Acoustic mapping of ocean currents using networked distributed sensors

Distributed underwater sensors are expected to provide oceanographic monitoring over large areas. As fabrication technology advances, low cost sensors will be available for many uses. The sensors communicate to each other and are networked using acoustic communications. This paper first studies the performance of such systems for current measurements using tomographic inversion approaches to compare with that of a conventional system which distributes the sensors on the periphery of the area of interest. It then proposes two simple signal processing methods for ocean current mapping (using distributed networked sensors) aimed at real-time in-buoy processing. Tomographic inversion generally requires solving a challenging high dimensional inverse problem, involving substantial computations. Given distributed sensors, currents can be constructed locally based on data from neighboring sensors. It is shown using simulated data that similar results are obtained using distributed processing as using conventional tomographic approaches. The advantage for distributed systems is that by increasing the number of nodes, one gains a much more improved performance. Furthermore, distributed systems use much less energy than a conventional tomographic system for the same area coverage. Experimental data from an acoustic communication and networking experiment are used to demonstrate the feasibility of acoustic current mapping.

Clutter reduction using Doppler sonar in a harbor environment

A high frequency experiment was conducted in the Woods Hole Harbor in Massachusetts to evaluate the effectiveness of Doppler sonar for discriminating targets from reverberation. Using a pulsed linear frequency modulated signal, one finds that the matched filtered outputs are filled with high-level discrete backscattered returns, referred to as clutter, which are often confused with the target echo. The high level non-target returns have an amplitude distribution that is heavy-tailed. Using a Doppler-sensitive binary-phase-shift-keying signal coded with an m-sequence, the target echo and clutter can be separated by Doppler and delay, and tracked using the Doppler spectrogram (Dopplergram). The Doppler filtered time series show a background reverberation with a Rayleigh-like amplitude distribution, with an improved signal-to-(peak) reverberation ratio compared with that without Doppler filtering. The reduced reverberation level with Doppler processing decreases the probability of false alarm (Pfa) for a given threshold level. Conversely, for a given Pfa, the higher signal-to-(peak) reverberation ratio implies a higher probability of detection. Transmission loss measurement was conducted to estimate some of the system parameters, e.g., the source level and target strength relative to the noise level.