at the minimum possible computational expense. In each of the following cases, after processing the data, we set data thresholds such that voxels with energy less than \(\epsilon_{\text{thresh}}\) dB of the maximum are treated as noise and not shown. We started by comparing the two different algorithms referenced in Section 2.2 in Figure 8: Kirchhoff migration and diffraction stack imaging. We used 0.5 cm resolution for this experiment and smoothed the data with a \(3\times 3\times 3\) box filter. For Kirchhoff migration and diffraction stack imaging, we set \(\epsilon_{\text{thresh}}=-14\) and \(-9\) dB, respectively. Because Kirchhoff migration incorporates angular information, it produced far superior results to the diffraction stack. Next, we considered the different scattering models discussed in Section 2.2. We processed the data using [PERSON] [PERSON]'s [28], [PERSON]'s [21], and [PERSON]'s [27] scattering models, in addition to not using any scattering model at all with thresholds \(\epsilon_{\text{thresh}}=-14,-14,-14\), and \(-22\) dB, respectively. In this experiment, we used a 0.1 cm resolution with a \(15\times 15\times 15\) box filter to give an equivalent smoothed volume. Figure 9  
Figure 8: A comparison of the results of Kirchhoff migration (**a,b**) and diffraction stack (**c,d**) imaging, with (**a,c**) showing 3D visualizations and (**b,d**) showing a top-down view. Kirchhoff migration successfully localizes the LL logo, while the diffraction stack produces a smoothed image. Figure 7: (**a**) The 200 kHz sparse aperture sonar array above the test tank and (**b**) CAD model of the target and acoustic reconstruction example. shows the results of each scattering model. The [PERSON] and Crowe bistatic model and Phong model outperform the others; however, we note that the scattering models have tunable parameters, and [PERSON] model results for the tank data can improve with further optimization. Nevertheless, this experiment demonstrates the importance of an appropriate scattering model in 3D imaging. Finally, using the [PERSON] and Crowe bistatic scattering model, we determined at what resolution to process the data. Our goal was to find the minimum resolution such that no discernible details were lost.