Study Shows How Sensor Helps to Predict Shooter Localization Accuracy in Urban Areas

Two sound events occur during a gunshot: the muzzle explosion and the supersonic shock wave. Acoustic sensors, including single or arrays of microphones, can pick up these sounds and use them to estimate a shooter’s location.

Study Shows How Sensor Helps to Predict Shooter Localization Accuracy in Urban Areas.
Luisa Still, of Sensor Data and Information Fusion, will discuss the important factors in determining shooter localization accuracy at the 182nd ASA Meeting. Image Credit: Luisa Still.

Luisa Still of Sensor Data and Information Fusion will speak at the 182nd Conference of the Acoustical Society of America at the Sheraton Denver Downtown Hotel on the critical aspects of determining shooter localization accuracy. Still’s presentation will be held on May 23rd, 2022 at 12:45 PM Eastern US time.

Buildings and other impediments in an urban setting may reflect, refract and trap sound waves. The interaction of these factors can have a significant impact on the accuracy of shooter localization. Predicting this precision in advance is critical for mission planning in urban contexts since it can determine the number of sensors required, as well as their needs and placements.

Still and her research colleagues modeled acoustic sensor readings using geometric factors. Researchers were able to derive a prediction of localization accuracy using this modeling and information on sensor properties, sensor-to-shooter geometry, and the urban environment.

In our approach, the prediction can be interpreted as an ellipse-shaped area around the true shooter location. The smaller the ellipse-shaped area, the higher the expected localization accuracy.

Luisa Still, Sensor Data and Information Fusion

The researchers compared their accuracy predictions to experimental results using different geometries, weaponry, and sensor kinds. The sensor-to-shooter geometry and shot direction of the sensor network had a substantial impact on localization accuracy. The closer the shooting line is to a sensor, the more accurate their source prediction will be. Adding more sensors improved accuracy, but there were diminishing returns after a while.

Each urban environment is too individual (e.g., in terms of layout, building types, vegetation) to make a general recommendation for a sensor set up. This is where our research comes in. We can use our approach to recommend the best possible setup with the highest accuracy for a given location or area.

Luisa Still, Sensor Data and Information Fusion

Journal Reference:

Still, L. and Oispuu, M. (2022) Prediction of shooter localization accuracy in an urban environment. The Journal of the Acoustical Society of


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