A steganographic approach to sonar tracking

Steganographic transmission waveforms are desirable for many applications, such as underwater acoustic communications, surveillance, detection, and tracking. In the context of active sonar tracking, an overall approach is presented that covers several topics including background sound modeling, steganographic security assessment of transmission waveforms, target motion modeling, and batch track detection. In shallow water, environment background sound dominated by snapping shrimp, the presented approach shows feasibility of steganographic sonar for target track detection. A background sound modeling approach is presented that utilizes symbolic time-series analysis with phase space representation and clustering of time-series segments. The time-evolving characteristics are captured with a hidden Markov model. Steganographic security of the transmission waveform can be assessed by measuring the Kullback-Leibler divergence between the cover model and the stego model. Conventional tracking approaches fail to perform reliably and existing track-before-detect approaches also fail due to overwhelming search computation when they use simplistic short timescale motion models. A long timescale target motion model with considerations for plausibility is presented and utilized in a batch track detection approach. A Monte-Carlo-based simulation is performed to find the scenarios that demonstrate the feasibility of steganographic sonar in a shallow water environment with snapping shrimp sound.