# My primary research interests lie in the area of **Acoustics** and **Array Signal Processing**.
I have worked on many interdisciplinary projects in different areas such as Underwater Acoustics, Bioacoustics, Acoustical Imaging, Room Acoustics, etc.

# Please click on a topic for more information.

__Array Signal Processing__

__Array Signal Processing__

# Array Signal Processing is a research area that uses the data collected by an array of receivers to extract knowledge about the source signal and its location. In my research, I have worked on source signal reconstruction, sound source localization, and beamforming.

**Broadband Sparse-Array Beamforming **

** Reconstructing the Source Signal (Blind Deconvolution)**

** Sound Source Localization using a Vertical Array**

## Remote sound source localization using a vertical array

# Synthetic Time Reversal (STR) can be used to estimate simultaneously the source signal and impulse response waveforms from a remote unknown source. Unfortunately, the unknown time shift in the reconstructed waveforms prevents elementary
distance-equals-speed-times-time estimation of the source-array range. However, the relative timing between peaks in the STR impulse response can be used to estimate the source range and depth when some environmental
information is available.

# As a preliminary step, the correspondence between ray-path arrival angles (from beamforming outputs) and impulse response peaks must be determined. Once all possible ray path arrival angles have been considered,
the arrival angles and STR-estimated relative time shifts for the various paths connecting the source and the array are known. In a multipath environment, this angle and timing information is a signature of the source
location, and this location may be estimated when there is enough environmental information for propagation calculations.

# Figure below illustrates propagation results via the plane-wave beamforming output, from the experiment explained in Synthetic Time Reversal section, at a source-array ranges of 100 m. At this source-array range, the direct path at 5° and
surface-reflected path at 30° show up clearly throughout the signal bandwidth, while a weaker bottom reflection at –34° is also apparent.

#

# The ray-based back-propagation technique is based on acoustic time reversal (or phase conjugation in the frequency domain). First, the environmental information and the ray arrival angles are used to compute 3 rays launched at angles (which can be found from beamformer output shown in figure above) starting from the center of the array and extending out to the largest array-source range of interest, about 600 m in the current investigation. Next, the STR-determined impulse response is idealized as a series of perfect impulses that occur with the STR-determined arrival-time differences. This series of impulses is then time reversed and each impulse is launched along its associated ray path from the array. As the various impulses, located at range-depth coordinates (r_{m}, z_{m}) propagate away from the array along their corresponding rays, the root-mean-square (rms) impulse position, based on Euclidian distances from the impulse centroid, is monitored. The centroid location with the minimum value within the domain of interest provides an estimate of the source location. An example of such a ray-based back-propagation calculation is shown on figure below where the impulse positions are shown for three different times. In this figure, the array is on the left at r = 0 and the three rays emerge from the array-center depth of 33.5 m. In this case, a global minimum is occurs when the impulse centroid is located at (27m, 100m) when the source was actually located at (30m, 100m).

#

# The root-mean-square (rms) impulse position, based on Euclidian distances from the impulse centroid, is shown below. Here, the actual source location is at 100m range. the minimum occurs at 100m range, too. The other two local minimums corresponds to the other two intersections of ray paths (shown in ray trace plot)

#

# More details in:
**Shima H. Abadi**, Daniel Rouseff, David R. Dowling: "Blind deconvolution for robust signal estimation and approximate source ranging", Journal of the Acoustical Society of America, Vol.131, Issue 4.
[Link]

** Sound Source Localization using a Long Horizontal Array**

**Broadband Sparse-Array Beamforming****Reconstructing the Source Signal (Blind Deconvolution)****Sound Source Localization using a Vertical Array**## Remote sound source localization using a vertical array

# Synthetic Time Reversal (STR) can be used to estimate simultaneously the source signal and impulse response waveforms from a remote unknown source. Unfortunately, the unknown time shift in the reconstructed waveforms prevents elementary distance-equals-speed-times-time estimation of the source-array range. However, the relative timing between peaks in the STR impulse response can be used to estimate the source range and depth when some environmental information is available.

# As a preliminary step, the correspondence between ray-path arrival angles (from beamforming outputs) and impulse response peaks must be determined. Once all possible ray path arrival angles have been considered, the arrival angles and STR-estimated relative time shifts for the various paths connecting the source and the array are known. In a multipath environment, this angle and timing information is a signature of the source location, and this location may be estimated when there is enough environmental information for propagation calculations.

# Figure below illustrates propagation results via the plane-wave beamforming output, from the experiment explained in Synthetic Time Reversal section, at a source-array ranges of 100 m. At this source-array range, the direct path at 5° and surface-reflected path at 30° show up clearly throughout the signal bandwidth, while a weaker bottom reflection at –34° is also apparent.

# The ray-based back-propagation technique is based on acoustic time reversal (or phase conjugation in the frequency domain). First, the environmental information and the ray arrival angles are used to compute 3 rays launched at angles (which can be found from beamformer output shown in figure above) starting from the center of the array and extending out to the largest array-source range of interest, about 600 m in the current investigation. Next, the STR-determined impulse response is idealized as a series of perfect impulses that occur with the STR-determined arrival-time differences. This series of impulses is then time reversed and each impulse is launched along its associated ray path from the array. As the various impulses, located at range-depth coordinates (r_{m}, z_{m}) propagate away from the array along their corresponding rays, the root-mean-square (rms) impulse position, based on Euclidian distances from the impulse centroid, is monitored. The centroid location with the minimum value within the domain of interest provides an estimate of the source location. An example of such a ray-based back-propagation calculation is shown on figure below where the impulse positions are shown for three different times. In this figure, the array is on the left at r = 0 and the three rays emerge from the array-center depth of 33.5 m. In this case, a global minimum is occurs when the impulse centroid is located at (27m, 100m) when the source was actually located at (30m, 100m).

# The root-mean-square (rms) impulse position, based on Euclidian distances from the impulse centroid, is shown below. Here, the actual source location is at 100m range. the minimum occurs at 100m range, too. The other two local minimums corresponds to the other two intersections of ray paths (shown in ray trace plot)

# More details in:
**Shima H. Abadi**, Daniel Rouseff, David R. Dowling: "Blind deconvolution for robust signal estimation and approximate source ranging", Journal of the Acoustical Society of America, Vol.131, Issue 4.
[Link]

**Shima H. Abadi**, Daniel Rouseff, David R. Dowling: "Blind deconvolution for robust signal estimation and approximate source ranging", Journal of the Acoustical Society of America, Vol.131, Issue 4. [Link]**Sound Source Localization using a Long Horizontal Array**__Acoustical Imaging__

__Acoustical Imaging__

# Acoustic signals received by an array of receivers can be used for imaging and sound source localization. In my research, I have developed a novel beamforming technique which has higher resolution compared to the existing methods. The main application of this method is biomedical imaging.

__Whale Localization__

__Whale Localization__

# The localization of marine mammals is important for biological studies and for assessments of the impact of anthropogenic activities on the marine environment. Passive acoustic monitoring (PAM) has become an increasingly popular method for localizing certain marine mammal species that are acoustically active. I have used both vertical and horizontal hydrophone arrays to find the location of Baleen whales.

**Ranging of Bowhead Whale Calls using a Vertical Array****Ranging of Baleen Whale Calls using a Long Horizontal Array**

__Animal Bioacoustics__

__Animal Bioacoustics__

**Studying the Impact of Seismic Reflection Surveys on Baleen Whales (coming soon)**