Wooyoung Hong

Performance comparison of target localization for active sonar systems

The performance comparison of target localization for active sonar and effective fusion algorithms for target localization of multistatic sonar is investigated. Active sonar can be categorized into monostatic, bistatic, and multistatic, depending on the number of receiver elements. Target localization performance depends on the system configuration. The target localization performance of the monostatic, bistatic, and multistatic sonar systems is compared assuming that each element can receive both range and azimuth information of the target. In addition, we propose the weighted least square (WLS) algorithm, which incorporates judicial weighting to the conventional least square (LS) method, and an efficient sensor arrangement rule for target localization in the multistatic sonar system. The representative experimental results demonstrate that the target localization performance of multistatic sonar configuration is superior in terms of root-mean-square error (RMSE), to monostatic sonar and bistatic sonar by 35.98% and 37.45%, respectively, while the proposed WLS algorithm showed an improvement of 2.27% compared with the LS method.

Enhancing model composability and reusability for entity-level combat simulation: A conceptual modeling approach:

This paper presents a conceptual model design for entity-level combat simulation to enhance model composability and reusability. For conceptual modeling, we first describe the following three problem situations: (1) joint design of logical/physical modeling; (2) flexible model modification during scenario extension; and (3) cooperative modeling with different domain experts. To this end, we propose a two-dimensional model partition method for a combat entity, which partitions the combat entity depending on the functional aspect horizontally and the abstract level vertically. Thus, the proposed method guarantees transparent simplification of the combat entity and facilitates flexible model composition when simulating in the integration and the interoperation environments. Based on the proposed conceptual modeling, empirical measurements demonstrate the enhancement of model composability and reusability during scenario extension for anti-submarine warfare from static decoy to mobile decoy and from pattern-running torpedo to wire-guided torpedo simulations.

Suppressing Ghost Targets via Gating and Track History in Y-Shaped Passive Linear Array Sonars

In Y-shaped passive linear array sonar (PLAS) systems composed of 3 sensor legs with consecutively missed detections in a full scan, the complex ghosts that occur due to bearing ambiguity seriously deteriorate the target tracking performance. A solution to the ghost problem is proposed which exploits the track information and geometrical relationship between each PLAS leg and the target. The region of possible ghost targets is first established by making use of the geometrical relationship of the PLAS with respect to the target. The ghost targets are then eliminated by means of the updated track information refined via a combination of 3-D assignment with gating and judicial track management. In the track management and gating procedure, we propose an optimal measurement selection criterion based on maximum joint probability data association (MJPDA), which combines both the soft and hard association techniques. The established tracks are updated by the Kalman filter with MJPDA and are terminated with a logic-based procedure. Representative simulations demonstrate the effectiveness of the proposed approach.

Modeling and Analysis of Monostatic Seafloor Reverberation from Bottom Consisting of Two Slopes

An incoherent reverberation from a continental shelf was simulated using a propagation model based on ray theory combined with several scattering strength formulas. The concept of an N × 2D reverberation model is used to consider azimuthal and radial dependent bottom. For verification of the reverberation model, the result is compared to consensus solutions of problem XI in Reverberation Modeling Workshop I (RMW I). Subsequently, the model is applied to one of data-inspired problems in Reverberation Modeling Workshop II (RMW II). Scattering strength formulas based on the Kirchhoff approximation (KA) and small slope approximation (SSA) are adapted to be applicable to a von Karman roughness spectral form. The monostatic reverberations on the continental shelf are observed at 200 Hz and 1600 Hz for various scattering cross-sections. The results with SSA scattering cross-section are examined to analyze the features of continental shelf reverberation depending on the sound speed profile and bottom slope, and they are found to affect both the pattern and level of reverberations.

An Adaptive Time Delay Estimation Method Based on Canonical Correlation Analysis

The localization of sources has a numerous number of applications. To estimate the position of sources, the relative delay between two or more received signals for the direct signal must be determined. Although the generalized cross-correlation method is the most popular technique, an approach based on eigenvalue decomposition (EVD) is also popular one, which utilizes an eigenvector of the minimum eigenvalue. The performance of the eigenvalue decomposition (EVD) based method degrades in the low SNR and the correlated environments, because it is difficult to select a single eigenvector for the minimum eigenvalue. In this paper, we propose a new adaptive algorithm based on Canonical Correlation Analysis (CCA) in order to extend the operation range to the lower SNR and the correlation environments. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue in the generalized eigenvalue decomposition (GEVD). The estimated eigenvector contains all the information that we need for time delay estimation. We have performed simulations with uncorrelated and correlated noise for several SNRs, showing that the CCA based algorithm can estimate the time delays more accurately than the adaptive EVD algorithm.

Effectiveness Analysis for a Lightweight Torpedo Considering Evasive Maneuvering and TACM of a Target

In the development phase of a torpedo, the effectiveness analysis is carried out to predict the performance and to learn how to use the torpedo. In order to obtain reliable data, it is required to model the tactical situation closely to the actual one. Because the submarine is a target of a lightweight torpedo, the anti-torpedo countermeasures of a submarine such as evasive maneuvering and TACM (Torpedo Acoustic Counter Measure) should be modeled in detail. In this paper, the evasive maneuvering is modeled reflecting the movement characteristics of the submarine. Furthermore various TACMs such as a floating-type decoy, a self-propelled decoy and jammers are also modeled. Then, effectiveness of a lightweight torpedo is measured and analyzed using the simulation program which is developed through the above modeling procedure.

Statistics on noise covariance matrix for covariance fitting-based compressive sensing direction-of-arrival estimation algorithm: For use with optimization via regularization.

A covariance fitting algorithm for the estimation of direction-of-arrivals of multiple incident signals is addressed in this paper. The scheme takes advantage of the fact that the incident signals are spatially sparse. A previous study has presented the regularization parameters of the covariance fitting for a very large number of snapshots. In this paper, a strategy on how to determine the regularization constant of the covariance fitting for a general number of snapshots is presented. The strategy essentially exploits the norm of the noise covariance matrix. The proposed algorithm has been validated via numerical simulations.

Target motion analysis with evolutionary search by fusion of two moving acoustic sensors

This paper focuses on target motion analysis by fusion of information from two moving acoustic sensors. These two sensors may obtain small measurements in order to make quick analysis of moving targets. In this situation, conventional approaches often fail to find accurate motion of targets. In this paper, a fusion algorithm for target motion analysis designed to handle this situation is proposed. First, optimization based PSO is applied in order to find accurate initial motion of targets. Second, the target trajectory is estimated via a sequential fusion algorithm based on UKF. According to the various simulated results, the effectiveness of the proposed method is then verified.

Approximation of a Warship Passive Sonar Signal Using Taylor Expansion

A passive sonar of warship is composed of several directional or omni-directional sensors. In order to model the acoustic signal received into a warship sonar, the wave propagation modeling is usually required from arbitrary noise source to all sensors equipped to the sonar. However, the full calculation for all sensors is time-consuming and the performance of sonar simulator deteriorates. In this study, we suggest an asymptotic method to estimate the sonar signal arrived to sensors adjacent to the reference sensor, where it is assumed that all information of eigenrays is known. This method is developed using Taylor series for the time delay of eigenray and similar to Fraunhofer and Fresnel approximation for sonar aperture. To validate the proposed method, some numerical experiments are performed for the passive sonar. The approximation when the second-order term is kept is vastly superior. In addition, the error criterion for each approximation is provided with a practical example.

Robust localization of moving object via fusion of TDOA and detection range measurements of acoustic sensors

In this paper, an area based method to estimate the position of unidentified moving objects by fusion of heterogeneous sensor data collected from a distributed acoustic sensor network is proposed. The surveillance region considered is composed of a couple of transmitters and multiple binary sensors which are assumed to be located in lattice formation. Each binary sensor may only determine whether or not an object was detected and the time difference of arrival (TDOA) between transmitting signals and object reflected signals. The proposed method estimates the candidate regions in which the object may be located from these two types of data and progressively fuses the regions into a single common region. Then with this common candidate region, the position of the object is estimated by Maximum Likelihood Estimation (MLE). The relevant experimental results demonstrate that the performance and effectiveness of the proposed method are superior compared with the conventional approaches.