Application of acoustic sensors in Persistent Surveillance Systems (PSS) has received considerable attention over the last
two decades because they can be rapidly deployed and have low cost. Conventional utilization of acoustic sensors in PSS
spans a wide range of applications including: vehicle classification, target tracking, activity understanding, speech
recognition, shooter detection, etc. This paper presents a current survey of physics-based acoustic signature classification
techniques for outdoor sounds recognition and understanding. Particularly, this paper focuses on taxonomy and ontology
of acoustic signatures resulted from group activities. The taxonomy and supportive ontology considered include: humanvehicle,
human-objects, and human-human interactions. This paper, in particular, exploits applicability of several
spectral analysis techniques as a means to maximize likelihood of correct acoustic source detection, recognition, and
discrimination. Spectral analysis techniques based on Fast Fourier Transform, Discrete Wavelet Transform, and Short
Time Fourier Transform are considered for extraction of features from acoustic sources. In addition, comprehensive
overviews of most current research activities related to scope of this work are presented with their applications.
Furthermore, future potential direction of research in this area is discussed for improvement of acoustic signature
recognition and classification technology suitable for PSS applications.