Multi-Purpose Acoustic Target Tracking For Additive Situational Awareness
Latasha Solomon · Defense Technical Information Center (DTIC) · 2008
The U.S. Army Research Laboratory (ARL) has successfully used acoustics to detect, localize, and track potential threats. This information has provided a wealth of information to the individual Soldier by supplying actionable situational awareness. Two particular scenarios where these algorithms would provide useful intelligence relate to collision avoidance and monitoring drug trafficking. This research analyzes the acoustic signals of several aerial platforms in an attempt to track each target of interest. Results of different signal-processing techniques conventional beamformer via minimum variance distortionless response (MVDR) and a Least-Squares (L-S) Estimator using time difference of arrivals (TDOA) are compared and contrasted. Application of a Kalman filter to the direction of arrival (DOA) estimates is explored. The results found that although neither algorithm performed flawlessly, the TDOA L-S method required less computation time and the MVDR algorithm produced more accurate tracking. The Kalman filter also improved results when used with both techniques.