P. R. Saseendran Pillai

Discrete Sine Transform based HMM underwater signal classifier

Underwater target recognition and classification has been a field of considerable importance due to its multidimensional applications. Much attention has been focused on this area and various underwater signal processing schemes have been devised over the time. Hidden Markov Models, because of their robustness, provide an effective architecture for the classification of underwater noise sources. A methodology is presented, in this paper, for the design and performance analysis of an HMM based underwater signal classification system, utilizing the Discrete Sine Transform based target specific features. Simulation results have been presented for typical underwater noise waveforms, such as Boat and Dolphin noises.

RMAC-M: Extending the R-MAC protocol for an energy efficient, delay tolerant underwater acoustic sensor network application with a mobile data mule node

One of the major applications of underwater acoustic sensor networks (UWASN) is ocean environment monitoring. Employing data mules is an energy efficient way of data collection from the underwater sensor nodes in such a network. A data mule node such as an autonomous underwater vehicle (AUV) periodically visits the stationary nodes to download data. By conserving the power required for data transmission over long distances to a remote data sink, this approach extends the network life time. In this paper we propose a new MAC protocol to support a single mobile data mule node to collect the data sensed by the sensor nodes in periodic runs through the network. In this approach, the nodes need to perform only short distance, single hop transmission to the data mule. The protocol design discussed in this paper is motivated to support such an application. The proposed protocol is a hybrid protocol, which employs a combination of schedule based access among the stationary nodes along with handshake based access to support mobile data mules. The new protocol, RMAC-M is developed as an extension to the energy efficient MAC protocol R-MAC by extending the slot time of R-MAC to include a contention part for a hand shake based data transfer. The mobile node makes use of a beacon to signal its presence to all the nearby nodes, which can then handshake with the mobile node for data transfer. Simulation results show that the new protocol provides efficient support for a mobile data mule node while preserving the advantages of R-MAC such as energy efficiency and fairness.

Localisation of underwater targets using sensor networks

Precise localisation and tracking of underwater targets in regimes like oceanography, fisheries and military applications is of prime importance owing to various phenomena that impede the accuracy of physical measurements. An approach for localisation of unknown underwater targets using a minimally configurable, three buoy sensor networks using passive listening concepts has been prototyped. The system comprises three sensor nodes, each consisting of mechanically steerable hydrophone array and support electronics. The sensor system picks up the noise emanations from the targets of interest and the hydrophone array of each node gets aligned to the Direction of maximum signal Arrival DOA. Using the DOAs measured, the distances of the target from the three nodes are computed. The prototype localiser model has been field tested and the validation tests yielded encouraging results within the limits of theoretical approximations and measurement errors, which necessitated the need for refining the estimates using Kalman filter.

Cost effective sensor buoy for ocean environmental monitoring

A low cost prototype sensor module comprising of a microcontroller and digital sensors for measuring the temperature, light as well as pressure, housed in a miniaturized buoy similar to a Sonobuoy has been developed for sampling the sea surface temperature, light intensity and sea level changes respectively. This standalone data logger module is interfaced with a ZigBee module, allowing addressable secure communication, for real time transfer of the parameters to a shore station, which will have a very good correlation with climate. The sensor module yielded satisfactory results during the field trials carried out in a hydroelectric reservoir with a small reduction in the measured values due to the encapsulation. An RF link was also established between the buoy and the shorestation and its performance was evaluated.

Development of (3,1) drive low‐frequency piezofilm hydrophones with improved sensitivity

Piezopolymers are becoming popular as the active material for the design of probes for sensing ultrasonic fields and quantitative determination of acoustic field parameters in water and biological media. A new innovative transducer design proposed here utilizes a poled piezofilm which is made to vibrate in (3,1) drive by a modified structural assembly. The voltage generated in this design is found to be greater compared to that in the conventional design, due to the concentration of acoustic pressure to a very small cross‐sectional area. The prototype design consists of a prestretched piezofilm fixed to a phosphor bronze diaphragm through a driver pin. The proposed design yielded sensitivities to the extent of −170 dB re: 1 V/μPa in water at around 1.5 kHz.

Deep learning architectures for underwater target recognition

Passive sonar target recognition is a challenging task due to the complex milieu of the ocean. Most of the state of the art target recognition systems depend on hand engineered feature extraction schemes in order to effectively represent the target signatures, based on expert knowledge. Due to the whimsical nature of the sources and medium, such feature engineering methods often fail to yield invariant features from the observations. In this paper, a deep unsupervised feature learning approach capable of capturing invariant features from the sensory signal stream through multi layered hierarchical abstraction has been adopted. These abstractions learned by the higher layers are mostly invariant and can be used as the discriminative features for the purpose of classification.

Tracking of a maneuvering underwater target

This paper elaborates a technique for improving the performance of a sensor network based system for tracking an abruptly maneuvering under water target. The results of tracking estimates of a maneuvering target may vary owing to various noises and interferences such as sensor errors and environmental noises. The conventional Kalman filter may induce unsatisfactory tracking errors when applied to the maneuvering target scenario, since the parameters of the filter cannot adapt itself to the highly maneuvering target. In this simulation study, a decision based maneuvering detection which depends on the chi-square significance test of the measurement residuals has been exercised. Upon detection of the maneuvering, the Kalman filter is reinitialized by resetting the parameters for improving the maneuvering target tracking estimates.

Improving the localization estimates using Kalman filters

Localization of underwater targets is an important requirement in surveillance operations. A method for improving the accuracy of the estimated location of an unknown target using Kalman filters is presented in this paper. The localisation is carried out using a sensor network comprising of three fixed surface buoy systems, each consisting of steerable hydrophone arrays and support electronics, positioned at the vertices of a triangle. The system picks up the noise emanations from the targets of interest and the hydrophone arrays of each node gets aligned to the direction of maximum signal arrival (DOA). Using the DOAs measured at each buoy system, the distances of the target from the three nodes are computed using the triangulation technique.

Prototype archival tags for studying the migratory routes of tuna

Archival electronic tags can be used for studying the migratory patterns of tuna, identifying their feeding and spawning grounds, etc. The size of the tag has to be miniaturized, to the extent possible so that by way of attaching such devices the swimming and natural behaviour of the tagged species remain unaffected. The design and development prototype archival tags for sampling the physical parameters of the ocean such as pressure, temperature and light intensity at preset intervals of time is presented in this paper. The tag has been encapsulated and its performance validated in the laboratory as well as in an open test facility in a reservoir.

Development of a hardware based underwater target identification system

An underwater target identification system comprising of a sensing element signal conditioner and a digital signal processor used for identifying targets of interest is presented in this paper. The sensing element picks up the noise waveforms emanating from the targets and the signal conditioner pre-processes and filters the captured signal into the desired spectral band for signal analysis. Signature features of the captured signal are extracted using the power spectral statistics implemented in a digital signal processing hardware. The features extracted are then compared with those available in the knowledge base, using pattern matching techniques, leading to the identification of underwater targets.