Sergey Simakov

Sensor scheduling for target tracking in large multistatic sonobuoy fields

Sonobuoy fields, consisting of many distributed emitter and receiver sonar sensors on buoys, are used to seek and track underwater targets in a defined search area. A sensor scheduling algorithm is required in order to optimise tracking performance by selecting which emitter sonobuoy should transmit in each time interval, and which waveform it should use. In this paper we describe a new long term sensor scheduling algorithm for sonobuoy fields, called the continuous probability states algorithm. This algorithm reduces the scheduling search space by keeping track of the probability that a target is undetected, rather than modelling all possible detection outcomes, which reduces the computation complexity of the algorithm. It is shown that this approach results in high quality tracking for multiple targets in a simulated sonobuoy field.

GPU acceleration of Threat Map computation and application to selection of sonar field controls

The Threat Probability Density Map displays the outcomes of the search effort prior to detection and is a digital representation of the probability density function of location of the existing undetected threat. The Threat Map readily provides such diagnostics as the probabilities of the threat being present in different areas of interest and this information can be utilised in selection of sensor field controls. In this work we consider a GPU acceleration of the Monte-Carlo technique for Threat Map computation and discuss application to sonobuoys.

Optimal beamforming on synthetic interference and noise for active processing of multiplet line arrays

Optimal beamforming on synthetic noise and interference is a flexible and intuitive technique for shaping beam patterns. In this method, suppression of arrivals from undesirable directions is achieved through introduction of synthetic interferences and optimal beamforming using the resulting noise-interference covariance matrix. We apply this approach to a general multiplet line array and test the algorithm on representative multi-channel time-series obtained for a quadruplet line array.