In this paper, experimental results are presented on the performance of a new underwater communication compact multichannel receiver that utilizes a sphere vector sensor. It measures the x, y and z underwater particle velocity field components, and utilizes them for symbol recovery. Comparison of the sphere vector sensor experimental data with those collected using a scalar sensor receiver suggests that the multichannel nature of the sphere vector sensor receiver can provide a performance improvement for underwater communication. As another result, statistical analysis of the measured underwater particle velocity channels suggests the Student-t distribution as a suitable distribution to characterize such channels. This is useful in studies where a statistical model for the particle velocity channels is needed.

The largely unexplored underwater world has strong and multifaceted ties with our lives. There are numerous ocean-related areas and applications, such as oceanography, climate, pollution, and environmental monitoring, that have created increasing demand for wireless acoustic data communication among underwater sensors, platforms, and autonomous vehicles. Contrary to wireless transmission in air, electromagnetic waves are strongly attenuated in water, whereas acoustic waves are proper carriers of information in water, since compared to electromagnetic waves, they typically incur less attenuation in water. However, the underwater bandwidth is usually highly limited. Here, we demonstrate that it is possible to multiplex multiple data streams over acoustic particle velocity field components using a proposed compact vector transmitter over the same bandwidth. In existing underwater communication systems, data are conventionally modulated on acoustic pressure, i.e., scalar component of the acoustic field, using one scalar transmitter. Arrays of several spatially-separated scalar transmitters are also used to transmit multiple data streams simultaneously. However, given the large size of equipment carrying an array of several transmitters, many modern underwater platforms, such as autonomous underwater vehicles, cannot use multiple transmitters. Our experimental results demonstrate that using the developed vector transmitter, together with the proposed physics-based particle velocity modulation method over co-located underwater vector field components, multiple data streams can be concurrently transmitted, without requiring additional bandwidth. Using our findings, small-size underwater acoustic systems, modems, and equipment can be built that benefit from the acoustic vector field components.

Signal acquisition and sensing in underwater systems and applications is typically a challenging issue due to the small signal strength within the background noise. Here, we present a ring vector sensor communication receiver that can significantly improve signal acquisition, by utilizing the underwater acoustic vector field components, compared to the scalar component. The vector sensor receiver is a multichannel receiver that measures particle velocities, which are vector components of the underwater acoustic field, in addition to the scalar field component. According to the combination of our measured experimental data with our signal acquisition performance analysis, the introduced ring vector sensor receiver exhibits higher signal acquisition probabilities for the vector components compared to the scalar component. This can be attributed to certain characteristics of the vector field components. Another advantage of this multichannel receiver is that combining all of its channels can further increase the signal acquisition and packet detection probability in underwater communication systems compared to a single-channel approach.

Underwater signal detection in shallow water needs to be able to handle several types of distortion. One is the time-spreading distortion (TSD), in which several replicas of the transmitted signal arrive at different times, as a result of the signal traveling over multiple propagation paths. In this article, we present a multichannel signal detector for TSD channels. The performance of the detector is first studied analytically, by deriving closed-form equations for the detection and false alarm probabilities of the multichannel detector in TSD channels. The detector's performance is further evaluated via computer simulations and underwater experiments. Two types of multichannel receivers are used in the underwater experiments. The first one is a sphere vector sensor that measures the vector components of the acoustic field, i.e., the x , y , and z acoustic particle velocities, as well as the scalar component of the acoustic field, that is, the acoustic pressure, whereas the second one is composed of scalar sensors, which are hydrophones that measure only the scalar component of the acoustic field. Our results indicate that, as the number of channels of the receiver increases, the detection probability in TSD channels increases and, furthermore, the detection probability becomes less dependent on the choice of the required number of correlators for each channel of the receiver. Given the multichannel nature of a small-size vector sensor, such a sensor can serve as an effective and compact multichannel signal detector in TSD channels. This can be of particular importance in small underwater platforms that have considerable size constraints.

This paper presents a blind passive signal detection method for underwater sparse time-spreading distortion (TSD) channels, employing a dictionary learning (DL) algorithm. This approach estimates and separates the unknown signal from the unknown channel impulse response. A log-likelihood ratio detector is derived and utilized for sparse TSD channels. Simulations and underwater experiments with a vector sensor are conducted to evaluate the performance of the proposed DL-based blind passive method and compare it with other approaches. The improved detection probabilities achieved by this blind method demonstrate its effectiveness in the detection of unknown signals within TSD channels.