Performance Analysis of Communication Signals for Localization in Underwater Sensor Networks

Abstract

Efficient localization in underwater sensor networks faces challenges due to limited bandwidth, energy constraints, and hardware complexity. Traditional systems separate sensing and communication, often resulting in inefficient resource usage. To address this, integrated sensing and communication (ISAC) has emerged, leveraging shared waveforms for both functions. This paper investigates the feasibility of using communication-centric waveforms for underwater localization. Specifically, we evaluate the performance of super-permutated frequency shift keying and multiple frequency shift keying signals using a Cramer-Rao lower bound framework in a simplified bistatic scenario. Simulations incorporate temporally correlated autoregressive AR(1) noise and varying signal-to-noise ratio levels to assess localization accuracy. A comparative analysis with a traditional sonar waveform, linear frequency modulated signal, highlights the potential of communication signals for dual-purpose ISAC applications in bistatic sonar configurations in underwater environments.